Rethinking Indoor Localization Solutions Towards the Future of Mobile Location-Based Services
NASA Astrophysics Data System (ADS)
Guney, C.
2017-11-01
Satellite navigation systems with GNSS-enabled devices, such as smartphones, car navigation systems, have changed the way users travel in outdoor environment. GNSS is generally not well suited for indoor location and navigation because of two reasons: First, GNSS does not provide a high level of accuracy although indoor applications need higher accuracies. Secondly, poor coverage of satellite signals for indoor environments decreases its accuracy. So rather than using GNSS satellites within closed environments, existing indoor navigation solutions rely heavily on installed sensor networks. There is a high demand for accurate positioning in wireless networks in GNSS-denied environments. However, current wireless indoor positioning systems cannot satisfy the challenging needs of indoor location-aware applications. Nevertheless, access to a user's location indoors is increasingly important in the development of context-aware applications that increases business efficiency. In this study, how can the current wireless location sensing systems be tailored and integrated for specific applications, like smart cities/grids/buildings/cars and IoT applications, in GNSS-deprived areas.
a Schema for Extraction of Indoor Pedestrian Navigation Grid Network from Floor Plans
NASA Astrophysics Data System (ADS)
Niu, Lei; Song, Yiquan
2016-06-01
The requirement of the indoor navigation related tasks such emergency evacuation calls for efficient solutions for handling data sources. Therefore, the navigation grid extraction from existing floor plans draws attentions. To this, we have to thoroughly analyse the source data, such as Autocad dxf files. Then, we could establish a sounding navigation solution, which firstly complements the basic navigation rectangle boundaries, secondly subdivides these rectangles and finally generates accessible networks with these refined rectangles. Test files are introduced to validate the whole workflow and evaluate the solution performance. In conclusion, we have achieved the preliminary step of forming up accessible network from the navigation grids.
Indoor Pedestrian Navigation Using Foot-Mounted IMU and Portable Ultrasound Range Sensors
Girard, Gabriel; Côté, Stéphane; Zlatanova, Sisi; Barette, Yannick; St-Pierre, Johanne; van Oosterom, Peter
2011-01-01
Many solutions have been proposed for indoor pedestrian navigation. Some rely on pre-installed sensor networks, which offer good accuracy but are limited to areas that have been prepared for that purpose, thus requiring an expensive and possibly time-consuming process. Such methods are therefore inappropriate for navigation in emergency situations since the power supply may be disturbed. Other types of solutions track the user without requiring a prepared environment. However, they may have low accuracy. Offline tracking has been proposed to increase accuracy, however this prevents users from knowing their position in real time. This paper describes a real time indoor navigation system that does not require prepared building environments and provides tracking accuracy superior to previously described tracking methods. The system uses a combination of four techniques: foot-mounted IMU (Inertial Motion Unit), ultrasonic ranging, particle filtering and model-based navigation. The very purpose of the project is to combine these four well-known techniques in a novel way to provide better indoor tracking results for pedestrians. PMID:22164034
An indoor navigation system for the visually impaired.
Guerrero, Luis A; Vasquez, Francisco; Ochoa, Sergio F
2012-01-01
Navigation in indoor environments is highly challenging for the severely visually impaired, particularly in spaces visited for the first time. Several solutions have been proposed to deal with this challenge. Although some of them have shown to be useful in real scenarios, they involve an important deployment effort or use artifacts that are not natural for blind users. This paper presents an indoor navigation system that was designed taking into consideration usability as the quality requirement to be maximized. This solution enables one to identify the position of a person and calculates the velocity and direction of his movements. Using this information, the system determines the user's trajectory, locates possible obstacles in that route, and offers navigation information to the user. The solution has been evaluated using two experimental scenarios. Although the results are still not enough to provide strong conclusions, they indicate that the system is suitable to guide visually impaired people through an unknown built environment.
An Indoor Navigation System for the Visually Impaired
Guerrero, Luis A.; Vasquez, Francisco; Ochoa, Sergio F.
2012-01-01
Navigation in indoor environments is highly challenging for the severely visually impaired, particularly in spaces visited for the first time. Several solutions have been proposed to deal with this challenge. Although some of them have shown to be useful in real scenarios, they involve an important deployment effort or use artifacts that are not natural for blind users. This paper presents an indoor navigation system that was designed taking into consideration usability as the quality requirement to be maximized. This solution enables one to identify the position of a person and calculates the velocity and direction of his movements. Using this information, the system determines the user's trajectory, locates possible obstacles in that route, and offers navigation information to the user. The solution has been evaluated using two experimental scenarios. Although the results are still not enough to provide strong conclusions, they indicate that the system is suitable to guide visually impaired people through an unknown built environment. PMID:22969398
Comparing the Performance of Indoor Localization Systems through the EvAAL Framework.
Potortì, Francesco; Park, Sangjoon; Jiménez Ruiz, Antonio Ramón; Barsocchi, Paolo; Girolami, Michele; Crivello, Antonino; Lee, So Yeon; Lim, Jae Hyun; Torres-Sospedra, Joaquín; Seco, Fernando; Montoliu, Raul; Mendoza-Silva, Germán Martin; Pérez Rubio, Maria Del Carmen; Losada-Gutiérrez, Cristina; Espinosa, Felipe; Macias-Guarasa, Javier
2017-10-13
In recent years, indoor localization systems have been the object of significant research activity and of growing interest for their great expected social impact and their impressive business potential. Application areas include tracking and navigation, activity monitoring, personalized advertising, Active and Assisted Living (AAL), traceability, Internet of Things (IoT) networks, and Home-land Security. In spite of the numerous research advances and the great industrial interest, no canned solutions have yet been defined. The diversity and heterogeneity of applications, scenarios, sensor and user requirements, make it difficult to create uniform solutions. From that diverse reality, a main problem is derived that consists in the lack of a consensus both in terms of the metrics and the procedures used to measure the performance of the different indoor localization and navigation proposals. This paper introduces the general lines of the EvAAL benchmarking framework, which is aimed at a fair comparison of indoor positioning systems through a challenging competition under complex, realistic conditions. To evaluate the framework capabilities, we show how it was used in the 2016 Indoor Positioning and Indoor Navigation (IPIN) Competition. The 2016 IPIN competition considered three different scenario dimensions, with a variety of use cases: (1) pedestrian versus robotic navigation, (2) smartphones versus custom hardware usage and (3) real-time positioning versus off-line post-processing. A total of four competition tracks were evaluated under the same EvAAL benchmark framework in order to validate its potential to become a standard for evaluating indoor localization solutions. The experience gained during the competition and feedback from track organizers and competitors showed that the EvAAL framework is flexible enough to successfully fit the very different tracks and appears adequate to compare indoor positioning systems.
Comparing the Performance of Indoor Localization Systems through the EvAAL Framework
2017-01-01
In recent years, indoor localization systems have been the object of significant research activity and of growing interest for their great expected social impact and their impressive business potential. Application areas include tracking and navigation, activity monitoring, personalized advertising, Active and Assisted Living (AAL), traceability, Internet of Things (IoT) networks, and Home-land Security. In spite of the numerous research advances and the great industrial interest, no canned solutions have yet been defined. The diversity and heterogeneity of applications, scenarios, sensor and user requirements, make it difficult to create uniform solutions. From that diverse reality, a main problem is derived that consists in the lack of a consensus both in terms of the metrics and the procedures used to measure the performance of the different indoor localization and navigation proposals. This paper introduces the general lines of the EvAAL benchmarking framework, which is aimed at a fair comparison of indoor positioning systems through a challenging competition under complex, realistic conditions. To evaluate the framework capabilities, we show how it was used in the 2016 Indoor Positioning and Indoor Navigation (IPIN) Competition. The 2016 IPIN competition considered three different scenario dimensions, with a variety of use cases: (1) pedestrian versus robotic navigation, (2) smartphones versus custom hardware usage and (3) real-time positioning versus off-line post-processing. A total of four competition tracks were evaluated under the same EvAAL benchmark framework in order to validate its potential to become a standard for evaluating indoor localization solutions. The experience gained during the competition and feedback from track organizers and competitors showed that the EvAAL framework is flexible enough to successfully fit the very different tracks and appears adequate to compare indoor positioning systems. PMID:29027948
Collaborative WiFi Fingerprinting Using Sensor-Based Navigation on Smartphones.
Zhang, Peng; Zhao, Qile; Li, You; Niu, Xiaoji; Zhuang, Yuan; Liu, Jingnan
2015-07-20
This paper presents a method that trains the WiFi fingerprint database using sensor-based navigation solutions. Since micro-electromechanical systems (MEMS) sensors provide only a short-term accuracy but suffer from the accuracy degradation with time, we restrict the time length of available indoor navigation trajectories, and conduct post-processing to improve the sensor-based navigation solution. Different middle-term navigation trajectories that move in and out of an indoor area are combined to make up the database. Furthermore, we evaluate the effect of WiFi database shifts on WiFi fingerprinting using the database generated by the proposed method. Results show that the fingerprinting errors will not increase linearly according to database (DB) errors in smartphone-based WiFi fingerprinting applications.
Collaborative WiFi Fingerprinting Using Sensor-Based Navigation on Smartphones
Zhang, Peng; Zhao, Qile; Li, You; Niu, Xiaoji; Zhuang, Yuan; Liu, Jingnan
2015-01-01
This paper presents a method that trains the WiFi fingerprint database using sensor-based navigation solutions. Since micro-electromechanical systems (MEMS) sensors provide only a short-term accuracy but suffer from the accuracy degradation with time, we restrict the time length of available indoor navigation trajectories, and conduct post-processing to improve the sensor-based navigation solution. Different middle-term navigation trajectories that move in and out of an indoor area are combined to make up the database. Furthermore, we evaluate the effect of WiFi database shifts on WiFi fingerprinting using the database generated by the proposed method. Results show that the fingerprinting errors will not increase linearly according to database (DB) errors in smartphone-based WiFi fingerprinting applications. PMID:26205269
STEPPING - Smartphone-Based Portable Pedestrian Indoor Navigation
NASA Astrophysics Data System (ADS)
Lukianto, C.; Sternberg, H.
2011-12-01
Many current smartphones are fitted with GPS receivers, which, in combination with a map application form a pedestrian navigation system for outdoor purposes. However, once an area with insufficient satellite signal coverage is entered, these navigation systems cease to function. For indoor positioning, there are already several solutions available which are usually based on measured distances to reference points. These solutions can achieve resolutions as low as the sub-millimetre range depending on the complexity of the set-up. STEPPING project, developed at HCU Hamburg Germany aims at designing an indoor navigation system consisting of a small inertial navigation system and a new, robust sensor fusion algorithm running on a current smartphone. As this system is theoretically able to integrate any available positioning method, it is independent of a particular method and can thus be realized on a smartphone without affecting user mobility. Potential applications include --but are not limited to: Large trade fairs, airports, parking decks and shopping malls, as well as ambient assisted living scenarios.
Use of Assisted Photogrammetry for Indoor and Outdoor Navigation Purposes
NASA Astrophysics Data System (ADS)
Pagliari, D.; Cazzaniga, N. E.; Pinto, L.
2015-05-01
Nowadays, devices and applications that require navigation solutions are continuously growing. For instance, consider the increasing demand of mapping information or the development of applications based on users' location. In some case it could be sufficient an approximate solution (e.g. at room level), but in the large amount of cases a better solution is required. The navigation problem has been solved from a long time using Global Navigation Satellite System (GNSS). However, it can be unless in obstructed areas, such as in urban areas or inside buildings. An interesting low cost solution is photogrammetry, assisted using additional information to scale the photogrammetric problem and recovering a solution also in critical situation for image-based methods (e.g. poor textured surfaces). In this paper, the use of assisted photogrammetry has been tested for both outdoor and indoor scenarios. Outdoor navigation problem has been faced developing a positioning system with Ground Control Points extracted from urban maps as constrain and tie points automatically extracted from the images acquired during the survey. The proposed approach has been tested under different scenarios, recovering the followed trajectory with an accuracy of 0.20 m. For indoor navigation a solution has been thought to integrate the data delivered by Microsoft Kinect, by identifying interesting features on the RGB images and re-projecting them on the point clouds generated from the delivered depth maps. Then, these points have been used to estimate the rotation matrix between subsequent point clouds and, consequently, to recover the trajectory with few centimeters of error.
VLC-based indoor location awareness using LED light and image sensors
NASA Astrophysics Data System (ADS)
Lee, Seok-Ju; Yoo, Jong-Ho; Jung, Sung-Yoon
2012-11-01
Recently, indoor LED lighting can be considered for constructing green infra with energy saving and additionally providing LED-IT convergence services such as visible light communication (VLC) based location awareness and navigation services. For example, in case of large complex shopping mall, location awareness to navigate the destination is very important issue. However, the conventional navigation using GPS is not working indoors. Alternative location service based on WLAN has a problem that the position accuracy is low. For example, it is difficult to estimate the height exactly. If the position error of the height is greater than the height between floors, it may cause big problem. Therefore, conventional navigation is inappropriate for indoor navigation. Alternative possible solution for indoor navigation is VLC based location awareness scheme. Because indoor LED infra will be definitely equipped for providing lighting functionality, indoor LED lighting has a possibility to provide relatively high accuracy of position estimation combined with VLC technology. In this paper, we provide a new VLC based positioning system using visible LED lights and image sensors. Our system uses location of image sensor lens and location of reception plane. By using more than two image sensor, we can determine transmitter position less than 1m position error. Through simulation, we verify the validity of the proposed VLC based new positioning system using visible LED light and image sensors.
Private Graphs - Access Rights on Graphs for Seamless Navigation
NASA Astrophysics Data System (ADS)
Dorner, W.; Hau, F.; Pagany, R.
2016-06-01
After the success of GNSS (Global Navigational Satellite Systems) and navigation services for public streets, indoor seems to be the next big development in navigational services, relying on RTLS - Real Time Locating Services (e.g. WIFI) and allowing seamless navigation. In contrast to navigation and routing services on public streets, seamless navigation will cause an additional challenge: how to make routing data accessible to defined users or restrict access rights for defined areas or only to parts of the graph to a defined user group? The paper will present case studies and data from literature, where seamless and especially indoor navigation solutions are presented (hospitals, industrial complexes, building sites), but the problem of restricted access rights was only touched from a real world, but not a technical perspective. The analysis of case studies will show, that the objective of navigation and the different target groups for navigation solutions will demand well defined access rights and require solutions, how to make only parts of a graph to a user or application available to solve a navigational task. The paper will therefore introduce the concept of private graphs, which is defined as a graph for navigational purposes covering the street, road or floor network of an area behind a public street and suggest different approaches how to make graph data for navigational purposes available considering access rights and data protection, privacy and security issues as well.
Navigation studies based on the ubiquitous positioning technologies
NASA Astrophysics Data System (ADS)
Ye, Lei; Mi, Weijie; Wang, Defeng
2007-11-01
This paper summarized the nowadays positioning technologies, such as absolute positioning methods and relative positioning methods, indoor positioning and outdoor positioning, active positioning and passive positioning. Global Navigation Satellite System (GNSS) technologies were introduced as the omnipresent out-door positioning technologies, including GPS, GLONASS, Galileo and BD-1/2. After analysis of the shortcomings of GNSS, indoor positioning technologies were discussed and compared, including A-GPS, Cellular network, Infrared, Electromagnetism, Computer Vision Cognition, Embedded Pressure Sensor, Ultrasonic, RFID (Radio Frequency IDentification), Bluetooth, WLAN etc.. Then the concept and characteristics of Ubiquitous Positioning was proposed. After the ubiquitous positioning technologies contrast and selection followed by system engineering methodology, a navigation system model based on Incorporate Indoor-Outdoor Positioning Solution was proposed. And this model was simulated in the Galileo Demonstration for World Expo Shanghai project. In the conclusion, the prospects of ubiquitous positioning based navigation were shown, especially to satisfy the public location information acquiring requirement.
HyMoTrack: A Mobile AR Navigation System for Complex Indoor Environments.
Gerstweiler, Georg; Vonach, Emanuel; Kaufmann, Hannes
2015-12-24
Navigating in unknown big indoor environments with static 2D maps is a challenge, especially when time is a critical factor. In order to provide a mobile assistant, capable of supporting people while navigating in indoor locations, an accurate and reliable localization system is required in almost every corner of the building. We present a solution to this problem through a hybrid tracking system specifically designed for complex indoor spaces, which runs on mobile devices like smartphones or tablets. The developed algorithm only uses the available sensors built into standard mobile devices, especially the inertial sensors and the RGB camera. The combination of multiple optical tracking technologies, such as 2D natural features and features of more complex three-dimensional structures guarantees the robustness of the system. All processing is done locally and no network connection is needed. State-of-the-art indoor tracking approaches use mainly radio-frequency signals like Wi-Fi or Bluetooth for localizing a user. In contrast to these approaches, the main advantage of the developed system is the capability of delivering a continuous 3D position and orientation of the mobile device with centimeter accuracy. This makes it usable for localization and 3D augmentation purposes, e.g. navigation tasks or location-based information visualization.
HyMoTrack: A Mobile AR Navigation System for Complex Indoor Environments
Gerstweiler, Georg; Vonach, Emanuel; Kaufmann, Hannes
2015-01-01
Navigating in unknown big indoor environments with static 2D maps is a challenge, especially when time is a critical factor. In order to provide a mobile assistant, capable of supporting people while navigating in indoor locations, an accurate and reliable localization system is required in almost every corner of the building. We present a solution to this problem through a hybrid tracking system specifically designed for complex indoor spaces, which runs on mobile devices like smartphones or tablets. The developed algorithm only uses the available sensors built into standard mobile devices, especially the inertial sensors and the RGB camera. The combination of multiple optical tracking technologies, such as 2D natural features and features of more complex three-dimensional structures guarantees the robustness of the system. All processing is done locally and no network connection is needed. State-of-the-art indoor tracking approaches use mainly radio-frequency signals like Wi-Fi or Bluetooth for localizing a user. In contrast to these approaches, the main advantage of the developed system is the capability of delivering a continuous 3D position and orientation of the mobile device with centimeter accuracy. This makes it usable for localization and 3D augmentation purposes, e.g. navigation tasks or location-based information visualization. PMID:26712755
NASA Astrophysics Data System (ADS)
Štefanička, Tomáš; Ďuračiová, Renata; Seres, Csaba
2017-12-01
As a complex of buildings, the Faculty of Natural Sciences of the Comenius University in Bratislava tends to be difficult to navigate in spite of its size. An indoor navigation application could potentially save a lot of time and frustration. There are currently numerous technologies used in indoor navigation systems. Some of them focus on a high degree of precision and require significant financial investment; others provide only static information about a current location. In this paper we focused on the determination of an approximate location using inertial measurement systems available on most smartphones, i.e., a gyroscope and an accelerometer. The actual position of the device was calculated using "a walk detection method" based on a delayed lack of motion. We have developed an indoor navigation application that relies solely on open source JavaScript libraries to visualize the interior of the building and calculate the shortest path utilizing Dijsktra's routing algorithm. The application logic is located on the client side, so the software is able to work offline. Our solution represents an accessible lowcost and platform-independent web application that can significantly improve navigation at the Faculty of Natural Sciences. Although our application has been developed on a specific building complex, it could be used in other interiors as well.
A proposed UAV for indoor patient care.
Todd, Catherine; Watfa, Mohamed; El Mouden, Yassine; Sahir, Sana; Ali, Afrah; Niavarani, Ali; Lutfi, Aoun; Copiaco, Abigail; Agarwal, Vaibhavi; Afsari, Kiyan; Johnathon, Chris; Okafor, Onyeka; Ayad, Marina
2015-09-10
Indoor flight, obstacle avoidance and client-server communication of an Unmanned Aerial Vehicle (UAV) raises several unique research challenges. This paper examines current methods and associated technologies adapted within the literature toward autonomous UAV flight, for consideration in a proposed system for indoor healthcare administration with a quadcopter. We introduce Healthbuddy, a unique research initiative towards overcoming challenges associated with indoor navigation, collision detection and avoidance, stability, wireless drone-server communications and automated decision support for patient care in a GPS-denied environment. To address the identified research deficits, a drone-based solution is presented. The solution is preliminary as we develop and refine the suggested algorithms and hardware system to achieve the research objectives.
Chiang, Kai-Wei; Liao, Jhen-Kai; Tsai, Guang-Je; Chang, Hsiu-Wen
2015-01-01
Hardware sensors embedded in a smartphone allow the device to become an excellent mobile navigator. A smartphone is ideal for this task because its great international popularity has led to increased phone power and since most of the necessary infrastructure is already in place. However, using a smartphone for indoor pedestrian navigation can be problematic due to the low accuracy of sensors, imprecise predictability of pedestrian motion, and inaccessibility of the Global Navigation Satellite System (GNSS) in some indoor environments. Pedestrian Dead Reckoning (PDR) is one of the most common technologies used for pedestrian navigation, but in its present form, various errors tend to accumulate. This study introduces a fuzzy decision tree (FDT) aided by map information to improve the accuracy and stability of PDR with less dependency on infrastructure. First, the map is quickly surveyed by the Indoor Mobile Mapping System (IMMS). Next, Bluetooth beacons are implemented to enable the initializing of any position. Finally, map-aided FDT can estimate navigation solutions in real time. The experiments were conducted in different fields using a variety of smartphones and users in order to verify stability. The contrast PDR system demonstrates low stability for each case without pre-calibration and post-processing, but the proposed low-complexity FDT algorithm shows good stability and accuracy under the same conditions. PMID:26729114
A Map/INS/Wi-Fi Integrated System for Indoor Location-Based Service Applications
Yu, Chunyang; Lan, Haiyu; Gu, Fuqiang; Yu, Fei; El-Sheimy, Naser
2017-01-01
In this research, a new Map/INS/Wi-Fi integrated system for indoor location-based service (LBS) applications based on a cascaded Particle/Kalman filter framework structure is proposed. Two-dimension indoor map information, together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value, are integrated for estimating positioning information. The main challenge of this research is how to make effective use of various measurements that complement each other in order to obtain an accurate, continuous, and low-cost position solution without increasing the computational burden of the system. Therefore, to eliminate the cumulative drift caused by low-cost IMU sensor errors, the ubiquitous Wi-Fi signal and non-holonomic constraints are rationally used to correct the IMU-derived navigation solution through the extended Kalman Filter (EKF). Moreover, the map-aiding method and map-matching method are innovatively combined to constrain the primary Wi-Fi/IMU-derived position through an Auxiliary Value Particle Filter (AVPF). Different sources of information are incorporated through a cascaded structure EKF/AVPF filter algorithm. Indoor tests show that the proposed method can effectively reduce the accumulation of positioning errors of a stand-alone Inertial Navigation System (INS), and provide a stable, continuous and reliable indoor location service. PMID:28574471
A Map/INS/Wi-Fi Integrated System for Indoor Location-Based Service Applications.
Yu, Chunyang; Lan, Haiyu; Gu, Fuqiang; Yu, Fei; El-Sheimy, Naser
2017-06-02
In this research, a new Map/INS/Wi-Fi integrated system for indoor location-based service (LBS) applications based on a cascaded Particle/Kalman filter framework structure is proposed. Two-dimension indoor map information, together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value, are integrated for estimating positioning information. The main challenge of this research is how to make effective use of various measurements that complement each other in order to obtain an accurate, continuous, and low-cost position solution without increasing the computational burden of the system. Therefore, to eliminate the cumulative drift caused by low-cost IMU sensor errors, the ubiquitous Wi-Fi signal and non-holonomic constraints are rationally used to correct the IMU-derived navigation solution through the extended Kalman Filter (EKF). Moreover, the map-aiding method and map-matching method are innovatively combined to constrain the primary Wi-Fi/IMU-derived position through an Auxiliary Value Particle Filter (AVPF). Different sources of information are incorporated through a cascaded structure EKF/AVPF filter algorithm. Indoor tests show that the proposed method can effectively reduce the accumulation of positioning errors of a stand-alone Inertial Navigation System (INS), and provide a stable, continuous and reliable indoor location service.
Indoor navigation by image recognition
NASA Astrophysics Data System (ADS)
Choi, Io Teng; Leong, Chi Chong; Hong, Ka Wo; Pun, Chi-Man
2017-07-01
With the progress of smartphones hardware, it is simple on smartphone using image recognition technique such as face detection. In addition, indoor navigation system development is much slower than outdoor navigation system. Hence, this research proves a usage of image recognition technique for navigation in indoor environment. In this paper, we introduced an indoor navigation application that uses the indoor environment features to locate user's location and a route calculating algorithm to generate an appropriate path for user. The application is implemented on Android smartphone rather than iPhone. Yet, the application design can also be applied on iOS because the design is implemented without using special features only for Android. We found that digital navigation system provides better and clearer location information than paper map. Also, the indoor environment is ideal for Image recognition processing. Hence, the results motivate us to design an indoor navigation system using image recognition.
NFC Internal: An Indoor Navigation System
Ozdenizci, Busra; Coskun, Vedat; Ok, Kerem
2015-01-01
Indoor navigation systems have recently become a popular research field due to the lack of GPS signals indoors. Several indoors navigation systems have already been proposed in order to eliminate deficiencies; however each of them has several technical and usability limitations. In this study, we propose NFC Internal, a Near Field Communication (NFC)-based indoor navigation system, which enables users to navigate through a building or a complex by enabling a simple location update, simply by touching NFC tags those are spread around and orient users to the destination. In this paper, we initially present the system requirements, give the design details and study the viability of NFC Internal with a prototype application and a case study. Moreover, we evaluate the performance of the system and compare it with existing indoor navigation systems. It is seen that NFC Internal has considerable advantages and significant contributions to existing indoor navigation systems in terms of security and privacy, cost, performance, robustness, complexity, user preference and commercial availability. PMID:25825976
Integration of Kinect and Low-Cost Gnss for Outdoor Navigation
NASA Astrophysics Data System (ADS)
Pagliaria, D.; Pinto, L.; Reguzzoni, M.; Rossi, L.
2016-06-01
Since its launch on the market, Microsoft Kinect sensor has represented a great revolution in the field of low cost navigation, especially for indoor robotic applications. In fact, this system is endowed with a depth camera, as well as a visual RGB camera, at a cost of about 200. The characteristics and the potentiality of the Kinect sensor have been widely studied for indoor applications. The second generation of this sensor has been announced to be capable of acquiring data even outdoors, under direct sunlight. The task of navigating passing from an indoor to an outdoor environment (and vice versa) is very demanding because the sensors that work properly in one environment are typically unsuitable in the other one. In this sense the Kinect could represent an interesting device allowing bridging the navigation solution between outdoor and indoor. In this work the accuracy and the field of application of the new generation of Kinect sensor have been tested outdoor, considering different lighting conditions and the reflective properties of the emitted ray on different materials. Moreover, an integrated system with a low cost GNSS receiver has been studied, with the aim of taking advantage of the GNSS positioning when the satellite visibility conditions are good enough. A kinematic test has been performed outdoor by using a Kinect sensor and a GNSS receiver and it is here presented.
Exploitation of Semantic Building Model in Indoor Navigation Systems
NASA Astrophysics Data System (ADS)
Anjomshoaa, A.; Shayeganfar, F.; Tjoa, A. Min
2009-04-01
There are many types of indoor and outdoor navigation tools and methodologies available. A majority of these solutions are based on Global Positioning Systems (GPS) and instant video and image processing. These approaches are ideal for open world environments where very few information about the target location is available, but for large scale building environments such as hospitals, governmental offices, etc the end-user will need more detailed information about the surrounding context which is especially important in case of people with special needs. This paper presents a smart indoor navigation solution that is based on Semantic Web technologies and Building Information Model (BIM). The proposed solution is also aligned with Google Android's concepts to enlighten the realization of results. Keywords: IAI IFCXML, Building Information Model, Indoor Navigation, Semantic Web, Google Android, People with Special Needs 1 Introduction Built environment is a central factor in our daily life and a big portion of human life is spent inside buildings. Traditionally the buildings are documented using building maps and plans by utilization of IT tools such as computer-aided design (CAD) applications. Documenting the maps in an electronic way is already pervasive but CAD drawings do not suffice the requirements regarding effective building models that can be shared with other building-related applications such as indoor navigation systems. The navigation in built environment is not a new issue, however with the advances in emerging technologies like GPS, mobile and networked environments, and Semantic Web new solutions have been suggested to enrich the traditional building maps and convert them to smart information resources that can be reused in other applications and improve the interpretability with building inhabitants and building visitors. Other important issues that should be addressed in building navigation scenarios are location tagging and end-user communication. The available solutions for location tagging are mostly based on proximity sensors and the information are bound to sensor references. In the proposed solution of this paper, the sensors simply play a role similar to annotations in Semantic Web world. Hence the sensors data in ontology sense bridges the gap between sensed information and building model. Combining these two and applying the proper inference rules, the building visitors will be able to reach their destinations with instant support of their communication devices such as hand helds, wearable computers, mobiles, etc. In a typical scenario of this kind, user's profile will be delivered to the smart building (via building ad-hoc services) and the appropriate route for user will be calculated and delivered to user's end-device. The calculated route is calculated by considering all constraints and requirements of the end user. So for example if the user is using a wheelchair, the calculated route should not contain stairs or narrow corridors that the wheelchair does not pass through. Then user starts to navigate through building by following the instructions of the end-device which are in turn generated from the calculated route. During the navigation process, the end-device should also interact with the smart building to sense the locations by reading the surrounding tags. So for example when a visually impaired person arrives at an unknown space, the tags will be sensed and the relevant information will be delivered to user in the proper way of communication. For example the building model can be used to generate a voice message for a blind person about a space and tell him/her that "the space has 3 doors, and the door on the left should be chosen which needs to be pushed to open". In this paper we will mainly focus on automatic generation of semantic building information models (Semantic BIM) and delivery of results to the end user. Combining the building information model with the environment and user constraints using Semantic Web technologies will make many scenarios conceivable. The generated IFC ontology that is base on the commonly accepted IFC (Industry Foundation Classes) standard can be used as the basis of information sharing between buildings, people, and applications. The proposed solution is aiming to facilitate the building navigation in an intuitive and extendable way that is easy to use by end-users and at the same time easy to maintain and manage by building administrators.
Indoor Navigation from Point Clouds: 3d Modelling and Obstacle Detection
NASA Astrophysics Data System (ADS)
Díaz-Vilariño, L.; Boguslawski, P.; Khoshelham, K.; Lorenzo, H.; Mahdjoubi, L.
2016-06-01
In the recent years, indoor modelling and navigation has become a research of interest because many stakeholders require navigation assistance in various application scenarios. The navigational assistance for blind or wheelchair people, building crisis management such as fire protection, augmented reality for gaming, tourism or training emergency assistance units are just some of the direct applications of indoor modelling and navigation. Navigational information is traditionally extracted from 2D drawings or layouts. Real state of indoors, including opening position and geometry for both windows and doors, and the presence of obstacles is commonly ignored. In this work, a real indoor-path planning methodology based on 3D point clouds is developed. The value and originality of the approach consist on considering point clouds not only for reconstructing semantically-rich 3D indoor models, but also for detecting potential obstacles in the route planning and using these for readapting the routes according to the real state of the indoor depictured by the laser scanner.
Usability analysis of indoor map application in a shopping centre
NASA Astrophysics Data System (ADS)
Dewi, R. S.; Hadi, R. K.
2018-04-01
Although indoor navigation is still new in Indonesia, its future development is very promising. Similar to the outdoor one, the indoor navigation technology provides several important functions to support route and landmark findings. Furthermore, there is also a need that indoor navigation can support the public safety especially during disaster evacuation process in a building. It is a common that the indoor navigation technologies are built as applications where users can access this technology using their smartphones, tablets, or personal computers. Therefore, a usability analysis is important to ensure the indoor navigation applications can be operated by users with highest functionality. Among several indoor map applications which were available in the market, this study chose to analyse indoor Google Maps due to its availability and popularity in Indonesia. The experiments to test indoor Google Maps was conducted in one of the biggest shopping centre building in Surabaya, Indonesia. The usability was measured by employing System Usability Scale (SUS) questionnaire. The result showed that the SUS score of indoor Google Maps was below the average score of other cellular applications to indicate the users still had high difficulty in operating and learning the features of indoor Google Maps.
In campus location finder using mobile application services
NASA Astrophysics Data System (ADS)
Fai, Low Weng; Audah, Lukman
2017-09-01
Navigation services become very common in this era, the application include Google Map, Waze and etc. Although navigation application contains the main routing service in open area but not all of the buildings are recorded in the database. In this project, an application is made for the indoor and outdoor navigation in Universiti Tun Hussein Onn Malaysia (UTHM). It is used to help outsider and new incoming students by navigating them from their current location to destination using mobile application name "U Finder". Thunkable website has been used to build the application for outdoor and indoor navigation. Outdoor navigation is linked to the Google Map and indoor navigation is using the QR code for positioning and routing picture for navigation. The outdoor navigation can route user to the main faculties in UTHM and indoor navigation is only done for the G1 building in UTHM.
Seamless positioning and navigation by using geo-referenced images and multi-sensor data.
Li, Xun; Wang, Jinling; Li, Tao
2013-07-12
Ubiquitous positioning is considered to be a highly demanding application for today's Location-Based Services (LBS). While satellite-based navigation has achieved great advances in the past few decades, positioning and navigation in indoor scenarios and deep urban areas has remained a challenging topic of substantial research interest. Various strategies have been adopted to fill this gap, within which vision-based methods have attracted growing attention due to the widespread use of cameras on mobile devices. However, current vision-based methods using image processing have yet to revealed their full potential for navigation applications and are insufficient in many aspects. Therefore in this paper, we present a hybrid image-based positioning system that is intended to provide seamless position solution in six degrees of freedom (6DoF) for location-based services in both outdoor and indoor environments. It mainly uses visual sensor input to match with geo-referenced images for image-based positioning resolution, and also takes advantage of multiple onboard sensors, including the built-in GPS receiver and digital compass to assist visual methods. Experiments demonstrate that such a system can greatly improve the position accuracy for areas where the GPS signal is negatively affected (such as in urban canyons), and it also provides excellent position accuracy for indoor environments.
Seamless Positioning and Navigation by Using Geo-Referenced Images and Multi-Sensor Data
Li, Xun; Wang, Jinling; Li, Tao
2013-01-01
Ubiquitous positioning is considered to be a highly demanding application for today's Location-Based Services (LBS). While satellite-based navigation has achieved great advances in the past few decades, positioning and navigation in indoor scenarios and deep urban areas has remained a challenging topic of substantial research interest. Various strategies have been adopted to fill this gap, within which vision-based methods have attracted growing attention due to the widespread use of cameras on mobile devices. However, current vision-based methods using image processing have yet to revealed their full potential for navigation applications and are insufficient in many aspects. Therefore in this paper, we present a hybrid image-based positioning system that is intended to provide seamless position solution in six degrees of freedom (6DoF) for location-based services in both outdoor and indoor environments. It mainly uses visual sensor input to match with geo-referenced images for image-based positioning resolution, and also takes advantage of multiple onboard sensors, including the built-in GPS receiver and digital compass to assist visual methods. Experiments demonstrate that such a system can greatly improve the position accuracy for areas where the GPS signal is negatively affected (such as in urban canyons), and it also provides excellent position accuracy for indoor environments. PMID:23857267
Bim-Based Indoor Path Planning Considering Obstacles
NASA Astrophysics Data System (ADS)
Xu, M.; Wei, S.; Zlatanova, S.; Zhang, R.
2017-09-01
At present, 87 % of people's activities are in indoor environment; indoor navigation has become a research issue. As the building structures for people's daily life are more and more complex, many obstacles influence humans' moving. Therefore it is essential to provide an accurate and efficient indoor path planning. Nowadays there are many challenges and problems in indoor navigation. Most existing path planning approaches are based on 2D plans, pay more attention to the geometric configuration of indoor space, often ignore rich semantic information of building components, and mostly consider simple indoor layout without taking into account the furniture. Addressing the above shortcomings, this paper uses BIM (IFC) as the input data and concentrates on indoor navigation considering obstacles in the multi-floor buildings. After geometric and semantic information are extracted, 2D and 3D space subdivision methods are adopted to build the indoor navigation network and to realize a path planning that avoids obstacles. The 3D space subdivision is based on triangular prism. The two approaches are verified by the experiments.
Extracting Topological Relations Between Indoor Spaces from Point Clouds
NASA Astrophysics Data System (ADS)
Tran, H.; Khoshelham, K.; Kealy, A.; Díaz-Vilariño, L.
2017-09-01
3D models of indoor environments are essential for many application domains such as navigation guidance, emergency management and a range of indoor location-based services. The principal components defined in different BIM standards contain not only building elements, such as floors, walls and doors, but also navigable spaces and their topological relations, which are essential for path planning and navigation. We present an approach to automatically reconstruct topological relations between navigable spaces from point clouds. Three types of topological relations, namely containment, adjacency and connectivity of the spaces are modelled. The results of initial experiments demonstrate the potential of the method in supporting indoor navigation.
Calculating Least Risk Paths in 3d Indoor Space
NASA Astrophysics Data System (ADS)
Vanclooster, A.; De Maeyer, Ph.; Fack, V.; Van de Weghe, N.
2013-08-01
Over the last couple of years, research on indoor environments has gained a fresh impetus; more specifically applications that support navigation and wayfinding have become one of the booming industries. Indoor navigation research currently covers the technological aspect of indoor positioning and the modelling of indoor space. The algorithmic development to support navigation has so far been left mostly untouched, as most applications mainly rely on adapting Dijkstra's shortest path algorithm to an indoor network. However, alternative algorithms for outdoor navigation have been proposed adding a more cognitive notion to the calculated paths and as such adhering to the natural wayfinding behaviour (e.g. simplest paths, least risk paths). These algorithms are currently restricted to outdoor applications. The need for indoor cognitive algorithms is highlighted by a more challenged navigation and orientation due to the specific indoor structure (e.g. fragmentation, less visibility, confined areas…). As such, the clarity and easiness of route instructions is of paramount importance when distributing indoor routes. A shortest or fastest path indoors not necessarily aligns with the cognitive mapping of the building. Therefore, the aim of this research is to extend those richer cognitive algorithms to three-dimensional indoor environments. More specifically for this paper, we will focus on the application of the least risk path algorithm of Grum (2005) to an indoor space. The algorithm as proposed by Grum (2005) is duplicated and tested in a complex multi-storey building. The results of several least risk path calculations are compared to the shortest paths in indoor environments in terms of total length, improvement in route description complexity and number of turns. Several scenarios are tested in this comparison: paths covering a single floor, paths crossing several building wings and/or floors. Adjustments to the algorithm are proposed to be more aligned to the specific structure of indoor environments (e.g. no turn restrictions, restricted usage of rooms, vertical movement) and common wayfinding strategies indoors. In a later stage, other cognitive algorithms will be implemented and tested in both an indoor and combined indoor-outdoor setting, in an effort to improve the overall user experience during navigation in indoor environments.
A flexible routing scheme for patients with topographical disorientation.
Torres-Solis, Jorge; Chau, Tom
2007-11-28
Individuals with topographical disorientation have difficulty navigating through indoor environments. Recent literature has suggested that ambient intelligence technologies may provide patients with navigational assistance through auditory or graphical instructions delivered via embedded devices. We describe an automatic routing engine for such an ambient intelligence system. The method routes patients with topographical disorientation through indoor environments by repeatedly computing the route of minimal cost from the current location of the patient to a specified destination. The cost of a given path not only reflects the physical distance between end points, but also incorporates individual patient abilities, the presence of mobility-impeding physical barriers within a building and the dynamic nature of the indoor environment. We demonstrate the method by routing simulated patients with either topographical disorientation or physical disabilities. Additionally, we exemplify the ability to route a patient from source to destination while taking into account changes to the building interior. When compared to a random walk, the proposed routing scheme offers potential cost-savings even when the patient follows only a subset of instructions. The routing method presented reduces the navigational effort for patients with topographical disorientation in indoor environments, accounting for physical abilities of the patient, environmental barriers and dynamic building changes. The routing algorithm and database proposed could be integrated into wearable and mobile platforms within the context of an ambient intelligence solution.
A hybrid smartphone indoor positioning solution for mobile LBS.
Liu, Jingbin; Chen, Ruizhi; Pei, Ling; Guinness, Robert; Kuusniemi, Heidi
2012-12-12
Smartphone positioning is an enabling technology used to create new business in the navigation and mobile location-based services (LBS) industries. This paper presents a smartphone indoor positioning engine named HIPE that can be easily integrated with mobile LBS. HIPE is a hybrid solution that fuses measurements of smartphone sensors with wireless signals. The smartphone sensors are used to measure the user's motion dynamics information (MDI), which represent the spatial correlation of various locations. Two algorithms based on hidden Markov model (HMM) problems, the grid-based filter and the Viterbi algorithm, are used in this paper as the central processor for data fusion to resolve the position estimates, and these algorithms are applicable for different applications, e.g., real-time navigation and location tracking, respectively. HIPE is more widely applicable for various motion scenarios than solutions proposed in previous studies because it uses no deterministic motion models, which have been commonly used in previous works. The experimental results showed that HIPE can provide adequate positioning accuracy and robustness for different scenarios of MDI combinations. HIPE is a cost-efficient solution, and it can work flexibly with different smartphone platforms, which may have different types of sensors available for the measurement of MDI data. The reliability of the positioning solution was found to increase with increasing precision of the MDI data.
LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments
Tang, Jian; Chen, Yuwei; Niu, Xiaoji; Wang, Li; Chen, Liang; Liu, Jingbin; Shi, Chuang; Hyyppä, Juha
2015-01-01
A new scan that matches an aided Inertial Navigation System (INS) with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR) and Simultaneous Localization and Mapping (SLAM) technologies are normally used to estimate positions as separate tools. However, there are critical implementation problems with each standalone system. The drift errors of velocity, position, and heading angles in an INS will accumulate over time, and on-line calibration is a must for sustaining positioning accuracy. SLAM performance is poor in featureless environments where the matching errors can significantly increase. Each standalone positioning method cannot offer a sustainable navigation solution with acceptable accuracy. This paper integrates two complementary technologies—INS and LiDAR SLAM—into one navigation frame with a loosely coupled Extended Kalman Filter (EKF) to use the advantages and overcome the drawbacks of each system to establish a stable long-term navigation process. Static and dynamic field tests were carried out with a self-developed Unmanned Ground Vehicle (UGV) platform—NAVIS. The results prove that the proposed approach can provide positioning accuracy at the centimetre level for long-term operations, even in a featureless indoor environment. PMID:26184206
LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments.
Tang, Jian; Chen, Yuwei; Niu, Xiaoji; Wang, Li; Chen, Liang; Liu, Jingbin; Shi, Chuang; Hyyppä, Juha
2015-07-10
A new scan that matches an aided Inertial Navigation System (INS) with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR) and Simultaneous Localization and Mapping (SLAM) technologies are normally used to estimate positions as separate tools. However, there are critical implementation problems with each standalone system. The drift errors of velocity, position, and heading angles in an INS will accumulate over time, and on-line calibration is a must for sustaining positioning accuracy. SLAM performance is poor in featureless environments where the matching errors can significantly increase. Each standalone positioning method cannot offer a sustainable navigation solution with acceptable accuracy. This paper integrates two complementary technologies-INS and LiDAR SLAM-into one navigation frame with a loosely coupled Extended Kalman Filter (EKF) to use the advantages and overcome the drawbacks of each system to establish a stable long-term navigation process. Static and dynamic field tests were carried out with a self-developed Unmanned Ground Vehicle (UGV) platform-NAVIS. The results prove that the proposed approach can provide positioning accuracy at the centimetre level for long-term operations, even in a featureless indoor environment.
About the Subdivision of Indoor Spaces in Indoorgml
NASA Astrophysics Data System (ADS)
Diakité, A. A.; Zlatanova, S.; Li, K.-J.
2017-10-01
Boosted by the dynamic urbanization of cities, indoor environments are getting more and more complex in order to be able to host people properly. While most of our time is spent inside buildings, the need of GIS tools to assist our daily activities that can become tedious, such as indoor navigation or facility management, became more and more urgent. In that perspective, the IndoorGML standard is aiming to address the gaps left by other standards regarding the spatial modelling for indoor navigation. It includes several concepts such as the organization of the spaces into cells along with their network representation and the possibility to represent multiple connected layers. However, being at its first stage, several concepts of the standard could be improved. One of these is the cell subspacing that is not enough discussed in the current version of the standard. In this paper, we explore all the aspects involved in the subdivision process, from the identification of the navigable and non-navigable space cells to the generation of a navigation graph. We propose several criteria on which the indoor sub-spacing can rely to be automatically performed and and illustrate them on a 3D indoor model.
Preliminary study of a millimeter wave FMCW InSAR for UAS indoor navigation.
Scannapieco, Antonio F; Renga, Alfredo; Moccia, Antonio
2015-01-22
Small autonomous unmanned aerial systems (UAS) could be used for indoor inspection in emergency missions, such as damage assessment or the search for survivors in dangerous environments, e.g., power plants, underground railways, mines and industrial warehouses. Two basic functions are required to carry out these tasks, that is autonomous GPS-denied navigation with obstacle detection and high-resolution 3Dmapping with moving target detection. State-of-the-art sensors for UAS are very sensitive to environmental conditions and often fail in the case of poor visibility caused by dust, fog, smoke, flames or other factors that are met as nominal mission scenarios when operating indoors. This paper is a preliminary study concerning an innovative radar sensor based on the interferometric Synthetic Aperture Radar (SAR) principle, which has the potential to satisfy stringent requirements set by indoor autonomous operation. An architectural solution based on a frequency-modulated continuous wave (FMCW) scheme is proposed after a detailed analysis of existing compact and lightweight SAR. A preliminary system design is obtained, and the main imaging peculiarities of the novel sensor are discussed, demonstrating that high-resolution, high-quality observation of an assigned control volume can be achieved.
Preliminary Study of a Millimeter Wave FMCW InSAR for UAS Indoor Navigation
Scannapieco, Antonio F.; Renga, Alfredo; Moccia, Antonio
2015-01-01
Small autonomous unmanned aerial systems (UAS) could be used for indoor inspection in emergency missions, such as damage assessment or the search for survivors in dangerous environments, e.g., power plants, underground railways, mines and industrial warehouses. Two basic functions are required to carry out these tasks, that is autonomous GPS-denied navigation with obstacle detection and high-resolution 3D mapping with moving target detection. State-of-the-art sensors for UAS are very sensitive to environmental conditions and often fail in the case of poor visibility caused by dust, fog, smoke, flames or other factors that are met as nominal mission scenarios when operating indoors. This paper is a preliminary study concerning an innovative radar sensor based on the interferometric Synthetic Aperture Radar (SAR) principle, which has the potential to satisfy stringent requirements set by indoor autonomous operation. An architectural solution based on a frequency-modulated continuous wave (FMCW) scheme is proposed after a detailed analysis of existing compact and lightweight SAR. A preliminary system design is obtained, and the main imaging peculiarities of the novel sensor are discussed, demonstrating that high-resolution, high-quality observation of an assigned control volume can be achieved. PMID:25621606
A Hybrid 3D Indoor Space Model
NASA Astrophysics Data System (ADS)
Jamali, Ali; Rahman, Alias Abdul; Boguslawski, Pawel
2016-10-01
GIS integrates spatial information and spatial analysis. An important example of such integration is for emergency response which requires route planning inside and outside of a building. Route planning requires detailed information related to indoor and outdoor environment. Indoor navigation network models including Geometric Network Model (GNM), Navigable Space Model, sub-division model and regular-grid model lack indoor data sources and abstraction methods. In this paper, a hybrid indoor space model is proposed. In the proposed method, 3D modeling of indoor navigation network is based on surveying control points and it is less dependent on the 3D geometrical building model. This research proposes a method of indoor space modeling for the buildings which do not have proper 2D/3D geometrical models or they lack semantic or topological information. The proposed hybrid model consists of topological, geometrical and semantical space.
A New Indoor Positioning System Architecture Using GPS Signals.
Xu, Rui; Chen, Wu; Xu, Ying; Ji, Shengyue
2015-04-29
The pseudolite system is a good alternative for indoor positioning systems due to its large coverage area and accurate positioning solution. However, for common Global Positioning System (GPS) receivers, the pseudolite system requires some modifications of the user terminals. To solve the problem, this paper proposes a new pseudolite-based indoor positioning system architecture. The main idea is to receive real-world GPS signals, repeat each satellite signal and transmit those using indoor transmitting antennas. The transmitted GPS-like signal can be processed (signal acquisition and tracking, navigation data decoding) by the general receiver and thus no hardware-level modification on the receiver is required. In addition, all Tx can be synchronized with each other since one single clock is used in Rx/Tx. The proposed system is simulated using a software GPS receiver. The simulation results show the indoor positioning system is able to provide high accurate horizontal positioning in both static and dynamic situations.
A Hybrid Smartphone Indoor Positioning Solution for Mobile LBS
Liu, Jingbin; Chen, Ruizhi; Pei, Ling; Guinness, Robert; Kuusniemi, Heidi
2012-01-01
Smartphone positioning is an enabling technology used to create new business in the navigation and mobile location-based services (LBS) industries. This paper presents a smartphone indoor positioning engine named HIPE that can be easily integrated with mobile LBS. HIPE is a hybrid solution that fuses measurements of smartphone sensors with wireless signals. The smartphone sensors are used to measure the user’s motion dynamics information (MDI), which represent the spatial correlation of various locations. Two algorithms based on hidden Markov model (HMM) problems, the grid-based filter and the Viterbi algorithm, are used in this paper as the central processor for data fusion to resolve the position estimates, and these algorithms are applicable for different applications, e.g., real-time navigation and location tracking, respectively. HIPE is more widely applicable for various motion scenarios than solutions proposed in previous studies because it uses no deterministic motion models, which have been commonly used in previous works. The experimental results showed that HIPE can provide adequate positioning accuracy and robustness for different scenarios of MDI combinations. HIPE is a cost-efficient solution, and it can work flexibly with different smartphone platforms, which may have different types of sensors available for the measurement of MDI data. The reliability of the positioning solution was found to increase with increasing precision of the MDI data. PMID:23235455
Enabling Autonomous Navigation for Affordable Scooters.
Liu, Kaikai; Mulky, Rajathswaroop
2018-06-05
Despite the technical success of existing assistive technologies, for example, electric wheelchairs and scooters, they are still far from effective enough in helping those in need navigate to their destinations in a hassle-free manner. In this paper, we propose to improve the safety and autonomy of navigation by designing a cutting-edge autonomous scooter, thus allowing people with mobility challenges to ambulate independently and safely in possibly unfamiliar surroundings. We focus on indoor navigation scenarios for the autonomous scooter where the current location, maps, and nearby obstacles are unknown. To achieve semi-LiDAR functionality, we leverage the gyros-based pose data to compensate the laser motion in real time and create synthetic mapping of simple environments with regular shapes and deep hallways. Laser range finders are suitable for long ranges with limited resolution. Stereo vision, on the other hand, provides 3D structural data of nearby complex objects. To achieve simultaneous fine-grained resolution and long range coverage in the mapping of cluttered and complex environments, we dynamically fuse the measurements from the stereo vision camera system, the synthetic laser scanner, and the LiDAR. We propose solutions to self-correct errors in data fusion and create a hybrid map to assist the scooter in achieving collision-free navigation in an indoor environment.
Automatic Recognition of Indoor Navigation Elements from Kinect Point Clouds
NASA Astrophysics Data System (ADS)
Zeng, L.; Kang, Z.
2017-09-01
This paper realizes automatically the navigating elements defined by indoorGML data standard - door, stairway and wall. The data used is indoor 3D point cloud collected by Kinect v2 launched in 2011 through the means of ORB-SLAM. By contrast, it is cheaper and more convenient than lidar, but the point clouds also have the problem of noise, registration error and large data volume. Hence, we adopt a shape descriptor - histogram of distances between two randomly chosen points, proposed by Osada and merges with other descriptor - in conjunction with random forest classifier to recognize the navigation elements (door, stairway and wall) from Kinect point clouds. This research acquires navigation elements and their 3-d location information from each single data frame through segmentation of point clouds, boundary extraction, feature calculation and classification. Finally, this paper utilizes the acquired navigation elements and their information to generate the state data of the indoor navigation module automatically. The experimental results demonstrate a high recognition accuracy of the proposed method.
Fast fingerprint database maintenance for indoor positioning based on UGV SLAM.
Tang, Jian; Chen, Yuwei; Chen, Liang; Liu, Jingbin; Hyyppä, Juha; Kukko, Antero; Kaartinen, Harri; Hyyppä, Hannu; Chen, Ruizhi
2015-03-04
Indoor positioning technology has become more and more important in the last two decades. Utilizing Received Signal Strength Indicator (RSSI) fingerprints of Signals of OPportunity (SOP) is a promising alternative navigation solution. However, as the RSSIs vary during operation due to their physical nature and are easily affected by the environmental change, one challenge of the indoor fingerprinting method is maintaining the RSSI fingerprint database in a timely and effective manner. In this paper, a solution for rapidly updating the fingerprint database is presented, based on a self-developed Unmanned Ground Vehicles (UGV) platform NAVIS. Several SOP sensors were installed on NAVIS for collecting indoor fingerprint information, including a digital compass collecting magnetic field intensity, a light sensor collecting light intensity, and a smartphone which collects the access point number and RSSIs of the pre-installed WiFi network. The NAVIS platform generates a map of the indoor environment and collects the SOPs during processing of the mapping, and then the SOP fingerprint database is interpolated and updated in real time. Field tests were carried out to evaluate the effectiveness and efficiency of the proposed method. The results showed that the fingerprint databases can be quickly created and updated with a higher sampling frequency (5Hz) and denser reference points compared with traditional methods, and the indoor map can be generated without prior information. Moreover, environmental changes could also be detected quickly for fingerprint indoor positioning.
Indoor Subspacing to Implement Indoorgml for Indoor Navigation
NASA Astrophysics Data System (ADS)
Jung, H.; Lee, J.
2015-10-01
According to an increasing demand for indoor navigation, there are great attempts to develop applicable indoor network. Representation for a room as a node is not sufficient to apply complex and large buildings. As OGC established IndoorGML, subspacing to partition the space for constructing logical network is introduced. Concerning subspacing for indoor network, transition space like halls or corridors also have to be considered. This study presents the subspacing process for creating an indoor network in shopping mall. Furthermore, categorization of transition space is performed and subspacing of this space is considered. Hall and squares in mall is especially defined for subspacing. Finally, implementation of subspacing process for indoor network is presented.
Georeferencing in Gnss-Challenged Environment: Integrating Uwb and Imu Technologies
NASA Astrophysics Data System (ADS)
Toth, C. K.; Koppanyi, Z.; Navratil, V.; Grejner-Brzezinska, D.
2017-05-01
Acquiring geospatial data in GNSS compromised environments remains a problem in mapping and positioning in general. Urban canyons, heavily vegetated areas, indoor environments represent different levels of GNSS signal availability from weak to no signal reception. Even outdoors, with multiple GNSS systems, with an ever-increasing number of satellites, there are many situations with limited or no access to GNSS signals. Independent navigation sensors, such as IMU can provide high-data rate information but their initial accuracy degrades quickly, as the measurement data drift over time unless positioning fixes are provided from another source. At The Ohio State University's Satellite Positioning and Inertial Navigation (SPIN) Laboratory, as one feasible solution, Ultra- Wideband (UWB) radio units are used to aid positioning and navigating in GNSS compromised environments, including indoor and outdoor scenarios. Here we report about experiences obtained with georeferencing a pushcart based sensor system under canopied areas. The positioning system is based on UWB and IMU sensor integration, and provides sensor platform orientation for an electromagnetic inference (EMI) sensor. Performance evaluation results are provided for various test scenarios, confirming acceptable results for applications where high accuracy is not required.
Fast Fingerprint Database Maintenance for Indoor Positioning Based on UGV SLAM
Tang, Jian; Chen, Yuwei; Chen, Liang; Liu, Jingbin; Hyyppä, Juha; Kukko, Antero; Kaartinen, Harri; Hyyppä, Hannu; Chen, Ruizhi
2015-01-01
Indoor positioning technology has become more and more important in the last two decades. Utilizing Received Signal Strength Indicator (RSSI) fingerprints of Signals of OPportunity (SOP) is a promising alternative navigation solution. However, as the RSSIs vary during operation due to their physical nature and are easily affected by the environmental change, one challenge of the indoor fingerprinting method is maintaining the RSSI fingerprint database in a timely and effective manner. In this paper, a solution for rapidly updating the fingerprint database is presented, based on a self-developed Unmanned Ground Vehicles (UGV) platform NAVIS. Several SOP sensors were installed on NAVIS for collecting indoor fingerprint information, including a digital compass collecting magnetic field intensity, a light sensor collecting light intensity, and a smartphone which collects the access point number and RSSIs of the pre-installed WiFi network. The NAVIS platform generates a map of the indoor environment and collects the SOPs during processing of the mapping, and then the SOP fingerprint database is interpolated and updated in real time. Field tests were carried out to evaluate the effectiveness and efficiency of the proposed method. The results showed that the fingerprint databases can be quickly created and updated with a higher sampling frequency (5Hz) and denser reference points compared with traditional methods, and the indoor map can be generated without prior information. Moreover, environmental changes could also be detected quickly for fingerprint indoor positioning. PMID:25746096
NASA Astrophysics Data System (ADS)
Chow, J. C. K.
2017-09-01
In the absence of external reference position information (e.g. surveyed targets or Global Navigation Satellite Systems) Simultaneous Localization and Mapping (SLAM) has proven to be an effective method for indoor navigation. The positioning drift can be reduced with regular loop-closures and global relaxation as the backend, thus achieving a good balance between exploration and exploitation. Although vision-based systems like laser scanners are typically deployed for SLAM, these sensors are heavy, energy inefficient, and expensive, making them unattractive for wearables or smartphone applications. However, the concept of SLAM can be extended to non-optical systems such as magnetometers. Instead of matching features such as walls and furniture using some variation of the Iterative Closest Point algorithm, the local magnetic field can be matched to provide loop-closure and global trajectory updates in a Gaussian Process (GP) SLAM framework. With a MEMS-based inertial measurement unit providing a continuous trajectory, and the matching of locally distinct magnetic field maps, experimental results in this paper show that a drift-free navigation solution in an indoor environment with millimetre-level accuracy can be achieved. The GP-SLAM approach presented can be formulated as a maximum a posteriori estimation problem and it can naturally perform loop-detection, feature-to-feature distance minimization, global trajectory optimization, and magnetic field map estimation simultaneously. Spatially continuous features (i.e. smooth magnetic field signatures) are used instead of discrete feature correspondences (e.g. point-to-point) as in conventional vision-based SLAM. These position updates from the ambient magnetic field also provide enough information for calibrating the accelerometer bias and gyroscope bias in-use. The only restriction for this method is the need for magnetic disturbances (which is typically not an issue for indoor environments); however, no assumptions are required for the general motion of the sensor (e.g. static periods).
Indoor integrated navigation and synchronous data acquisition method for Android smartphone
NASA Astrophysics Data System (ADS)
Hu, Chunsheng; Wei, Wenjian; Qin, Shiqiao; Wang, Xingshu; Habib, Ayman; Wang, Ruisheng
2015-08-01
Smartphones are widely used at present. Most smartphones have cameras and kinds of sensors, such as gyroscope, accelerometer and magnet meter. Indoor navigation based on smartphone is very important and valuable. According to the features of the smartphone and indoor navigation, a new indoor integrated navigation method is proposed, which uses MEMS (Micro-Electro-Mechanical Systems) IMU (Inertial Measurement Unit), camera and magnet meter of smartphone. The proposed navigation method mainly involves data acquisition, camera calibration, image measurement, IMU calibration, initial alignment, strapdown integral, zero velocity update and integrated navigation. Synchronous data acquisition of the sensors (gyroscope, accelerometer and magnet meter) and the camera is the base of the indoor navigation on the smartphone. A camera data acquisition method is introduced, which uses the camera class of Android to record images and time of smartphone camera. Two kinds of sensor data acquisition methods are introduced and compared. The first method records sensor data and time with the SensorManager of Android. The second method realizes open, close, data receiving and saving functions in C language, and calls the sensor functions in Java language with JNI interface. A data acquisition software is developed with JDK (Java Development Kit), Android ADT (Android Development Tools) and NDK (Native Development Kit). The software can record camera data, sensor data and time at the same time. Data acquisition experiments have been done with the developed software and Sumsang Note 2 smartphone. The experimental results show that the first method of sensor data acquisition is convenient but lost the sensor data sometimes, the second method is much better in real-time performance and much less in data losing. A checkerboard image is recorded, and the corner points of the checkerboard are detected with the Harris method. The sensor data of gyroscope, accelerometer and magnet meter have been recorded about 30 minutes. The bias stability and noise feature of the sensors have been analyzed. Besides the indoor integrated navigation, the integrated navigation and synchronous data acquisition method can be applied to outdoor navigation.
A 3D Model Based Imdoor Navigation System for Hubei Provincial Museum
NASA Astrophysics Data System (ADS)
Xu, W.; Kruminaite, M.; Onrust, B.; Liu, H.; Xiong, Q.; Zlatanova, S.
2013-11-01
3D models are more powerful than 2D maps for indoor navigation in a complicate space like Hubei Provincial Museum because they can provide accurate descriptions of locations of indoor objects (e.g., doors, windows, tables) and context information of these objects. In addition, the 3D model is the preferred navigation environment by the user according to the survey. Therefore a 3D model based indoor navigation system is developed for Hubei Provincial Museum to guide the visitors of museum. The system consists of three layers: application, web service and navigation, which is built to support localization, navigation and visualization functions of the system. There are three main strengths of this system: it stores all data needed in one database and processes most calculations on the webserver which make the mobile client very lightweight, the network used for navigation is extracted semi-automatically and renewable, the graphic user interface (GUI), which is based on a game engine, has high performance of visualizing 3D model on a mobile display.
Design, Implementation and Evaluation of an Indoor Navigation System for Visually Impaired People
Martinez-Sala, Alejandro Santos; Losilla, Fernando; Sánchez-Aarnoutse, Juan Carlos; García-Haro, Joan
2015-01-01
Indoor navigation is a challenging task for visually impaired people. Although there are guidance systems available for such purposes, they have some drawbacks that hamper their direct application in real-life situations. These systems are either too complex, inaccurate, or require very special conditions (i.e., rare in everyday life) to operate. In this regard, Ultra-Wideband (UWB) technology has been shown to be effective for indoor positioning, providing a high level of accuracy and low installation complexity. This paper presents SUGAR, an indoor navigation system for visually impaired people which uses UWB for positioning, a spatial database of the environment for pathfinding through the application of the A* algorithm, and a guidance module. The interaction with the user takes place using acoustic signals and voice commands played through headphones. The suitability of the system for indoor navigation has been verified by means of a functional and usable prototype through a field test with a blind person. In addition, other tests have been conducted in order to show the accuracy of different relevant parts of the system. PMID:26703610
Kumar, G. Ajay; Patil, Ashok Kumar; Patil, Rekha; Park, Seong Sill; Chai, Young Ho
2017-01-01
Mapping the environment of a vehicle and localizing a vehicle within that unknown environment are complex issues. Although many approaches based on various types of sensory inputs and computational concepts have been successfully utilized for ground robot localization, there is difficulty in localizing an unmanned aerial vehicle (UAV) due to variation in altitude and motion dynamics. This paper proposes a robust and efficient indoor mapping and localization solution for a UAV integrated with low-cost Light Detection and Ranging (LiDAR) and Inertial Measurement Unit (IMU) sensors. Considering the advantage of the typical geometric structure of indoor environments, the planar position of UAVs can be efficiently calculated from a point-to-point scan matching algorithm using measurements from a horizontally scanning primary LiDAR. The altitude of the UAV with respect to the floor can be estimated accurately using a vertically scanning secondary LiDAR scanner, which is mounted orthogonally to the primary LiDAR. Furthermore, a Kalman filter is used to derive the 3D position by fusing primary and secondary LiDAR data. Additionally, this work presents a novel method for its application in the real-time classification of a pipeline in an indoor map by integrating the proposed navigation approach. Classification of the pipeline is based on the pipe radius estimation considering the region of interest (ROI) and the typical angle. The ROI is selected by finding the nearest neighbors of the selected seed point in the pipeline point cloud, and the typical angle is estimated with the directional histogram. Experimental results are provided to determine the feasibility of the proposed navigation system and its integration with real-time application in industrial plant engineering. PMID:28574474
INL Autonomous Navigation System
DOE Office of Scientific and Technical Information (OSTI.GOV)
2005-03-30
The INL Autonomous Navigation System provides instructions for autonomously navigating a robot. The system permits high-speed autonomous navigation including obstacle avoidance, waypoing navigation and path planning in both indoor and outdoor environments.
Duque Domingo, Jaime; Cerrada, Carlos; Valero, Enrique; Cerrada, Jose A
2017-10-20
This work presents an Indoor Positioning System to estimate the location of people navigating in complex indoor environments. The developed technique combines WiFi Positioning Systems and depth maps , delivering promising results in complex inhabited environments, consisting of various connected rooms, where people are freely moving. This is a non-intrusive system in which personal information about subjects is not needed and, although RGB-D cameras are installed in the sensing area, users are only required to carry their smart-phones. In this article, the methods developed to combine the above-mentioned technologies and the experiments performed to test the system are detailed. The obtained results show a significant improvement in terms of accuracy and performance with respect to previous WiFi-based solutions as well as an extension in the range of operation.
Navigation of robotic system using cricket motes
NASA Astrophysics Data System (ADS)
Patil, Yogendra J.; Baine, Nicholas A.; Rattan, Kuldip S.
2011-06-01
This paper presents a novel algorithm for self-mapping of the cricket motes that can be used for indoor navigation of autonomous robotic systems. The cricket system is a wireless sensor network that can provide indoor localization service to its user via acoustic ranging techniques. The behavior of the ultrasonic transducer on the cricket mote is studied and the regions where satisfactorily distance measurements can be obtained are recorded. Placing the motes in these regions results fine-grain mapping of the cricket motes. Trilateration is used to obtain a rigid coordinate system, but is insufficient if the network is to be used for navigation. A modified SLAM algorithm is applied to overcome the shortcomings of trilateration. Finally, the self-mapped cricket motes can be used for navigation of autonomous robotic systems in an indoor location.
Autonomous indoor wayfinding for individuals with cognitive impairments
2010-01-01
Background A challenge to individuals with cognitive impairments in wayfinding is how to remain oriented, recall routines, and travel in unfamiliar areas in a way relying on limited cognitive capacity. While people without disabilities often use maps or written directions as navigation tools or for remaining oriented, this cognitively-impaired population is very sensitive to issues of abstraction (e.g. icons on maps or signage) and presents the designer with a challenge to tailor navigation information specific to each user and context. Methods This paper describes an approach to providing distributed cognition support of travel guidance for persons with cognitive disabilities. A solution is proposed based on passive near-field RFID tags and scanning PDAs. A prototype is built and tested in field experiments with real subjects. The unique strength of the system is the ability to provide unique-to-the-user prompts that are triggered by context. The key to the approach is to spread the context awareness across the system, with the context being flagged by the RFID tags and the appropriate response being evoked by displaying the appropriate path guidance images indexed by the intersection of specific end-user and context ID embedded in RFID tags. Results We found that passive RFIDs generally served as good context for triggering navigation prompts, although individual differences in effectiveness varied. The results of controlled experiments provided more evidence with regard to applicabilities of the proposed autonomous indoor wayfinding method. Conclusions Our findings suggest that the ability to adapt indoor wayfinding devices for appropriate timing of directions and standing orientation will be particularly important. PMID:20840786
NASA Astrophysics Data System (ADS)
Qin, M.; Wan, X.; Shao, Y. Y.; Li, S. Y.
2018-04-01
Vision-based navigation has become an attractive solution for autonomous navigation for planetary exploration. This paper presents our work of designing and building an autonomous vision-based GPS-denied unmanned vehicle and developing an ARFM (Adaptive Robust Feature Matching) based VO (Visual Odometry) software for its autonomous navigation. The hardware system is mainly composed of binocular stereo camera, a pan-and tilt, a master machine, a tracked chassis. And the ARFM-based VO software system contains four modules: camera calibration, ARFM-based 3D reconstruction, position and attitude calculation, BA (Bundle Adjustment) modules. Two VO experiments were carried out using both outdoor images from open dataset and indoor images captured by our vehicle, the results demonstrate that our vision-based unmanned vehicle is able to achieve autonomous localization and has the potential for future planetary exploration.
Fan, Qigao; Wu, Yaheng; Hui, Jing; Wu, Lei; Yu, Zhenzhong; Zhou, Lijuan
2014-01-01
In some GPS failure conditions, positioning for mobile target is difficult. This paper proposed a new method based on INS/UWB for attitude angle and position synchronous tracking of indoor carrier. Firstly, error model of INS/UWB integrated system is built, including error equation of INS and UWB. And combined filtering model of INS/UWB is researched. Simulation results show that the two subsystems are complementary. Secondly, integrated navigation data fusion strategy of INS/UWB based on Kalman filtering theory is proposed. Simulation results show that FAKF method is better than the conventional Kalman filtering. Finally, an indoor experiment platform is established to verify the integrated navigation theory of INS/UWB, which is geared to the needs of coal mine working environment. Static and dynamic positioning results show that the INS/UWB integrated navigation system is stable and real-time, positioning precision meets the requirements of working condition and is better than any independent subsystem.
Indoor Navigation by People with Visual Impairment Using a Digital Sign System
Legge, Gordon E.; Beckmann, Paul J.; Tjan, Bosco S.; Havey, Gary; Kramer, Kevin; Rolkosky, David; Gage, Rachel; Chen, Muzi; Puchakayala, Sravan; Rangarajan, Aravindhan
2013-01-01
There is a need for adaptive technology to enhance indoor wayfinding by visually-impaired people. To address this need, we have developed and tested a Digital Sign System. The hardware and software consist of digitally-encoded signs widely distributed throughout a building, a handheld sign-reader based on an infrared camera, image-processing software, and a talking digital map running on a mobile device. Four groups of subjects—blind, low vision, blindfolded sighted, and normally sighted controls—were evaluated on three navigation tasks. The results demonstrate that the technology can be used reliably in retrieving information from the signs during active mobility, in finding nearby points of interest, and following routes in a building from a starting location to a destination. The visually impaired subjects accurately and independently completed the navigation tasks, but took substantially longer than normally sighted controls. This fully functional prototype system demonstrates the feasibility of technology enabling independent indoor navigation by people with visual impairment. PMID:24116156
Indoor magnetic navigation for the blind.
Riehle, Timothy H; Anderson, Shane M; Lichter, Patrick A; Giudice, Nicholas A; Sheikh, Suneel I; Knuesel, Robert J; Kollmann, Daniel T; Hedin, Daniel S
2012-01-01
Indoor navigation technology is needed to support seamless mobility for the visually impaired. This paper describes the construction of and evaluation of a navigation system that infers the users' location using only magnetic sensing. It is well known that the environments within steel frame structures are subject to significant magnetic distortions. Many of these distortions are persistent and have sufficient strength and spatial characteristics to allow their use as the basis for a location technology. This paper describes the development and evaluation of a prototype magnetic navigation system consisting of a wireless magnetometer placed at the users' hip streaming magnetic readings to a smartphone processing location algorithms. Human trials were conducted to assess the efficacy of the system by studying route-following performance with blind and sighted subjects using the navigation system for real-time guidance.
Intelligent navigation and accurate positioning of an assist robot in indoor environments
NASA Astrophysics Data System (ADS)
Hua, Bin; Rama, Endri; Capi, Genci; Jindai, Mitsuru; Tsuri, Yosuke
2017-12-01
Intact robot's navigation and accurate positioning in indoor environments are still challenging tasks. Especially in robot applications, assisting disabled and/or elderly people in museums/art gallery environments. In this paper, we present a human-like navigation method, where the neural networks control the wheelchair robot to reach the goal location safely, by imitating the supervisor's motions, and positioning in the intended location. In a museum similar environment, the mobile robot starts navigation from various positions, and uses a low-cost camera to track the target picture, and a laser range finder to make a safe navigation. Results show that the neural controller with the Conjugate Gradient Backpropagation training algorithm gives a robust response to guide the mobile robot accurately to the goal position.
Pedestrian mobile mapping system for indoor environments based on MEMS IMU and range camera
NASA Astrophysics Data System (ADS)
Haala, N.; Fritsch, D.; Peter, M.; Khosravani, A. M.
2011-12-01
This paper describes an approach for the modeling of building interiors based on a mobile device, which integrates modules for pedestrian navigation and low-cost 3D data collection. Personal navigation is realized by a foot mounted low cost MEMS IMU, while 3D data capture for subsequent indoor modeling uses a low cost range camera, which was originally developed for gaming applications. Both steps, navigation and modeling, are supported by additional information as provided from the automatic interpretation of evacuation plans. Such emergency plans are compulsory for public buildings in a number of countries. They consist of an approximate floor plan, the current position and escape routes. Additionally, semantic information like stairs, elevators or the floor number is available. After the user has captured an image of such a floor plan, this information is made explicit again by an automatic raster-to-vector-conversion. The resulting coarse indoor model then provides constraints at stairs or building walls, which restrict the potential movement of the user. This information is then used to support pedestrian navigation by eliminating drift effects of the used low-cost sensor system. The approximate indoor building model additionally provides a priori information during subsequent indoor modeling. Within this process, the low cost range camera Kinect is used for the collection of multiple 3D point clouds, which are aligned by a suitable matching step and then further analyzed to refine the coarse building model.
Ganz, Aura; Schafer, James; Gandhi, Siddhesh; Puleo, Elaine; Wilson, Carole; Robertson, Meg
2012-01-01
We introduce PERCEPT system, an indoor navigation system for the blind and visually impaired. PERCEPT will improve the quality of life and health of the visually impaired community by enabling independent living. Using PERCEPT, blind users will have independent access to public health facilities such as clinics, hospitals, and wellness centers. Access to healthcare facilities is crucial for this population due to the multiple health conditions that they face such as diabetes and its complications. PERCEPT system trials with 24 blind and visually impaired users in a multistory building show PERCEPT system effectiveness in providing appropriate navigation instructions to these users. The uniqueness of our system is that it is affordable and that its design follows orientation and mobility principles. We hope that PERCEPT will become a standard deployed in all indoor public spaces, especially in healthcare and wellness facilities. PMID:23316225
Performance Characteristic Mems-Based IMUs for UAVs Navigation
NASA Astrophysics Data System (ADS)
Mohamed, H. A.; Hansen, J. M.; Elhabiby, M. M.; El-Sheimy, N.; Sesay, A. B.
2015-08-01
Accurate 3D reconstruction has become essential for non-traditional mapping applications such as urban planning, mining industry, environmental monitoring, navigation, surveillance, pipeline inspection, infrastructure monitoring, landslide hazard analysis, indoor localization, and military simulation. The needs of these applications cannot be satisfied by traditional mapping, which is based on dedicated data acquisition systems designed for mapping purposes. Recent advances in hardware and software development have made it possible to conduct accurate 3D mapping without using costly and high-end data acquisition systems. Low-cost digital cameras, laser scanners, and navigation systems can provide accurate mapping if they are properly integrated at the hardware and software levels. Unmanned Aerial Vehicles (UAVs) are emerging as a mobile mapping platform that can provide additional economical and practical advantages. However, such economical and practical requirements need navigation systems that can provide uninterrupted navigation solution. Hence, testing the performance characteristics of Micro-Electro-Mechanical Systems (MEMS) or low cost navigation sensors for various UAV applications is important research. This work focuses on studying the performance characteristics under different manoeuvres using inertial measurements integrated with single point positioning, Real-Time-Kinematic (RTK), and additional navigational aiding sensors. Furthermore, the performance of the inertial sensors is tested during Global Positioning System (GPS) signal outage.
Method of mobile robot indoor navigation by artificial landmarks with use of computer vision
NASA Astrophysics Data System (ADS)
Glibin, E. S.; Shevtsov, A. A.; Enik, O. A.
2018-05-01
The article describes an algorithm of the mobile robot indoor navigation based on the use of visual odometry. The results of the experiment identifying calculation errors in the distance traveled on a slip are presented. It is shown that the use of computer vision allows one to correct erroneous coordinates of the robot with the help of artificial landmarks. The control system utilizing the proposed method has been realized on the basis of Arduino Mego 2560 controller and a single-board computer Raspberry Pi 3. The results of the experiment on the mobile robot navigation with the use of this control system are presented.
Scene Recognition for Indoor Localization Using a Multi-Sensor Fusion Approach.
Liu, Mengyun; Chen, Ruizhi; Li, Deren; Chen, Yujin; Guo, Guangyi; Cao, Zhipeng; Pan, Yuanjin
2017-12-08
After decades of research, there is still no solution for indoor localization like the GNSS (Global Navigation Satellite System) solution for outdoor environments. The major reasons for this phenomenon are the complex spatial topology and RF transmission environment. To deal with these problems, an indoor scene constrained method for localization is proposed in this paper, which is inspired by the visual cognition ability of the human brain and the progress in the computer vision field regarding high-level image understanding. Furthermore, a multi-sensor fusion method is implemented on a commercial smartphone including cameras, WiFi and inertial sensors. Compared to former research, the camera on a smartphone is used to "see" which scene the user is in. With this information, a particle filter algorithm constrained by scene information is adopted to determine the final location. For indoor scene recognition, we take advantage of deep learning that has been proven to be highly effective in the computer vision community. For particle filter, both WiFi and magnetic field signals are used to update the weights of particles. Similar to other fingerprinting localization methods, there are two stages in the proposed system, offline training and online localization. In the offline stage, an indoor scene model is trained by Caffe (one of the most popular open source frameworks for deep learning) and a fingerprint database is constructed by user trajectories in different scenes. To reduce the volume requirement of training data for deep learning, a fine-tuned method is adopted for model training. In the online stage, a camera in a smartphone is used to recognize the initial scene. Then a particle filter algorithm is used to fuse the sensor data and determine the final location. To prove the effectiveness of the proposed method, an Android client and a web server are implemented. The Android client is used to collect data and locate a user. The web server is developed for indoor scene model training and communication with an Android client. To evaluate the performance, comparison experiments are conducted and the results demonstrate that a positioning accuracy of 1.32 m at 95% is achievable with the proposed solution. Both positioning accuracy and robustness are enhanced compared to approaches without scene constraint including commercial products such as IndoorAtlas.
Scene Recognition for Indoor Localization Using a Multi-Sensor Fusion Approach
Chen, Ruizhi; Li, Deren; Chen, Yujin; Guo, Guangyi; Cao, Zhipeng
2017-01-01
After decades of research, there is still no solution for indoor localization like the GNSS (Global Navigation Satellite System) solution for outdoor environments. The major reasons for this phenomenon are the complex spatial topology and RF transmission environment. To deal with these problems, an indoor scene constrained method for localization is proposed in this paper, which is inspired by the visual cognition ability of the human brain and the progress in the computer vision field regarding high-level image understanding. Furthermore, a multi-sensor fusion method is implemented on a commercial smartphone including cameras, WiFi and inertial sensors. Compared to former research, the camera on a smartphone is used to “see” which scene the user is in. With this information, a particle filter algorithm constrained by scene information is adopted to determine the final location. For indoor scene recognition, we take advantage of deep learning that has been proven to be highly effective in the computer vision community. For particle filter, both WiFi and magnetic field signals are used to update the weights of particles. Similar to other fingerprinting localization methods, there are two stages in the proposed system, offline training and online localization. In the offline stage, an indoor scene model is trained by Caffe (one of the most popular open source frameworks for deep learning) and a fingerprint database is constructed by user trajectories in different scenes. To reduce the volume requirement of training data for deep learning, a fine-tuned method is adopted for model training. In the online stage, a camera in a smartphone is used to recognize the initial scene. Then a particle filter algorithm is used to fuse the sensor data and determine the final location. To prove the effectiveness of the proposed method, an Android client and a web server are implemented. The Android client is used to collect data and locate a user. The web server is developed for indoor scene model training and communication with an Android client. To evaluate the performance, comparison experiments are conducted and the results demonstrate that a positioning accuracy of 1.32 m at 95% is achievable with the proposed solution. Both positioning accuracy and robustness are enhanced compared to approaches without scene constraint including commercial products such as IndoorAtlas. PMID:29292761
First Experiments with the Tango Tablet for Indoor Scanning
NASA Astrophysics Data System (ADS)
Diakité, Abdoulaye A.; Zlatanova, Sisi
2016-06-01
During the last two decades, the third dimension took an important place in the heart of every multimedia. While the 3D technologies mainly used to be tools and subject for researchers, they are becoming commercially available to large public. To make it even more accessible, the Project Tango, leaded by Google, integrates in a simple Android tablet sensors that are able to perform acquisition of the 3D information of a real life scene. This makes it possible for a large number of applications to have access to it, ranging from gaming to indoor navigation, including virtual and augmented reality. In this paper we investigate the ability of the Tango tablet to perform the acquisition of indoor building environment to support application such as indoor navigation. We proceed to several scans in different buildings and we study the characteristics of the output models.
NASA Astrophysics Data System (ADS)
Moafipoor, Shahram
Personal navigators (PN) have been studied for about a decade in different fields and applications, such as safety and rescue operations, security and emergency services, and police and military applications. The common goal of all these applications is to provide precise and reliable position, velocity, and heading information of each individual in various environments. In the PN system developed in this dissertation, the underlying assumption is that the system does not require pre-existing infrastructure to enable pedestrian navigation. To facilitate this capability, a multisensor system concept, based on the Global Positioning System (GPS), inertial navigation, barometer, magnetometer, and a human pedometry model has been developed. An important aspect of this design is to use the human body as navigation sensor to facilitate Dead Reckoning (DR) navigation in GPS-challenged environments. The system is designed predominantly for outdoor environments, where occasional loss of GPS lock may happen; however, testing and performance demonstration have been extended to indoor environments. DR navigation is based on a relative-measurement approach, with the key idea of integrating the incremental motion information in the form of step direction (SD) and step length (SL) over time. The foundation of the intelligent navigation system concept proposed here rests in exploiting the human locomotion pattern, as well as change of locomotion in varying environments. In this context, the term intelligent navigation represents the transition from the conventional point-to-point DR to dynamic navigation using the knowledge about the mechanism of the moving person. This approach increasingly relies on integrating knowledge-based systems (KBS) and artificial intelligence (AI) methodologies, including artificial neural networks (ANN) and fuzzy logic (FL). In addition, a general framework of the quality control for the real-time validation of the DR processing is proposed, based on a two-stage Kalman Filter approach. The performance comparison of the algorithm based on different field and simulated datasets, with varying levels of sensor errors, showed that 90 per cent success rate was achieved in detection of outliers for SL and 80 per cent for SD. The SL is predicted for both KBS-based ANN and FL approaches with an average accumulated error of 2 per cent, observed for the total distance traveled, which is generally an improvement over most of the existing pedometry systems. The target accuracy of the system is +/-(3-5)m CEP50 (circular error, probable 50%). This dissertation provides a performance analysis in the outdoor and indoor environments for different operators. Another objective of this dissertation is to test the system's navigation limitation in DR mode in terms of time and trajectory length in order to determine the upper limit of indoor operations. It was determined that for more than four indoor loops, where the user walked 261m in about 6.5 minutes, the DR performance met the required accuracy specifications. However, these results are only relevant to the existing data. Future studies should consider more comprehensive performance analysis for longer trajectories in challenging environments and possible extension to image-based navigation to expand the indoor capability of the system.
Swarm Optimization-Based Magnetometer Calibration for Personal Handheld Devices
Ali, Abdelrahman; Siddharth, Siddharth; Syed, Zainab; El-Sheimy, Naser
2012-01-01
Inertial Navigation Systems (INS) consist of accelerometers, gyroscopes and a processor that generates position and orientation solutions by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the user heading based on Earth's magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are usually corrupted by several errors, including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO)-based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometers. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. Furthermore, the proposed algorithm can help in the development of Pedestrian Navigation Devices (PNDs) when combined with inertial sensors and GPS/Wi-Fi for indoor navigation and Location Based Services (LBS) applications.
Implementation of a vector-based tracking loop receiver in a pseudolite navigation system.
So, Hyoungmin; Lee, Taikjin; Jeon, Sanghoon; Kim, Chongwon; Kee, Changdon; Kim, Taehee; Lee, Sanguk
2010-01-01
We propose a vector tracking loop (VTL) algorithm for an asynchronous pseudolite navigation system. It was implemented in a software receiver and experiments in an indoor navigation system were conducted. Test results show that the VTL successfully tracks signals against the near-far problem, one of the major limitations in pseudolite navigation systems, and could improve positioning availability by extending pseudolite navigation coverage.
To localise or to be localised with WiFi in the Hubei museum?
NASA Astrophysics Data System (ADS)
Verbree, E.; Zlatanova, S.; van Winden, K. B. A.; van der Laan, E. B.; Makri, A.; Taizhou, L.; Haojun, A.
2013-11-01
Indoor localisation is in demand for a variety of applications within the built environment. An overall solution based on a single technology has not yet been determined. The aim of this paper is to gain insight on Signal Strength monitoring by a special kind of WiFi Monitors in comparison to the commonly known fingerprinting method for the purpose of a 3D indoor navigation system. Ttwo different WiFi based localisation techniques are tested during the MSc Geomatics DaRen Syntheses Project in the Hubei Provincial Museum, China. The first method detects the beacon frames send by smartphones, laptops and other WiFi enabled devices in range using Libelium Meshlium Xtreme monitors. Their MAC addresses and the signal strength is measured by the Meshlium Xtreme and stored on an external database. We call this method WiFi monitoring. The second method a Wifi enabled device, like a smartphone, measures the signal strength of multiple Wifi Access Points in range to localise itself based on a previously created radio map. This method is known as WiFi fingerprinting. Both methods have some advantages and disadvantages. Advantages of the common way of WiFi fingerprinting are that the implementation costs are relatively low, because it is usually possible to use (a part of) the existing WiFi AP infrastructure. WiFi fingerprinting can reach a relatively high accuracy in the order of magnitude of meters. Finally, the location granularity can be adjusted to what is necessary for the purpose of the indoor localisation. This makes it employable for a wide range of purposes. The question remains how suitable these methods are for a 3D indoor navigation system for the Hubei provincial museum. One important aspect is the localisation-granularity necessary for the application. In a museum it is not necessary to know the exact X,Y position of a user (such high accuracy is unnecessary), more important is to know in which room the user is located so the information on exhibitions can be presented and the starting point of the navigation can be determined. Both methods can track the user and tell the room he or she is located at. Although WiFi smartphone monitoring may have a low update frequency it is still suitable for a navigation system for a museum since visitors usually spend more than a couple of minutes within a room.
An Agent-Based Model for Navigation Simulation in a Heterogeneous Environment
ERIC Educational Resources Information Center
Shanklin, Teresa A.
2012-01-01
Complex navigation (e.g. indoor and outdoor environments) can be studied as a system-of-systems problem. The model is made up of disparate systems that can aid a user in navigating from one location to another, utilizing whatever sensor system or information is available. By using intelligent navigation sensors and techniques (e.g. RFID, Wifi,…
Diaz-Estrella, Antonio; Reyes-Lecuona, Arcadio; Langley, Alyson; Brown, Michael; Sharples, Sarah
2018-01-01
Inertial sensors offer the potential for integration into wireless virtual reality systems that allow the users to walk freely through virtual environments. However, owing to drift errors, inertial sensors cannot accurately estimate head and body orientations in the long run, and when walking indoors, this error cannot be corrected by magnetometers, due to the magnetic field distortion created by ferromagnetic materials present in buildings. This paper proposes a technique, called EHBD (Equalization of Head and Body Directions), to address this problem using two head- and shoulder-located magnetometers. Due to their proximity, their distortions are assumed to be similar and the magnetometer measurements are used to detect when the user is looking straight forward. Then, the system corrects the discrepancies between the estimated directions of the head and the shoulder, which are provided by gyroscopes and consequently are affected by drift errors. An experiment is conducted to evaluate the performance of this technique in two tasks (navigation and navigation plus exploration) and using two different locomotion techniques: (1) gaze-directed mode (GD) in which the walking direction is forced to be the same as the head direction, and (2) decoupled direction mode (DD) in which the walking direction can be different from the viewing direction. The obtained results show that both locomotion modes show similar matching of the target path during the navigation task, while DD’s path matches the target path more closely than GD in the navigation plus exploration task. These results validate the EHBD technique especially when allowing different walking and viewing directions in the navigation plus exploration tasks, as expected. While the proposed method does not reach the accuracy of optical tracking (ideal case), it is an acceptable and satisfactory solution for users and is much more compact, portable and economical. PMID:29621298
Indoor Navigation using Direction Sensor and Beacons
NASA Technical Reports Server (NTRS)
Shields, Joel; Jeganathan, Muthu
2004-01-01
A system for indoor navigation of a mobile robot includes (1) modulated infrared beacons at known positions on the walls and ceiling of a room and (2) a cameralike sensor, comprising a wide-angle lens with a position-sensitive photodetector at the focal plane, mounted in a known position and orientation on the robot. The system also includes a computer running special-purpose software that processes the sensor readings to obtain the position and orientation of the robot in all six degrees of freedom in a coordinate system embedded in the room.
Canoe: An Autonomous Infrastructure-Free Indoor Navigation System.
Dong, Kai; Wu, Wenjia; Ye, Haibo; Yang, Ming; Ling, Zhen; Yu, Wei
2017-04-30
The development of the Internet of Things (IoT) has accelerated research in indoor navigation systems, a majority of which rely on adequate wireless signals and sources. Nonetheless, deploying such a system requires periodic site-survey, which is time consuming and labor intensive. To address this issue, in this paper we present Canoe , an indoor navigation system that considers shopping mall scenarios. In our system, we do not assume any prior knowledge, such as floor-plan or the shop locations, access point placement or power settings, historical RSS measurements or fingerprints, etc. Instead, Canoe requires only that the shop owners collect and publish RSS values at the entrances of their shops and can direct a consumer to any of these shops by comparing the observed RSS values. The locations of the consumers and the shops are estimated using maximum likelihood estimation. In doing this, the direction of the target shop relative to the current orientation of the consumer can be precisely computed, such that the direction that a consumer should move can be determined. We have conducted extensive simulations using a real-world dataset. Our experiments in a real shopping mall demonstrate that if 50% of the shops publish their RSS values, Canoe can precisely navigate a consumer within 30 s, with an error rate below 9%.
Canoe: An Autonomous Infrastructure-Free Indoor Navigation System
Dong, Kai; Wu, Wenjia; Ye, Haibo; Yang, Ming; Ling, Zhen; Yu, Wei
2017-01-01
The development of the Internet of Things (IoT) has accelerated research in indoor navigation systems, a majority of which rely on adequate wireless signals and sources. Nonetheless, deploying such a system requires periodic site-survey, which is time consuming and labor intensive. To address this issue, in this paper we present Canoe, an indoor navigation system that considers shopping mall scenarios. In our system, we do not assume any prior knowledge, such as floor-plan or the shop locations, access point placement or power settings, historical RSS measurements or fingerprints, etc. Instead, Canoe requires only that the shop owners collect and publish RSS values at the entrances of their shops and can direct a consumer to any of these shops by comparing the observed RSS values. The locations of the consumers and the shops are estimated using maximum likelihood estimation. In doing this, the direction of the target shop relative to the current orientation of the consumer can be precisely computed, such that the direction that a consumer should move can be determined. We have conducted extensive simulations using a real-world dataset. Our experiments in a real shopping mall demonstrate that if 50% of the shops publish their RSS values, Canoe can precisely navigate a consumer within 30 s, with an error rate below 9%. PMID:28468291
Tian, Qinglin; Salcic, Zoran; Wang, Kevin I-Kai; Pan, Yun
2015-12-05
Pedestrian dead reckoning is a common technique applied in indoor inertial navigation systems that is able to provide accurate tracking performance within short distances. Sensor drift is the main bottleneck in extending the system to long-distance and long-term tracking. In this paper, a hybrid system integrating traditional pedestrian dead reckoning based on the use of inertial measurement units, short-range radio frequency systems and particle filter map matching is proposed. The system is a drift-free pedestrian navigation system where position error and sensor drift is regularly corrected and is able to provide long-term accurate and reliable tracking. Moreover, the whole system is implemented on a commercial off-the-shelf smartphone and achieves real-time positioning and tracking performance with satisfactory accuracy.
Tracked robot controllers for climbing obstacles autonomously
NASA Astrophysics Data System (ADS)
Vincent, Isabelle
2009-05-01
Research in mobile robot navigation has demonstrated some success in navigating flat indoor environments while avoiding obstacles. However, the challenge of analyzing complex environments to climb obstacles autonomously has had very little success due to the complexity of the task. Unmanned ground vehicles currently exhibit simple autonomous behaviours compared to the human ability to move in the world. This paper presents the control algorithms designed for a tracked mobile robot to autonomously climb obstacles by varying its tracks configuration. Two control algorithms are proposed to solve the autonomous locomotion problem for climbing obstacles. First, a reactive controller evaluates the appropriate geometric configuration based on terrain and vehicle geometric considerations. Then, a reinforcement learning algorithm finds alternative solutions when the reactive controller gets stuck while climbing an obstacle. The methodology combines reactivity to learning. The controllers have been demonstrated in box and stair climbing simulations. The experiments illustrate the effectiveness of the proposed approach for crossing obstacles.
NASA Astrophysics Data System (ADS)
Namie, Hiromune; Morishita, Hisashi
The authors focused on the development of an indoor positioning system which is easy to use, portable and available for everyone. This system is capable of providing the correct position anywhere indoors, including onboard ships, and was invented in order to evaluate the availability of GPS indoors. Although the performance of GPS is superior outdoors, there has been considerable research regarding indoor GPS involving sensitive GPS, pseudolites (GPS pseudo satellite), RFID (Radio Frequency IDentification) tags, and wireless LAN .However, the positioning rate and the precision are not high enough for general use, which is the reason why these technologies have not yet spread to personal navigation systems. In this regard, the authors attempted to implement an indoor positioning system using cellular phones with built-in GPS and infrared light data communication functionality, which are widely used in Japan. GPS is becoming increasingly popular, where GPGGS sentences of the NMEA outputted from the GPS receiver provide spatiotemporal information including latitude, longitude, altitude, and time or ECEF xyz coordinates. As GPS applications grow rapidly, spatiotemporal data becomes key to the ubiquitous outdoor and indoor seamless positioning services at least for the entire area of Japan, as well as to becoming familiar with satellite positioning systems (e.g. GPS). Furthermore, the authors are also working on the idea of using PDAs (Personal Digital Assistants), as cellular phones with built-in GPS and PDA functionality are also becoming increasingly popular.
Gao, Yanbin; Liu, Shifei; Atia, Mohamed M.; Noureldin, Aboelmagd
2015-01-01
This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory. PMID:26389906
A BLE-Based Pedestrian Navigation System for Car Searching in Indoor Parking Garages
Wang, Sheng-Shih
2018-01-01
The continuous global increase in the number of cars has led to an increase in parking issues, particularly with respect to the search for available parking spaces and finding cars. In this paper, we propose a navigation system for car owners to find their cars in indoor parking garages. The proposed system comprises a car-searching mobile app and a positioning-assisting subsystem. The app guides car owners to their cars based on a “turn-by-turn” navigation strategy, and has the ability to correct the user’s heading orientation. The subsystem uses beacon technology for indoor positioning, supporting self-guidance of the car-searching mobile app. This study also designed a local coordinate system to support the identification of the locations of parking spaces and beacon devices. We used Android as the platform to implement the proposed car-searching mobile app, and used Bytereal HiBeacon devices to implement the proposed positioning-assisting subsystem. We also deployed the system in a parking lot in our campus for testing. The experimental results verified that the proposed system not only works well, but also provides the car owner with the correct route guidance information. PMID:29734753
Gao, Yanbin; Liu, Shifei; Atia, Mohamed M; Noureldin, Aboelmagd
2015-09-15
This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory.
Position, Location, Place and Area: AN Indoor Perspective
NASA Astrophysics Data System (ADS)
Sithole, George; Zlatanova, Sisi
2016-06-01
Over the last decade, harnessing the commercial potential of smart mobile devices in indoor environments has spurred interest in indoor mapping and navigation. Users experience indoor environments differently. For this reason navigational models have to be designed to adapt to a user's personality, and to reflect as many cognitive maps as possible. This paper presents an extension of a previously proposed framework. In this extension the notion of placement is accounted for, thereby enabling one aspect of the `personalised indoor experience'. In the paper, firstly referential expressions are used as a tool to discuss the different ways of thinking of placement within indoor spaces. Next, placement is expressed in terms of the concept of Position, Location, Place and Area. Finally, the previously proposed framework is extended to include these concepts of placement. An example is provided of the use of the extended framework. Notable characteristics of the framework are: (1) Sub-spaces, resources and agents can simultaneously possess different types of placement, e.g., a person in a room can have an xyz position and a location defined by the room number. While these entities can simultaneously have different forms of placement, only one is dominant. (2) Sub-spaces, resources and agents are capable of possessing modifiers that alter their access and usage. (3) Sub-spaces inherit the modifiers of the resources or agents contained in them. (4) Unlike conventional navigational models which treat resources and obstacles as different types of entities, in the proposed framework there are only resources and whether a resource is an obstacle is determined by a modifier that determines whether a user can access the resource. The power of the framework is that it blends the geometry and topology of space, the influence of human activity within sub-spaces together with the different notions of placement in a way that is simple and yet very flexible.
Magnetic Field Aided Indoor Navigation
2009-03-01
fields; this 13 compass was made to look like the big dipper , so that the end of the bowl would point in the horizontal northward direction, also like...the big dipper [1]. From these early observations and uses, merchants began using compasses to navigate to their various trading locations. This was
Indoor Air Quality in Schools: Understanding the Problem and Finding the Solution.
ERIC Educational Resources Information Center
Bacci, Geoff
2002-01-01
Describes issues and solutions involving indoor air quality in school. Includes indoor air quality action plans, the role of the environmental consultant, and resources available to help school districts develop an indoor air quality action plan. (PKP)
A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots.
Sherwin, Tyrone; Easte, Mikala; Chen, Andrew Tzer-Yeu; Wang, Kevin I-Kai; Dai, Wenbin
2018-02-14
Location-aware services are one of the key elements of modern intelligent applications. Numerous real-world applications such as factory automation, indoor delivery, and even search and rescue scenarios require autonomous robots to have the ability to navigate in an unknown environment and reach mobile targets with minimal or no prior infrastructure deployment. This research investigates and proposes a novel approach of dynamic target localisation using a single RF emitter, which will be used as the basis of allowing autonomous robots to navigate towards and reach a target. Through the use of multiple directional antennae, Received Signal Strength (RSS) is compared to determine the most probable direction of the targeted emitter, which is combined with the distance estimates to improve the localisation performance. The accuracy of the position estimate is further improved using a particle filter to mitigate the fluctuating nature of real-time RSS data. Based on the direction information, a motion control algorithm is proposed, using Simultaneous Localisation and Mapping (SLAM) and A* path planning to enable navigation through unknown complex environments. A number of navigation scenarios were developed in the context of factory automation applications to demonstrate and evaluate the functionality and performance of the proposed system.
A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots
Sherwin, Tyrone; Easte, Mikala; Wang, Kevin I-Kai; Dai, Wenbin
2018-01-01
Location-aware services are one of the key elements of modern intelligent applications. Numerous real-world applications such as factory automation, indoor delivery, and even search and rescue scenarios require autonomous robots to have the ability to navigate in an unknown environment and reach mobile targets with minimal or no prior infrastructure deployment. This research investigates and proposes a novel approach of dynamic target localisation using a single RF emitter, which will be used as the basis of allowing autonomous robots to navigate towards and reach a target. Through the use of multiple directional antennae, Received Signal Strength (RSS) is compared to determine the most probable direction of the targeted emitter, which is combined with the distance estimates to improve the localisation performance. The accuracy of the position estimate is further improved using a particle filter to mitigate the fluctuating nature of real-time RSS data. Based on the direction information, a motion control algorithm is proposed, using Simultaneous Localisation and Mapping (SLAM) and A* path planning to enable navigation through unknown complex environments. A number of navigation scenarios were developed in the context of factory automation applications to demonstrate and evaluate the functionality and performance of the proposed system. PMID:29443906
Indoor Positioning System Using Magnetic Field Map Navigation and an Encoder System
Kim, Han-Sol; Seo, Woojin; Baek, Kwang-Ryul
2017-01-01
In the indoor environment, variation of the magnetic field is caused by building structures, and magnetic field map navigation is based on this feature. In order to estimate position using this navigation, a three-axis magnetic field must be measured at every point to build a magnetic field map. After the magnetic field map is obtained, the position of the mobile robot can be estimated with a likelihood function whereby the measured magnetic field data and the magnetic field map are used. However, if only magnetic field map navigation is used, the estimated position can have large errors. In order to improve performance, we propose a particle filter system that integrates magnetic field map navigation and an encoder system. In this paper, multiple magnetic sensors and three magnetic field maps (a horizontal intensity map, a vertical intensity map, and a direction information map) are used to update the weights of particles. As a result, the proposed system estimates the position and orientation of a mobile robot more accurately than previous systems. Also, when the number of magnetic sensors increases, this paper shows that system performance improves. Finally, experiment results are shown from the proposed system that was implemented and evaluated. PMID:28327513
Indoor Positioning System Using Magnetic Field Map Navigation and an Encoder System.
Kim, Han-Sol; Seo, Woojin; Baek, Kwang-Ryul
2017-03-22
In the indoor environment, variation of the magnetic field is caused by building structures, and magnetic field map navigation is based on this feature. In order to estimate position using this navigation, a three-axis magnetic field must be measured at every point to build a magnetic field map. After the magnetic field map is obtained, the position of the mobile robot can be estimated with a likelihood function whereby the measured magnetic field data and the magnetic field map are used. However, if only magnetic field map navigation is used, the estimated position can have large errors. In order to improve performance, we propose a particle filter system that integrates magnetic field map navigation and an encoder system. In this paper, multiple magnetic sensors and three magnetic field maps (a horizontal intensity map, a vertical intensity map, and a direction information map) are used to update the weights of particles. As a result, the proposed system estimates the position and orientation of a mobile robot more accurately than previous systems. Also, when the number of magnetic sensors increases, this paper shows that system performance improves. Finally, experiment results are shown from the proposed system that was implemented and evaluated.
National Guard Counterdrug Programs
2001-02-14
comparisons to locate indoor Marijuana grows, outdoor infrastructure - Monitor activity at known sites - Meth labs, stash houses, marijuana grows - Real...Identifies key signatures of structures for indoor growth of cannabis - Vehiclelvessel surveillance * Video capabilities for evidence e Global Positioning...System Navigational Equipment - Identify marijuana locations for ground recovery Contact Information Voice (703) 607-5665 DSN Voice 327-5665 FAX (703
Automatic Generation of Indoor Navigable Space Using a Point Cloud and its Scanner Trajectory
NASA Astrophysics Data System (ADS)
Staats, B. R.; Diakité, A. A.; Voûte, R. L.; Zlatanova, S.
2017-09-01
Automatic generation of indoor navigable models is mostly based on 2D floor plans. However, in many cases the floor plans are out of date. Buildings are not always built according to their blue prints, interiors might change after a few years because of modified walls and doors, and furniture may be repositioned to the user's preferences. Therefore, new approaches for the quick recording of indoor environments should be investigated. This paper concentrates on laser scanning with a Mobile Laser Scanner (MLS) device. The MLS device stores a point cloud and its trajectory. If the MLS device is operated by a human, the trajectory contains information which can be used to distinguish different surfaces. In this paper a method is presented for the identification of walkable surfaces based on the analysis of the point cloud and the trajectory of the MLS scanner. This method consists of several steps. First, the point cloud is voxelized. Second, the trajectory is analysing and projecting to acquire seed voxels. Third, these seed voxels are generated into floor regions by the use of a region growing process. By identifying dynamic objects, doors and furniture, these floor regions can be modified so that each region represents a specific navigable space inside a building as a free navigable voxel space. By combining the point cloud and its corresponding trajectory, the walkable space can be identified for any type of building even if the interior is scanned during business hours.
SYNAISTHISI: an IoT-powered smart visitor management and cognitive recommendations system
NASA Astrophysics Data System (ADS)
Thanos, Giorgos Konstandinos; Karafylli, Christina; Karafylli, Maria; Zacharakis, Dimitris; Papadimitriou, Apostolis; Dimitros, Kostantinos; Kanellopoulou, Konstantina; Kyriazanos, Dimitris M.; Thomopoulos, Stelios C. A.
2016-05-01
Location-based and navigation services are really needed to help visitors and audience of big events, complex buildings, shopping malls, airports and large companies. However, the lack of GPS and proper mapping indoors usually renders location-based applications and services useless or simply not applicable in such environments. SYNAISTHISI introduces a mobile application for smartphones which offers navigation capabilities outside and inside buildings and through multiple floor levels. The application comes together with a suite of helpful services, including personalized recommendations, visit/event management and a helpful search functionality in order to navigate to a specific location, event or person. As the user finds his way towards his destination, NFC-enabled checkpoints and bluetooth beacons assist him, while offering re-routing, check-in/out capabilities and useful information about ongoing meetings and nearby events. The application is supported by a back-end GIS system which can provide a broad and clear view to event organizers, campus managers and field personnel for purposes of event logistics, safety and security. SYNAISTHISI system comes with plenty competitive advantages including (a) Seamless Navigation as users move between outdoor and indoor areas and different floor levels by using innovative routing algorithms, (b) connection to and powered by IoT platform, for localization and real-time information feedback, (c) dynamic personalized recommendations based on user profile, location and real-time information provided by the IoT platform and (d) Indoor localization without the need for expensive infrastructure and installations.
Brayfield, Brad P.
2016-01-01
The navigation of bees and ants from hive to food and back has captivated people for more than a century. Recently, the Navigation by Scene Familiarity Hypothesis (NSFH) has been proposed as a parsimonious approach that is congruent with the limited neural elements of these insects’ brains. In the NSFH approach, an agent completes an initial training excursion, storing images along the way. To retrace the path, the agent scans the area and compares the current scenes to those previously experienced. By turning and moving to minimize the pixel-by-pixel differences between encountered and stored scenes, the agent is guided along the path without having memorized the sequence. An important premise of the NSFH is that the visual information of the environment is adequate to guide navigation without aliasing. Here we demonstrate that an image landscape of an indoor setting possesses ample navigational information. We produced a visual landscape of our laboratory and part of the adjoining corridor consisting of 2816 panoramic snapshots arranged in a grid at 12.7-cm centers. We show that pixel-by-pixel comparisons of these images yield robust translational and rotational visual information. We also produced a simple algorithm that tracks previously experienced routes within our lab based on an insect-inspired scene familiarity approach and demonstrate that adequate visual information exists for an agent to retrace complex training routes, including those where the path’s end is not visible from its origin. We used this landscape to systematically test the interplay of sensor morphology, angles of inspection, and similarity threshold with the recapitulation performance of the agent. Finally, we compared the relative information content and chance of aliasing within our visually rich laboratory landscape to scenes acquired from indoor corridors with more repetitive scenery. PMID:27119720
Comparative analysis of ROS-based monocular SLAM methods for indoor navigation
NASA Astrophysics Data System (ADS)
Buyval, Alexander; Afanasyev, Ilya; Magid, Evgeni
2017-03-01
This paper presents a comparison of four most recent ROS-based monocular SLAM-related methods: ORB-SLAM, REMODE, LSD-SLAM, and DPPTAM, and analyzes their feasibility for a mobile robot application in indoor environment. We tested these methods using video data that was recorded from a conventional wide-angle full HD webcam with a rolling shutter. The camera was mounted on a human-operated prototype of an unmanned ground vehicle, which followed a closed-loop trajectory. Both feature-based methods (ORB-SLAM, REMODE) and direct SLAMrelated algorithms (LSD-SLAM, DPPTAM) demonstrated reasonably good results in detection of volumetric objects, corners, obstacles and other local features. However, we met difficulties with recovering typical for offices homogeneously colored walls, since all of these methods created empty spaces in a reconstructed sparse 3D scene. This may cause collisions of an autonomously guided robot with unfeatured walls and thus limits applicability of maps, which are obtained by the considered monocular SLAM-related methods for indoor robot navigation.
wayGoo: a platform for geolocating and managing indoor and outdoor spaces
NASA Astrophysics Data System (ADS)
Thomopoulos, Stelios C. A.; Karafylli, Christina; Karafylli, Maria; Motos, Dionysis; Lampropoulos, Vassilis; Dimitros, Kostantinos; Margonis, Christos
2016-05-01
wayGoo2 is a platform for Geolocating and Managing indoor and outdoor spaces and content with multidimensional indoor and outdoor Navigation and Guidance. Its main components are a Geographic Information System, a back-end server, front-end applications and a web-based Content Management System (CMS). It constitutes a fully integrated 2D/3D space and content management system that creates a repository that consists of a database, content components and administrative data. wayGoo can connect to any third party database and event management data-source. The platform is secure as the data is only available through a Restful web service using https security protocol in conjunction with an API key used for authentication. To enhance users experience, wayGoo makes the content available by extracting components out of the repository and constructing targeted applications. The wayGoo platform supports geo-referencing of indoor and outdoor information and use of metadata. It also allows the use of existing information such as maps and databases. The platform enables planning through integration of content that is connected either spatially, temporally or contextually, and provides immediate access to all spatial data through interfaces and interactive 2D and 3D representations. wayGoo constitutes a mean to document and preserve assets through computerized techniques and provides a system that enhances the protection of your space, people and guests when combined with wayGoo notification and alert system. It constitutes a strong marketing tool providing staff and visitors with an immersive tool for navigation in indoor spaces and allowing users to organize their agenda and to discover events through wayGoo event scheduler and recommendation system. Furthermore, the wayGoo platform can be used in Security applications and event management, e.g. CBRNE incidents, man-made and natural disasters, etc., to document and geolocate information and sensor data (off line and real time) on one end, and offer navigation capabilities in indoor and outdoor spaces. Furthermore, the wayGoo platform can be used for the creation of immersive environments and experiences in conjunction with VR/AR (Virtual and Augmented Reality) technologies.
Gunther, Eric J M; Sliker, Levin J; Bodine, Cathy
2017-11-01
Unemployment among the almost 5 million working-age adults with cognitive disabilities in the USA is a costly problem in both tax dollars and quality of life. Job coaching is an effective tool to overcome this, but the cost of job coaching services sums with every new employee or change of employment roles. There is a need for a cost-effective, automated alternative to job coaching that incurs a one-time cost and can be reused for multiple employees or roles. An effective automated job coach must be aware of its location and the location of destinations within the job site. This project presents a design and prototype of a cart-mounted indoor positioning and navigation system with necessary original software using Ultra High Frequency Radio Frequency Identification (UHF RFID). The system presented in this project for use within a warehouse setting is one component of an automated job coach to assist in the job of order filler. The system demonstrated accuracy to within 0.3 m under the correct conditions with strong potential to serve as the basis for an effective indoor navigation system to assist warehouse workers with disabilities. Implications for rehabilitation An automated job coach could improve employability of and job retention for people with cognitive disabilities. An indoor navigation system using ultra high frequency radio frequency identification was proposed with an average positioning accuracy of 0.3 m. The proposed system, in combination with a non-linear context-aware prompting system, could be used as an automated job coach for warehouse order fillers with cognitive disabilities.
Problems In Indoor Mapping and Modelling
NASA Astrophysics Data System (ADS)
Zlatanova, S.; Sithole, G.; Nakagawa, M.; Zhu, Q.
2013-11-01
Research in support of indoor mapping and modelling (IMM) has been active for over thirty years. This research has come in the form of As-Built surveys, Data structuring, Visualisation techniques, Navigation models and so forth. Much of this research is founded on advancements in photogrammetry, computer vision and image analysis, computer graphics, robotics, laser scanning and many others. While IMM used to be the privy of engineers, planners, consultants, contractors, and designers, this is no longer the case as commercial enterprises and individuals are also beginning to apply indoor models in their business process and applications. There are three main reasons for this. Firstly, the last two decades have seen greater use of spatial information by enterprises and the public. Secondly, IMM has been complimented by advancements in mobile computing and internet communications, making it easier than ever to access and interact with spatial information. Thirdly, indoor modelling has been advanced geometrically and semantically, opening doors for developing user-oriented, context-aware applications. This reshaping of the public's attitude and expectations with regards to spatial information has realised new applications and spurred demand for indoor models and the tools to use them. This paper examines the present state of IMM and considers the research areas that deserve attention in the future. In particular the paper considers problems in IMM that are relevant to commercial enterprises and the general public, groups this paper expects will emerge as the greatest users IMM. The subject of indoor modelling and mapping is discussed here in terms of Acquisitions and Sensors, Data Structures and Modelling, Visualisation, Applications, Legal Issues and Standards. Problems are discussed in terms of those that exist and those that are emerging. Existing problems are those that are currently being researched. Emerging problems are those problems or demands that are expected to arise because of social changes, technological advancements, or commercial interests. The motivation of this work is to define a set of research problems that are either being investigated or should be investigated. These will hopefully provide a framework for assessing progress and advances in indoor modelling. The framework will be developed in the form of a problem matrix, detailing existing and emerging problems, their solutions and present best practices. Once the framework is complete it will be published online so that the IMM community can discuss and modify it as necessary. When the framework has reached a steady state an empirical benchmark will be provided to test solutions to posed problems. A yearly evaluation of the problem matrix will follow, the results of which will be published.
2010-11-01
3-10 Multiple Images of an Image Sequence Figure 3-10 A Digital Magnetic Compass from KVH Industries 3-11 Figure 3-11 Earth’s Magnetic Field 3-11...ARINO SENER – Ingenieria y Sistemas S.A Aerospace Division Parque Tecnologico de Madrid Calle Severo Ocho 4 28760 Tres Cantos Madrid Email...experts from government, academia, industry and the military produced an analysis of future navigation sensors and systems whose performance
Numerical evaluation of mobile robot navigation in static indoor environment via EGAOR Iteration
NASA Astrophysics Data System (ADS)
Dahalan, A. A.; Saudi, A.; Sulaiman, J.; Din, W. R. W.
2017-09-01
One of the key issues in mobile robot navigation is the ability for the robot to move from an arbitrary start location to a specified goal location without colliding with any obstacles while traveling, also known as mobile robot path planning problem. In this paper, however, we examined the performance of a robust searching algorithm that relies on the use of harmonic potentials of the environment to generate smooth and safe path for mobile robot navigation in a static known indoor environment. The harmonic potentials will be discretized by using Laplacian’s operator to form a system of algebraic approximation equations. This algebraic linear system will be computed via 4-Point Explicit Group Accelerated Over-Relaxation (4-EGAOR) iterative method for rapid computation. The performance of the proposed algorithm will then be compared and analyzed against the existing algorithms in terms of number of iterations and execution time. The result shows that the proposed algorithm performed better than the existing methods.
Fast and reliable obstacle detection and segmentation for cross-country navigation
NASA Technical Reports Server (NTRS)
Talukder, A.; Manduchi, R.; Rankin, A.; Matthies, L.
2002-01-01
Obstacle detection is one of the main components of the control system of autonomous vehicles. In the case of indoor/urban navigation, obstacles are typically defined as surface points that are higher than the ground plane. This characterization, however, cannot be used in cross-country and unstructured environments, where the notion of ground plane is often not meaningful.
a Review of Recent Research in Indoor Modelling & Mapping
NASA Astrophysics Data System (ADS)
Gunduz, M.; Isikdag, U.; Basaraner, M.
2016-06-01
Indoor modeling and mapping has been an active area of research in last 20 years in order to tackle the problems related to positioning and tracking of people and objects indoors, and provides many opportunities for several domains ranging from emergency response to logistics in micro urban spaces. The outputs of recent research in the field have been presented in several scientific publications and events primarily related to spatial information science and technology. This paper summarizes the outputs of last 10 years of research on indoor modeling and mapping within a proper classification which covers 7 areas, i.e. Information Acquisition by Sensors, Model Definition, Model Integration, Indoor Positioning and LBS, Routing & Navigation Methods, Augmented and Virtual Reality Applications, and Ethical Issues. Finally, the paper outlines the current and future research directions and concluding remarks.
Indoor Navigation Design Integrated with Smart Phones and Rfid Devices
NASA Astrophysics Data System (ADS)
Ortakci, Y.; Demiral, E.; Atila, U.; Karas, I. R.
2015-10-01
High rise, complex and huge buildings in the cities are almost like a small city with their tens of floors, hundreds of corridors and rooms and passages. Due to size and complexity of these buildings, people need guidance to find their way to the destination in these buildings. In this study, a mobile application is developed to visualize pedestrian's indoor position as 3D in their smartphone and RFID Technology is used to detect the position of pedestrian. While the pedestrian is walking on his/her way on the route, smartphone will guide the pedestrian by displaying the photos of indoor environment on the route. Along the tour, an RFID (Radio-Frequency Identification) device is integrated to the system. The pedestrian will carry the RFID device during his/her tour in the building. The RFID device will send the position data to the server directly in every two seconds periodically. On the other side, the pedestrian will just select the destination point in the mobile application on smartphone and sent the destination point to the server. The shortest path from the pedestrian position to the destination point is found out by the script on the server. This script also sends the environment photo of the first node on the acquired shortest path to the client as an indoor navigation module.
Maravall, Darío; de Lope, Javier; Fuentes, Juan P
2017-01-01
We introduce a hybrid algorithm for the self-semantic location and autonomous navigation of robots using entropy-based vision and visual topological maps. In visual topological maps the visual landmarks are considered as leave points for guiding the robot to reach a target point (robot homing) in indoor environments. These visual landmarks are defined from images of relevant objects or characteristic scenes in the environment. The entropy of an image is directly related to the presence of a unique object or the presence of several different objects inside it: the lower the entropy the higher the probability of containing a single object inside it and, conversely, the higher the entropy the higher the probability of containing several objects inside it. Consequently, we propose the use of the entropy of images captured by the robot not only for the landmark searching and detection but also for obstacle avoidance. If the detected object corresponds to a landmark, the robot uses the suggestions stored in the visual topological map to reach the next landmark or to finish the mission. Otherwise, the robot considers the object as an obstacle and starts a collision avoidance maneuver. In order to validate the proposal we have defined an experimental framework in which the visual bug algorithm is used by an Unmanned Aerial Vehicle (UAV) in typical indoor navigation tasks.
Maravall, Darío; de Lope, Javier; Fuentes, Juan P.
2017-01-01
We introduce a hybrid algorithm for the self-semantic location and autonomous navigation of robots using entropy-based vision and visual topological maps. In visual topological maps the visual landmarks are considered as leave points for guiding the robot to reach a target point (robot homing) in indoor environments. These visual landmarks are defined from images of relevant objects or characteristic scenes in the environment. The entropy of an image is directly related to the presence of a unique object or the presence of several different objects inside it: the lower the entropy the higher the probability of containing a single object inside it and, conversely, the higher the entropy the higher the probability of containing several objects inside it. Consequently, we propose the use of the entropy of images captured by the robot not only for the landmark searching and detection but also for obstacle avoidance. If the detected object corresponds to a landmark, the robot uses the suggestions stored in the visual topological map to reach the next landmark or to finish the mission. Otherwise, the robot considers the object as an obstacle and starts a collision avoidance maneuver. In order to validate the proposal we have defined an experimental framework in which the visual bug algorithm is used by an Unmanned Aerial Vehicle (UAV) in typical indoor navigation tasks. PMID:28900394
a Fast and Flexible Method for Meta-Map Building for Icp Based Slam
NASA Astrophysics Data System (ADS)
Kurian, A.; Morin, K. W.
2016-06-01
Recent developments in LiDAR sensors make mobile mapping fast and cost effective. These sensors generate a large amount of data which in turn improves the coverage and details of the map. Due to the limited range of the sensor, one has to collect a series of scans to build the entire map of the environment. If we have good GNSS coverage, building a map is a well addressed problem. But in an indoor environment, we have limited GNSS reception and an inertial solution, if available, can quickly diverge. In such situations, simultaneous localization and mapping (SLAM) is used to generate a navigation solution and map concurrently. SLAM using point clouds possesses a number of computational challenges even with modern hardware due to the shear amount of data. In this paper, we propose two strategies for minimizing the cost of computation and storage when a 3D point cloud is used for navigation and real-time map building. We have used the 3D point cloud generated by Leica Geosystems's Pegasus Backpack which is equipped with Velodyne VLP-16 LiDARs scanners. To improve the speed of the conventional iterative closest point (ICP) algorithm, we propose a point cloud sub-sampling strategy which does not throw away any key features and yet significantly reduces the number of points that needs to be processed and stored. In order to speed up the correspondence finding step, a dual kd-tree and circular buffer architecture is proposed. We have shown that the proposed method can run in real time and has excellent navigation accuracy characteristics.
Adaptations and Analysis of the AFIT Noise Radar Network for Indoor Navigation
2013-03-01
capable of producing bistatic/multistatic radar images. NTR is unique because it utilizes amplified random thermal noise as its transmission waveform...structure and operation of NTR is described. A minutia of the EM theory describing the various phenomenon found when operating RF devices in indoor...construction of NTR is simple in comparison to other CW radars. The system begins with a commercial thermal noise source, which produces a uniform
Audible vision for the blind and visually impaired in indoor open spaces.
Yu, Xunyi; Ganz, Aura
2012-01-01
In this paper we introduce Audible Vision, a system that can help blind and visually impaired users navigate in large indoor open spaces. The system uses computer vision to estimate the location and orientation of the user, and enables the user to perceive his/her relative position to a landmark through 3D audio. Testing shows that Audible Vision can work reliably in real-life ever-changing environment crowded with people.
Drift Reduction in Pedestrian Navigation System by Exploiting Motion Constraints and Magnetic Field.
Ilyas, Muhammad; Cho, Kuk; Baeg, Seung-Ho; Park, Sangdeok
2016-09-09
Pedestrian navigation systems (PNS) using foot-mounted MEMS inertial sensors use zero-velocity updates (ZUPTs) to reduce drift in navigation solutions and estimate inertial sensor errors. However, it is well known that ZUPTs cannot reduce all errors, especially as heading error is not observable. Hence, the position estimates tend to drift and even cyclic ZUPTs are applied in updated steps of the Extended Kalman Filter (EKF). This urges the use of other motion constraints for pedestrian gait and any other valuable heading reduction information that is available. In this paper, we exploit two more motion constraints scenarios of pedestrian gait: (1) walking along straight paths; (2) standing still for a long time. It is observed that these motion constraints (called "virtual sensor"), though considerably reducing drift in PNS, still need an absolute heading reference. One common absolute heading estimation sensor is the magnetometer, which senses the Earth's magnetic field and, hence, the true heading angle can be calculated. However, magnetometers are susceptible to magnetic distortions, especially in indoor environments. In this work, an algorithm, called magnetic anomaly detection (MAD) and compensation is designed by incorporating only healthy magnetometer data in the EKF updating step, to reduce drift in zero-velocity updated INS. Experiments are conducted in GPS-denied and magnetically distorted environments to validate the proposed algorithms.
Fuzzy Logic Based Control for Autonomous Mobile Robot Navigation
Masmoudi, Mohamed Slim; Masmoudi, Mohamed
2016-01-01
This paper describes the design and the implementation of a trajectory tracking controller using fuzzy logic for mobile robot to navigate in indoor environments. Most of the previous works used two independent controllers for navigation and avoiding obstacles. The main contribution of the paper can be summarized in the fact that we use only one fuzzy controller for navigation and obstacle avoidance. The used mobile robot is equipped with DC motor, nine infrared range (IR) sensors to measure the distance to obstacles, and two optical encoders to provide the actual position and speeds. To evaluate the performances of the intelligent navigation algorithms, different trajectories are used and simulated using MATLAB software and SIMIAM navigation platform. Simulation results show the performances of the intelligent navigation algorithms in terms of simulation times and travelled path. PMID:27688748
Study on Data Clustering and Intelligent Decision Algorithm of Indoor Localization
NASA Astrophysics Data System (ADS)
Liu, Zexi
2018-01-01
Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.
The Smartphone-Based Offline Indoor Location Competition at IPIN 2016: Analysis and Future Work.
Torres-Sospedra, Joaquín; Jiménez, Antonio R; Knauth, Stefan; Moreira, Adriano; Beer, Yair; Fetzer, Toni; Ta, Viet-Cuong; Montoliu, Raul; Seco, Fernando; Mendoza-Silva, Germán M; Belmonte, Oscar; Koukofikis, Athanasios; Nicolau, Maria João; Costa, António; Meneses, Filipe; Ebner, Frank; Deinzer, Frank; Vaufreydaz, Dominique; Dao, Trung-Kien; Castelli, Eric
2017-03-10
This paper presents the analysis and discussion of the off-site localization competition track, which took place during the Seventh International Conference on Indoor Positioning and Indoor Navigation (IPIN 2016). Five international teams proposed different strategies for smartphone-based indoor positioning using the same reference data. The competitors were provided with several smartphone-collected signal datasets, some of which were used for training (known trajectories), and others for evaluating (unknown trajectories). The competition permits a coherent evaluation method of the competitors' estimations, where inside information to fine-tune their systems is not offered, and thus provides, in our opinion, a good starting point to introduce a fair comparison between the smartphone-based systems found in the literature. The methodology, experience, feedback from competitors and future working lines are described.
Autonomous Wheeled Robot Platform Testbed for Navigation and Mapping Using Low-Cost Sensors
NASA Astrophysics Data System (ADS)
Calero, D.; Fernandez, E.; Parés, M. E.
2017-11-01
This paper presents the concept of an architecture for a wheeled robot system that helps researchers in the field of geomatics to speed up their daily research on kinematic geodesy, indoor navigation and indoor positioning fields. The presented ideas corresponds to an extensible and modular hardware and software system aimed at the development of new low-cost mapping algorithms as well as at the evaluation of the performance of sensors. The concept, already implemented in the CTTC's system ARAS (Autonomous Rover for Automatic Surveying) is generic and extensible. This means that it is possible to incorporate new navigation algorithms or sensors at no maintenance cost. Only the effort related to the development tasks required to either create such algorithms needs to be taken into account. As a consequence, change poses a much small problem for research activities in this specific area. This system includes several standalone sensors that may be combined in different ways to accomplish several goals; that is, this system may be used to perform a variety of tasks, as, for instance evaluates positioning algorithms performance or mapping algorithms performance.
Autonomous detection of indoor and outdoor signs
NASA Astrophysics Data System (ADS)
Holden, Steven; Snorrason, Magnus; Goodsell, Thomas; Stevens, Mark R.
2005-05-01
Most goal-oriented mobile robot tasks involve navigation to one or more known locations. This is generally done using GPS coordinates and landmarks outdoors, or wall-following and fiducial marks indoors. Such approaches ignore the rich source of navigation information that is already in place for human navigation in all man-made environments: signs. A mobile robot capable of detecting and reading arbitrary signs could be tasked using directions that are intuitive to hu-mans, and it could report its location relative to intuitive landmarks (a street corner, a person's office, etc.). Such ability would not require active marking of the environment and would be functional in the absence of GPS. In this paper we present an updated version of a system we call Sign Understanding in Support of Autonomous Navigation (SUSAN). This system relies on cues common to most signs, the presence of text, vivid color, and compact shape. By not relying on templates, SUSAN can detect a wide variety of signs: traffic signs, street signs, store-name signs, building directories, room signs, etc. In this paper we focus on the text detection capability. We present results summarizing probability of detection and false alarm rate across many scenes containing signs of very different designs and in a variety of lighting conditions.
A Modular Localization System as a Positioning Service for Road Transport
Brida, Peter; Machaj, Juraj; Benikovsky, Jozef
2014-01-01
In recent times smart devices have attracted a large number of users. Since many of these devices allow position estimation using Global Navigation Satellite Systems (GNSS) signals, a large number of location-based applications and services have emerged, especially in transport systems. However GNSS signals are affected by the environment and are not always present, especially in dense urban environment or indoors. In this work firstly a Modular Localization Algorithm is proposed to allow seamless switching between different positioning modules. This helps us develop a positioning system that is able to provide position estimates in both indoor and outdoor environments without any user interaction. Since the proposed system can run as a service on any smart device, it could allow users to navigate not only in outdoor environments, but also indoors, e.g., underground garages, tunnels etc. Secondly we present the proposal of a 2-phase map reduction algorithm which allows one to significantly reduce the complexity of position estimation processes in case that positioning is performed using a fingerprinting framework. The proposed 2-phase map reduction algorithm can also improve the accuracy of the position estimates by filtering out reference points that are far from the mobile device. Both algorithms were implemented into a positioning system and tested in real world conditions in both indoor and outdoor environments. PMID:25353979
Jan, Shau-Shiun; Hsu, Li-Ta; Tsai, Wen-Ming
2010-01-01
In order to provide the seamless navigation and positioning services for indoor environments, an indoor location based service (LBS) test bed is developed to integrate the indoor positioning system and the indoor three-dimensional (3D) geographic information system (GIS). A wireless sensor network (WSN) is used in the developed indoor positioning system. Considering the power consumption, in this paper the ZigBee radio is used as the wireless protocol, and the received signal strength (RSS) fingerprinting positioning method is applied as the primary indoor positioning algorithm. The matching processes of the user location include the nearest neighbor (NN) algorithm, the K-weighted nearest neighbors (KWNN) algorithm, and the probabilistic approach. To enhance the positioning accuracy for the dynamic user, the particle filter is used to improve the positioning performance. As part of this research, a 3D indoor GIS is developed to be used with the indoor positioning system. This involved using the computer-aided design (CAD) software and the virtual reality markup language (VRML) to implement a prototype indoor LBS test bed. Thus, a rapid and practical procedure for constructing a 3D indoor GIS is proposed, and this GIS is easy to update and maintenance for users. The building of the Department of Aeronautics and Astronautics at National Cheng Kung University in Taiwan is used as an example to assess the performance of various algorithms for the indoor positioning system.
Jan, Shau-Shiun; Hsu, Li-Ta; Tsai, Wen-Ming
2010-01-01
In order to provide the seamless navigation and positioning services for indoor environments, an indoor location based service (LBS) test bed is developed to integrate the indoor positioning system and the indoor three-dimensional (3D) geographic information system (GIS). A wireless sensor network (WSN) is used in the developed indoor positioning system. Considering the power consumption, in this paper the ZigBee radio is used as the wireless protocol, and the received signal strength (RSS) fingerprinting positioning method is applied as the primary indoor positioning algorithm. The matching processes of the user location include the nearest neighbor (NN) algorithm, the K-weighted nearest neighbors (KWNN) algorithm, and the probabilistic approach. To enhance the positioning accuracy for the dynamic user, the particle filter is used to improve the positioning performance. As part of this research, a 3D indoor GIS is developed to be used with the indoor positioning system. This involved using the computer-aided design (CAD) software and the virtual reality markup language (VRML) to implement a prototype indoor LBS test bed. Thus, a rapid and practical procedure for constructing a 3D indoor GIS is proposed, and this GIS is easy to update and maintenance for users. The building of the Department of Aeronautics and Astronautics at National Cheng Kung University in Taiwan is used as an example to assess the performance of various algorithms for the indoor positioning system. PMID:22319282
Pushbroom Stereo for High-Speed Navigation in Cluttered Environments
2014-09-01
inertial measurement sensors such as Achtelik et al .’s implemention of PTAM (parallel tracking and mapping) [15] with a barometric altimeter, stable flights...in indoor and outdoor environments are possible [1]. With a full vison- aided inertial navigation system (VINS), Li et al . have shown remarkable...avoidance on small UAVs. Stereo systems suffer from a similar speed issue, with most modern systems running at or below 30 Hz [8], [27]. Honegger et
The Smartphone-Based Offline Indoor Location Competition at IPIN 2016: Analysis and Future Work
Torres-Sospedra, Joaquín; Jiménez, Antonio R.; Knauth, Stefan; Moreira, Adriano; Beer, Yair; Fetzer, Toni; Ta, Viet-Cuong; Montoliu, Raul; Seco, Fernando; Mendoza-Silva, Germán M.; Belmonte, Oscar; Koukofikis, Athanasios; Nicolau, Maria João; Costa, António; Meneses, Filipe; Ebner, Frank; Deinzer, Frank; Vaufreydaz, Dominique; Dao, Trung-Kien; Castelli, Eric
2017-01-01
This paper presents the analysis and discussion of the off-site localization competition track, which took place during the Seventh International Conference on Indoor Positioning and Indoor Navigation (IPIN 2016). Five international teams proposed different strategies for smartphone-based indoor positioning using the same reference data. The competitors were provided with several smartphone-collected signal datasets, some of which were used for training (known trajectories), and others for evaluating (unknown trajectories). The competition permits a coherent evaluation method of the competitors’ estimations, where inside information to fine-tune their systems is not offered, and thus provides, in our opinion, a good starting point to introduce a fair comparison between the smartphone-based systems found in the literature. The methodology, experience, feedback from competitors and future working lines are described. PMID:28287447
Yuan, Xuebing; Yu, Shuai; Zhang, Shengzhi; Wang, Guoping; Liu, Sheng
2015-01-01
Inertial navigation based on micro-electromechanical system (MEMS) inertial measurement units (IMUs) has attracted numerous researchers due to its high reliability and independence. The heading estimation, as one of the most important parts of inertial navigation, has been a research focus in this field. Heading estimation using magnetometers is perturbed by magnetic disturbances, such as indoor concrete structures and electronic equipment. The MEMS gyroscope is also used for heading estimation. However, the accuracy of gyroscope is unreliable with time. In this paper, a wearable multi-sensor system has been designed to obtain the high-accuracy indoor heading estimation, according to a quaternion-based unscented Kalman filter (UKF) algorithm. The proposed multi-sensor system including one three-axis accelerometer, three single-axis gyroscopes, one three-axis magnetometer and one microprocessor minimizes the size and cost. The wearable multi-sensor system was fixed on waist of pedestrian and the quadrotor unmanned aerial vehicle (UAV) for heading estimation experiments in our college building. The results show that the mean heading estimation errors are less 10° and 5° to multi-sensor system fixed on waist of pedestrian and the quadrotor UAV, respectively, compared to the reference path. PMID:25961384
Multi Sensor Fusion Framework for Indoor-Outdoor Localization of Limited Resource Mobile Robots
Marín, Leonardo; Vallés, Marina; Soriano, Ángel; Valera, Ángel; Albertos, Pedro
2013-01-01
This paper presents a sensor fusion framework that improves the localization of mobile robots with limited computational resources. It employs an event based Kalman Filter to combine the measurements of a global sensor and an inertial measurement unit (IMU) on an event based schedule, using fewer resources (execution time and bandwidth) but with similar performance when compared to the traditional methods. The event is defined to reflect the necessity of the global information, when the estimation error covariance exceeds a predefined limit. The proposed experimental platforms are based on the LEGO Mindstorm NXT, and consist of a differential wheel mobile robot navigating indoors with a zenithal camera as global sensor, and an Ackermann steering mobile robot navigating outdoors with a SBG Systems GPS accessed through an IGEP board that also serves as datalogger. The IMU in both robots is built using the NXT motor encoders along with one gyroscope, one compass and two accelerometers from Hitecnic, placed according to a particle based dynamic model of the robots. The tests performed reflect the correct performance and low execution time of the proposed framework. The robustness and stability is observed during a long walk test in both indoors and outdoors environments. PMID:24152933
Multi sensor fusion framework for indoor-outdoor localization of limited resource mobile robots.
Marín, Leonardo; Vallés, Marina; Soriano, Ángel; Valera, Ángel; Albertos, Pedro
2013-10-21
This paper presents a sensor fusion framework that improves the localization of mobile robots with limited computational resources. It employs an event based Kalman Filter to combine the measurements of a global sensor and an inertial measurement unit (IMU) on an event based schedule, using fewer resources (execution time and bandwidth) but with similar performance when compared to the traditional methods. The event is defined to reflect the necessity of the global information, when the estimation error covariance exceeds a predefined limit. The proposed experimental platforms are based on the LEGO Mindstorm NXT, and consist of a differential wheel mobile robot navigating indoors with a zenithal camera as global sensor, and an Ackermann steering mobile robot navigating outdoors with a SBG Systems GPS accessed through an IGEP board that also serves as datalogger. The IMU in both robots is built using the NXT motor encoders along with one gyroscope, one compass and two accelerometers from Hitecnic, placed according to a particle based dynamic model of the robots. The tests performed reflect the correct performance and low execution time of the proposed framework. The robustness and stability is observed during a long walk test in both indoors and outdoors environments.
DEMONSTRATION OF AUTONOMOUS AIR MONITORING THROUGH ROBOTICS
This project included modifying an existing teleoperated robot to include autonomous navigation, large object avoidance, and air monitoring and demonstrating that prototype robot system in indoor and outdoor environments. An existing teleoperated "Surveyor" robot developed by ARD...
Detecting Signage and Doors for Blind Navigation and Wayfinding
Wang, Shuihua; Yang, Xiaodong; Tian, Yingli
2013-01-01
Signage plays a very important role to find destinations in applications of navigation and wayfinding. In this paper, we propose a novel framework to detect doors and signage to help blind people accessing unfamiliar indoor environments. In order to eliminate the interference information and improve the accuracy of signage detection, we first extract the attended areas by using a saliency map. Then the signage is detected in the attended areas by using a bipartite graph matching. The proposed method can handle multiple signage detection. Furthermore, in order to provide more information for blind users to access the area associated with the detected signage, we develop a robust method to detect doors based on a geometric door frame model which is independent to door appearances. Experimental results on our collected datasets of indoor signage and doors demonstrate the effectiveness and efficiency of our proposed method. PMID:23914345
Detecting Signage and Doors for Blind Navigation and Wayfinding.
Wang, Shuihua; Yang, Xiaodong; Tian, Yingli
2013-07-01
Signage plays a very important role to find destinations in applications of navigation and wayfinding. In this paper, we propose a novel framework to detect doors and signage to help blind people accessing unfamiliar indoor environments. In order to eliminate the interference information and improve the accuracy of signage detection, we first extract the attended areas by using a saliency map. Then the signage is detected in the attended areas by using a bipartite graph matching. The proposed method can handle multiple signage detection. Furthermore, in order to provide more information for blind users to access the area associated with the detected signage, we develop a robust method to detect doors based on a geometric door frame model which is independent to door appearances. Experimental results on our collected datasets of indoor signage and doors demonstrate the effectiveness and efficiency of our proposed method.
NASA Astrophysics Data System (ADS)
Nakagawa, M.; Akano, K.; Kobayashi, T.; Sekiguchi, Y.
2017-09-01
Image-based virtual reality (VR) is a virtual space generated with panoramic images projected onto a primitive model. In imagebased VR, realistic VR scenes can be generated with lower rendering cost, and network data can be described as relationships among VR scenes. The camera network data are generated manually or by an automated procedure using camera position and rotation data. When panoramic images are acquired in indoor environments, network data should be generated without Global Navigation Satellite Systems (GNSS) positioning data. Thus, we focused on image-based VR generation using a panoramic camera in indoor environments. We propose a methodology to automate network data generation using panoramic images for an image-based VR space. We verified and evaluated our methodology through five experiments in indoor environments, including a corridor, elevator hall, room, and stairs. We confirmed that our methodology can automatically reconstruct network data using panoramic images for image-based VR in indoor environments without GNSS position data.
Using Openstreetmap Data to Generate Building Models with Their Inner Structures for 3d Maps
NASA Astrophysics Data System (ADS)
Wang, Z.; Zipf, A.
2017-09-01
With the development of Web 2.0, more and more data related to indoor environments has been collected within the volunteered geographic information (VGI) framework, which creates a need for construction of indoor environments from VGI. In this study, we focus on generating 3D building models from OpenStreetMap (OSM) data, and provide an approach to support construction and visualization of indoor environments on 3D maps. In this paper, we present an algorithm which can extract building information from OSM data, and can construct building structures as well as inner building components (e.g., doors, rooms, and windows). A web application is built to support the processing and visualization of the building models on a 3D map. We test our approach with an indoor dataset collected from the field. The results show the feasibility of our approach and its potentials to provide support for a wide range of applications, such as indoor and outdoor navigation, urban planning, and incident management.
Indoorgml - a Standard for Indoor Spatial Modeling
NASA Astrophysics Data System (ADS)
Li, Ki-Joune
2016-06-01
With recent progress of mobile devices and indoor positioning technologies, it becomes possible to provide location-based services in indoor space as well as outdoor space. It is in a seamless way between indoor and outdoor spaces or in an independent way only for indoor space. However, we cannot simply apply spatial models developed for outdoor space to indoor space due to their differences. For example, coordinate reference systems are employed to indicate a specific position in outdoor space, while the location in indoor space is rather specified by cell number such as room number. Unlike outdoor space, the distance between two points in indoor space is not determined by the length of the straight line but the constraints given by indoor components such as walls, stairs, and doors. For this reason, we need to establish a new framework for indoor space from fundamental theoretical basis, indoor spatial data models, and information systems to store, manage, and analyse indoor spatial data. In order to provide this framework, an international standard, called IndoorGML has been developed and published by OGC (Open Geospatial Consortium). This standard is based on a cellular notion of space, which considers an indoor space as a set of non-overlapping cells. It consists of two types of modules; core module and extension module. While core module consists of four basic conceptual and implementation modeling components (geometric model for cell, topology between cells, semantic model of cell, and multi-layered space model), extension modules may be defined on the top of the core module to support an application area. As the first version of the standard, we provide an extension for indoor navigation.
An RFID Indoor Positioning Algorithm Based on Bayesian Probability and K-Nearest Neighbor.
Xu, He; Ding, Ye; Li, Peng; Wang, Ruchuan; Li, Yizhu
2017-08-05
The Global Positioning System (GPS) is widely used in outdoor environmental positioning. However, GPS cannot support indoor positioning because there is no signal for positioning in an indoor environment. Nowadays, there are many situations which require indoor positioning, such as searching for a book in a library, looking for luggage in an airport, emergence navigation for fire alarms, robot location, etc. Many technologies, such as ultrasonic, sensors, Bluetooth, WiFi, magnetic field, Radio Frequency Identification (RFID), etc., are used to perform indoor positioning. Compared with other technologies, RFID used in indoor positioning is more cost and energy efficient. The Traditional RFID indoor positioning algorithm LANDMARC utilizes a Received Signal Strength (RSS) indicator to track objects. However, the RSS value is easily affected by environmental noise and other interference. In this paper, our purpose is to reduce the location fluctuation and error caused by multipath and environmental interference in LANDMARC. We propose a novel indoor positioning algorithm based on Bayesian probability and K -Nearest Neighbor (BKNN). The experimental results show that the Gaussian filter can filter some abnormal RSS values. The proposed BKNN algorithm has the smallest location error compared with the Gaussian-based algorithm, LANDMARC and an improved KNN algorithm. The average error in location estimation is about 15 cm using our method.
Drift Reduction in Pedestrian Navigation System by Exploiting Motion Constraints and Magnetic Field
Ilyas, Muhammad; Cho, Kuk; Baeg, Seung-Ho; Park, Sangdeok
2016-01-01
Pedestrian navigation systems (PNS) using foot-mounted MEMS inertial sensors use zero-velocity updates (ZUPTs) to reduce drift in navigation solutions and estimate inertial sensor errors. However, it is well known that ZUPTs cannot reduce all errors, especially as heading error is not observable. Hence, the position estimates tend to drift and even cyclic ZUPTs are applied in updated steps of the Extended Kalman Filter (EKF). This urges the use of other motion constraints for pedestrian gait and any other valuable heading reduction information that is available. In this paper, we exploit two more motion constraints scenarios of pedestrian gait: (1) walking along straight paths; (2) standing still for a long time. It is observed that these motion constraints (called “virtual sensor”), though considerably reducing drift in PNS, still need an absolute heading reference. One common absolute heading estimation sensor is the magnetometer, which senses the Earth’s magnetic field and, hence, the true heading angle can be calculated. However, magnetometers are susceptible to magnetic distortions, especially in indoor environments. In this work, an algorithm, called magnetic anomaly detection (MAD) and compensation is designed by incorporating only healthy magnetometer data in the EKF updating step, to reduce drift in zero-velocity updated INS. Experiments are conducted in GPS-denied and magnetically distorted environments to validate the proposed algorithms. PMID:27618056
Localization and Mapping Using a Non-Central Catadioptric Camera System
NASA Astrophysics Data System (ADS)
Khurana, M.; Armenakis, C.
2018-05-01
This work details the development of an indoor navigation and mapping system using a non-central catadioptric omnidirectional camera and its implementation for mobile applications. Omnidirectional catadioptric cameras find their use in navigation and mapping of robotic platforms, owing to their wide field of view. Having a wider field of view, or rather a potential 360° field of view, allows the system to "see and move" more freely in the navigation space. A catadioptric camera system is a low cost system which consists of a mirror and a camera. Any perspective camera can be used. A platform was constructed in order to combine the mirror and a camera to build a catadioptric system. A calibration method was developed in order to obtain the relative position and orientation between the two components so that they can be considered as one monolithic system. The mathematical model for localizing the system was determined using conditions based on the reflective properties of the mirror. The obtained platform positions were then used to map the environment using epipolar geometry. Experiments were performed to test the mathematical models and the achieved location and mapping accuracies of the system. An iterative process of positioning and mapping was applied to determine object coordinates of an indoor environment while navigating the mobile platform. Camera localization and 3D coordinates of object points obtained decimetre level accuracies.
Multimodal sensing strategies for detecting transparent barriers indoors from a mobile platform
NASA Astrophysics Data System (ADS)
Acevedo, Isaiah; Kleine, R. Kaleb; Kraus, Dustan; Mascareñas, David
2015-04-01
There is currently an interest in developing mobile sensing platforms that fly indoors. The primary goal for these platforms is to be able to successfully navigate a building under various lighting and environmental conditions. There are numerous research challenges associated with this goal, one of which is the platform's ability to detect and identify the presence of transparent barriers. Transparent barriers could include windows, glass partitions, or skylights. For example, in order to successfully navigate inside of a structure, these platforms will need to sense if a space contains a transparent barrier and whether or not this space can be traversed. This project's focus has been developing a multimodal sensing system that can successfully identify such transparent barriers under various lighting conditions while aboard a mobile platform. Along with detecting transparent barriers, this sensing platform is capable of distinguishing between reflective, opaque, and transparent barriers. It will be critical for this system to be able to identify transparent barriers in real-time in order for the navigation system to maneuver accordingly. The properties associated with the interaction between various frequencies of light and transparent materials were one of the techniques leveraged to solve this problem.
Dynamic multisensor fusion for mobile robot navigation in an indoor environment
NASA Astrophysics Data System (ADS)
Jin, Taeseok; Lee, Jang-Myung; Luk, Bing L.; Tso, Shiu K.
2001-10-01
In this study, as the preliminary step for developing a multi-purpose Autonomous robust carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as sonar, CCD camera dn IR sensor for map-building mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. Smart sensory systems are crucial for successful autonomous systems. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, since there exist several recent thorough books and review paper on this paper. Instead we will focus on the main results with relevance to the intelligent service robot project at the Centre of Intelligent Design, Automation & Manufacturing (CIDAM). We will conclude by discussing some possible future extensions of the project. It is first dealt with the general principle of the navigation and guidance architecture, then the detailed functions recognizing environments updated, obstacle detection and motion assessment, with the first results form the simulations run.
Analysis Thermal Comfort Condition in Complex Residential Building, Case Study: Chiangmai, Thailand
NASA Astrophysics Data System (ADS)
Juangjandee, Warangkana
2017-10-01
Due to the increasing need for complex residential buildings, it appears that people migrate into the high-density urban areas because the infrastructural facilities can be easily found in the modern metropolitan areas. Such rapid growth of urbanization creates congested residential buildings obstructing solar radiation and wind flow, whereas most urban residents spend 80-90% of their time indoor. Furthermore, the buildings were mostly built with average materials and construction detail. This causes high humidity condition for tenants that could promote mould growth. This study aims to analyse thermal comfort condition in complex residential building, Thailand for finding the passive solution to improve indoor air quality and respond to local conditions. The research methodology will be in two folds: 1) surveying on case study 2) analysis for finding the passive solution of reducing humidity indoor air The result of the survey indicated that the building need to find passive solution for solving humidity problem, that can be divided into two ways which raising ventilation and indoor temperature including increasing wind-flow ventilation and adjusting thermal temperature, for example; improving building design and stack driven ventilation. For raising indoor temperature or increasing mean radiant temperature, daylight can be passive solution for complex residential design for reducing humidity and enhance illumination indoor space simultaneous.
GPS/Optical/Inertial Integration for 3D Navigation Using Multi-Copter Platforms
NASA Technical Reports Server (NTRS)
Dill, Evan T.; Young, Steven D.; Uijt De Haag, Maarten
2017-01-01
In concert with the continued advancement of a UAS traffic management system (UTM), the proposed uses of autonomous unmanned aerial systems (UAS) have become more prevalent in both the public and private sectors. To facilitate this anticipated growth, a reliable three-dimensional (3D) positioning, navigation, and mapping (PNM) capability will be required to enable operation of these platforms in challenging environments where global navigation satellite systems (GNSS) may not be available continuously. Especially, when the platform's mission requires maneuvering through different and difficult environments like outdoor opensky, outdoor under foliage, outdoor-urban and indoor, and may include transitions between these environments. There may not be a single method to solve the PNM problem for all environments. The research presented in this paper is a subset of a broader research effort, described in [1]. The research is focused on combining data from dissimilar sensor technologies to create an integrated navigation and mapping method that can enable reliable operation in both an outdoor and structured indoor environment. The integrated navigation and mapping design is utilizes a Global Positioning System (GPS) receiver, an Inertial Measurement Unit (IMU), a monocular digital camera, and three short to medium range laser scanners. This paper describes specifically the techniques necessary to effectively integrate the monocular camera data within the established mechanization. To evaluate the developed algorithms a hexacopter was built, equipped with the discussed sensors, and both hand-carried and flown through representative environments. This paper highlights the effect that the monocular camera has on the aforementioned sensor integration scheme's reliability, accuracy and availability.
PERCEPT: indoor navigation for the blind and visually impaired.
Ganz, Aura; Gandhi, Siddhesh Rajan; Schafer, James; Singh, Tushar; Puleo, Elaine; Mullett, Gary; Wilson, Carole
2011-01-01
In order to enhance the perception of indoor and unfamiliar environments for the blind and visually-impaired, we introduce the PERCEPT system that supports a number of unique features such as: a) Low deployment and maintenance cost; b) Scalability, i.e. we can deploy the system in very large buildings; c) An on-demand system that does not overwhelm the user, as it offers small amounts of information on demand; and d) Portability and ease-of-use, i.e., the custom handheld device carried by the user is compact and instructions are received audibly.
Mamdani Fuzzy System for Indoor Autonomous Mobile Robot
NASA Astrophysics Data System (ADS)
Khan, M. K. A. Ahamed; Rashid, Razif; Elamvazuthi, I.
2011-06-01
Several control algorithms for autonomous mobile robot navigation have been proposed in the literature. Recently, the employment of non-analytical methods of computing such as fuzzy logic, evolutionary computation, and neural networks has demonstrated the utility and potential of these paradigms for intelligent control of mobile robot navigation. In this paper, Mamdani fuzzy system for an autonomous mobile robot is developed. The paper begins with the discussion on the conventional controller and then followed by the description of fuzzy logic controller in detail.
Visual Navigation Constructing and Utilizing Simple Maps of an Indoor Environment
1989-03-01
places are con- nected to eachother , so that the robot may plan routes. On a more advanced level. navigation nmay require an understanding of the meaning...two vertical lines, suitably separated from eachother . through which it tries to lead the robot. CHAPTER 1. L’TRODUCTION 14 1.4 Context of the Project...the observer will have no trouble in determining where the wall is. A robot, with far less processing power than humans have. might be able determine
Liu, Wen; Fu, Xiao; Deng, Zhongliang
2016-12-02
Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS). Due to the absence of satellite signal in Global Navigation Satellite System (GNSS), various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP), which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC), is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1) and the XiDan Joy City (Floors 1 and 2, as Test-bed 2), and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means.
Liu, Wen; Fu, Xiao; Deng, Zhongliang
2016-01-01
Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS). Due to the absence of satellite signal in Global Navigation Satellite System (GNSS), various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP), which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC), is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1) and the XiDan Joy City (Floors 1 and 2, as Test-bed 2), and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means. PMID:27918454
A variety of common activities in the home, such as smoking and cooking, generate indoor particle concentrations. Mathematical indoor air quality models permit predictions of indoor pollutant concentrations in homes, provided that parameter values such as source strengths and ...
Indoor-Outdoor Detection Using a Smart Phone Sensor.
Wang, Weiping; Chang, Qiang; Li, Qun; Shi, Zesen; Chen, Wei
2016-09-22
In the era of mobile internet, Location Based Services (LBS) have developed dramatically. Seamless Indoor and Outdoor Navigation and Localization (SNAL) has attracted a lot of attention. No single positioning technology was capable of meeting the various positioning requirements in different environments. Selecting different positioning techniques for different environments is an alternative method. Detecting the users' current environment is crucial for this technique. In this paper, we proposed to detect the indoor/outdoor environment automatically without high energy consumption. The basic idea was simple: we applied a machine learning algorithm to classify the neighboring Global System for Mobile (GSM) communication cellular base station's signal strength in different environments, and identified the users' current context by signal pattern recognition. We tested the algorithm in four different environments. The results showed that the proposed algorithm was capable of identifying open outdoors, semi-outdoors, light indoors and deep indoors environments with 100% accuracy using the signal strength of four nearby GSM stations. The required hardware and signal are widely available in our daily lives, implying its high compatibility and availability.
Santoso, Fendy; Redmond, Stephen J
2015-10-01
This paper presents a comprehensive literature review of current progress in the application of state-of-the-art indoor positioning systems for telecare and telehealth monitoring. This review is the first in the literature that provides a comprehensive discussion on how existing wireless indoor positioning systems can benefit the development of home-based care systems. More specifically, this review provides an in-depth comparative study of how both system users and medical practitioners can get benefit from indoor positioning technologies; e.g. for real-time monitoring of patients suffering chronic cardiovascular conditions, general monitoring of activities of daily living (ADLs), fall detection systems for the elderly as well as indoor navigation systems for those suffering from visual impairments. Furthermore, it also details various aspects worth considering when choosing a certain technology for a specific healthcare application; e.g. the spatial precision demanded by the application, trade-offs between unobtrusiveness and complexity, and issues surrounding compliance and adherence with the use of wearable tags. Beyond the current state-of-the-art, this review also rigorously discusses several research opportunities and the challenges associated with each.
Study of the indoor decontamination using nanocoated woven polyester fabric
NASA Astrophysics Data System (ADS)
Memon, Hafeezullah; Kumari, Naveeta; Jatoi, Abdul Wahab; Khoso, Nazakat Ali
2017-11-01
This research primarily deals with the photocatalytic degradation of methanol in indoor air using nanocoated indoor textiles used for curtains as household textiles. The woven polyester was coated by titanium dioxide by sol gel method, using silicon-based binder. The characterization of the coating has been done using scanning electron microscopy (SEM) image analysis, energy dispersive analysis using X-ray (EDAX) and Fourier transform infrared spectroscopy (FTIR). The DIY instrument providing the similar environment as of indoor was designed to assess the performance of the degradation of formaldehyde under UV light. The photocatalytic degradation rate was measured using the absorption value of the solutions obtained in the result of liquid chromatography of test solution and reagent solution. Different amount of dosages (1-3 %) and different time period of coatings (half hour to 3 h) have been evaluated for optimization.
Challenges in Flying Quadrotor Unmanned Aerial Vehicle for 3d Indoor Reconstruction
NASA Astrophysics Data System (ADS)
Yan, J.; Grasso, N.; Zlatanova, S.; Braggaar, R. C.; Marx, D. B.
2017-09-01
Three-dimensional modelling plays a vital role in indoor 3D tracking, navigation, guidance and emergency evacuation. Reconstruction of indoor 3D models is still problematic, in part, because indoor spaces provide challenges less-documented than their outdoor counterparts. Challenges include obstacles curtailing image and point cloud capture, restricted accessibility and a wide array of indoor objects, each with unique semantics. Reconstruction of indoor environments can be achieved through a photogrammetric approach, e.g. by using image frames, aligned using recurring corresponding image points (CIP) to build coloured point clouds. Our experiments were conducted by flying a QUAV in three indoor environments and later reconstructing 3D models which were analysed under different conditions. Point clouds and meshes were created using Agisoft PhotoScan Professional. We concentrated on flight paths from two vantage points: 1) safety and security while flying indoors and 2) data collection needed for reconstruction of 3D models. We surmised that the main challenges in providing safe flight paths are related to the physical configuration of indoor environments, privacy issues, the presence of people and light conditions. We observed that the quality of recorded video used for 3D reconstruction has a high dependency on surface materials, wall textures and object types being reconstructed. Our results show that 3D indoor reconstruction predicated on video capture using a QUAV is indeed feasible, but close attention should be paid to flight paths and conditions ultimately influencing the quality of 3D models. Moreover, it should be decided in advance which objects need to be reconstructed, e.g. bare rooms or detailed furniture.
High-frequency imaging radar for robotic navigation and situational awareness
NASA Astrophysics Data System (ADS)
Thomas, David J.; Luo, Changan; Knox, Robert
2011-05-01
With increasingly available high frequency radar components, the practicality of imaging radar for mobile robotic applications is now practical. Navigation, ODOA, situational awareness and safety applications can be supported in small light weight packaging. Radar has the additional advantage of being able sense through aerosols, smoke and dust that can be difficult for many optical systems. The ability to directly measure the range rate of an object is also an advantage in radar applications. This paper will explore the applicability of high frequency imaging radar for mobile robotics and examine a W-band 360 degree imaging radar prototype. Indoor and outdoor performance data will be analyzed and evaluated for applicability to navigation and situational awareness.
Low Cost and Efficient 3d Indoor Mapping Using Multiple Consumer Rgb-D Cameras
NASA Astrophysics Data System (ADS)
Chen, C.; Yang, B. S.; Song, S.
2016-06-01
Driven by the miniaturization, lightweight of positioning and remote sensing sensors as well as the urgent needs for fusing indoor and outdoor maps for next generation navigation, 3D indoor mapping from mobile scanning is a hot research and application topic. The point clouds with auxiliary data such as colour, infrared images derived from 3D indoor mobile mapping suite can be used in a variety of novel applications, including indoor scene visualization, automated floorplan generation, gaming, reverse engineering, navigation, simulation and etc. State-of-the-art 3D indoor mapping systems equipped with multiple laser scanners product accurate point clouds of building interiors containing billions of points. However, these laser scanner based systems are mostly expensive and not portable. Low cost consumer RGB-D Cameras provides an alternative way to solve the core challenge of indoor mapping that is capturing detailed underlying geometry of the building interiors. Nevertheless, RGB-D Cameras have a very limited field of view resulting in low efficiency in the data collecting stage and incomplete dataset that missing major building structures (e.g. ceilings, walls). Endeavour to collect a complete scene without data blanks using single RGB-D Camera is not technic sound because of the large amount of human labour and position parameters need to be solved. To find an efficient and low cost way to solve the 3D indoor mapping, in this paper, we present an indoor mapping suite prototype that is built upon a novel calibration method which calibrates internal parameters and external parameters of multiple RGB-D Cameras. Three Kinect sensors are mounted on a rig with different view direction to form a large field of view. The calibration procedure is three folds: 1, the internal parameters of the colour and infrared camera inside each Kinect are calibrated using a chess board pattern, respectively; 2, the external parameters between the colour and infrared camera inside each Kinect are calibrated using a chess board pattern; 3, the external parameters between every Kinect are firstly calculated using a pre-set calibration field and further refined by an iterative closet point algorithm. Experiments are carried out to validate the proposed method upon RGB-D datasets collected by the indoor mapping suite prototype. The effectiveness and accuracy of the proposed method is evaluated by comparing the point clouds derived from the prototype with ground truth data collected by commercial terrestrial laser scanner at ultra-high density. The overall analysis of the results shows that the proposed method achieves seamless integration of multiple point clouds form different RGB-D cameras collected at 30 frame per second.
The development of a white cane which navigates the visually impaired.
Shiizu, Yuriko; Hirahara, Yoshiaki; Yanashima, Kenji; Magatani, Kazushige
2007-01-01
In this paper, we describe about a developed navigation system that supports the independent walking of the visually impaired in the indoor space. This system is composed of colored navigation lines, RFID tags and an intelligent white cane. In our system, some colored marking tapes are set on along the walking route. These lines are called navigation line. And also RFID tags are set on this line at each landmark point. The intelligent white cane can sense a color of navigation line and receive tag information. By vibration of white cane, the system informs the visually impaired that he/she is walking along the navigation line. At the landmark point, the system also notifies area information to him/her by pre-recorded voice. Ten normal subjects who were blind folded with an eye mask were tested with this system. All of them were able to walk along the navigation line. The performance of the area information system was good. Therefore, we have concluded that our system will be extremely valuable in supporting the activities of the visually impaired.
Inverse Source Data-Processing Strategies for Radio-Frequency Localization in Indoor Environments.
Gennarelli, Gianluca; Al Khatib, Obada; Soldovieri, Francesco
2017-10-27
Indoor positioning of mobile devices plays a key role in many aspects of our daily life. These include real-time people tracking and monitoring, activity recognition, emergency detection, navigation, and numerous location based services. Despite many wireless technologies and data-processing algorithms have been developed in recent years, indoor positioning is still a problem subject of intensive research. This paper deals with the active radio-frequency (RF) source localization in indoor scenarios. The localization task is carried out at the physical layer thanks to receiving sensor arrays which are deployed on the border of the surveillance region to record the signal emitted by the source. The localization problem is formulated as an imaging one by taking advantage of the inverse source approach. Different measurement configurations and data-processing/fusion strategies are examined to investigate their effectiveness in terms of localization accuracy under both line-of-sight (LOS) and non-line of sight (NLOS) conditions. Numerical results based on full-wave synthetic data are reported to support the analysis.
Inverse Source Data-Processing Strategies for Radio-Frequency Localization in Indoor Environments
Gennarelli, Gianluca; Al Khatib, Obada; Soldovieri, Francesco
2017-01-01
Indoor positioning of mobile devices plays a key role in many aspects of our daily life. These include real-time people tracking and monitoring, activity recognition, emergency detection, navigation, and numerous location based services. Despite many wireless technologies and data-processing algorithms have been developed in recent years, indoor positioning is still a problem subject of intensive research. This paper deals with the active radio-frequency (RF) source localization in indoor scenarios. The localization task is carried out at the physical layer thanks to receiving sensor arrays which are deployed on the border of the surveillance region to record the signal emitted by the source. The localization problem is formulated as an imaging one by taking advantage of the inverse source approach. Different measurement configurations and data-processing/fusion strategies are examined to investigate their effectiveness in terms of localization accuracy under both line-of-sight (LOS) and non-line of sight (NLOS) conditions. Numerical results based on full-wave synthetic data are reported to support the analysis. PMID:29077071
Space Subdivision in Indoor Mobile Laser Scanning Point Clouds Based on Scanline Analysis.
Zheng, Yi; Peter, Michael; Zhong, Ruofei; Oude Elberink, Sander; Zhou, Quan
2018-06-05
Indoor space subdivision is an important aspect of scene analysis that provides essential information for many applications, such as indoor navigation and evacuation route planning. Until now, most proposed scene understanding algorithms have been based on whole point clouds, which has led to complicated operations, high computational loads and low processing speed. This paper presents novel methods to efficiently extract the location of openings (e.g., doors and windows) and to subdivide space by analyzing scanlines. An opening detection method is demonstrated that analyses the local geometric regularity in scanlines to refine the extracted opening. Moreover, a space subdivision method based on the extracted openings and the scanning system trajectory is described. Finally, the opening detection and space subdivision results are saved as point cloud labels which will be used for further investigations. The method has been tested on a real dataset collected by ZEB-REVO. The experimental results validate the completeness and correctness of the proposed method for different indoor environment and scanning paths.
School Solutions. Special Report: IAQ and Energy.
ERIC Educational Resources Information Center
Birr, Dave
1999-01-01
Discusses how energy service companies (ESCO) can help schools upgrade their indoor air quality and make them environmentally sound. How ESCO's help in arranging funding for indoor environmental improvements through energy performance contracts is discussed. Tips on energy-efficiency measures for improving indoor environmental quality are…
An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database.
Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang
2016-01-28
In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m.
An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database
Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang
2016-01-01
In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m. PMID:26828496
A navigation system for the visually impaired using colored navigation lines and RFID tags.
Seto, First Tatsuya
2009-01-01
In this paper, we describe about a developed navigation system that supports the independent walking of the visually impaired in the indoor space. Our developed instrument consists of a navigation system and a map information system. These systems are installed on a white cane. Our navigation system can follow a colored navigation line that is set on the floor. In this system, a color sensor installed on the tip of a white cane senses the colored navigation line, and the system informs the visually impaired that he/she is walking along the navigation line by vibration. The color recognition system is controlled by a one-chip microprocessor and this system can discriminate 6 colored navigation lines. RFID tags and a receiver for these tags are used in the map information system. The RFID tags and the RFID tag receiver are also installed on a white cane. The receiver receives tag information and notifies map information to the user by mp3 formatted pre-recorded voice. Three normal subjects who were blindfolded with an eye mask were tested with this system. All of them were able to walk along the navigation line. The performance of the map information system was good. Therefore, our system will be extremely valuable in supporting the activities of the visually impaired.
Ott, Wayne R; Klepeis, Neil E; Switzer, Paul
2003-08-01
This paper derives the analytical solutions to multi-compartment indoor air quality models for predicting indoor air pollutant concentrations in the home and evaluates the solutions using experimental measurements in the rooms of a single-story residence. The model uses Laplace transform methods to solve the mass balance equations for two interconnected compartments, obtaining analytical solutions that can be applied without a computer. Environmental tobacco smoke (ETS) sources such as the cigarette typically emit pollutants for relatively short times (7-11 min) and are represented mathematically by a "rectangular" source emission time function, or approximated by a short-duration source called an "impulse" time function. Other time-varying indoor sources also can be represented by Laplace transforms. The two-compartment model is more complicated than the single-compartment model and has more parameters, including the cigarette or combustion source emission rate as a function of time, room volumes, compartmental air change rates, and interzonal air flow factors expressed as dimensionless ratios. This paper provides analytical solutions for the impulse, step (Heaviside), and rectangular source emission time functions. It evaluates the indoor model in an unoccupied two-bedroom home using cigars and cigarettes as sources with continuous measurements of carbon monoxide (CO), respirable suspended particles (RSP), and particulate polycyclic aromatic hydrocarbons (PPAH). Fine particle mass concentrations (RSP or PM3.5) are measured using real-time monitors. In our experiments, simultaneous measurements of concentrations at three heights in a bedroom confirm an important assumption of the model-spatial uniformity of mixing. The parameter values of the two-compartment model were obtained using a "grid search" optimization method, and the predicted solutions agreed well with the measured concentration time series in the rooms of the home. The door and window positions in each room had considerable effect on the pollutant concentrations observed in the home. Because of the small volumes and low air change rates of most homes, indoor pollutant concentrations from smoking activity in a home can be very high and can persist at measurable levels indoors for many hours.
Research into Kinect/Inertial Measurement Units Based on Indoor Robots.
Li, Huixia; Wen, Xi; Guo, Hang; Yu, Min
2018-03-12
As indoor mobile navigation suffers from low positioning accuracy and accumulation error, we carried out research into an integrated location system for a robot based on Kinect and an Inertial Measurement Unit (IMU). In this paper, the close-range stereo images are used to calculate the attitude information and the translation amount of the adjacent positions of the robot by means of the absolute orientation algorithm, for improving the calculation accuracy of the robot's movement. Relying on the Kinect visual measurement and the strap-down IMU devices, we also use Kalman filtering to obtain the errors of the position and attitude outputs, in order to seek the optimal estimation and correct the errors. Experimental results show that the proposed method is able to improve the positioning accuracy and stability of the indoor mobile robot.
A Bionic Camera-Based Polarization Navigation Sensor
Wang, Daobin; Liang, Huawei; Zhu, Hui; Zhang, Shuai
2014-01-01
Navigation and positioning technology is closely related to our routine life activities, from travel to aerospace. Recently it has been found that Cataglyphis (a kind of desert ant) is able to detect the polarization direction of skylight and navigate according to this information. This paper presents a real-time bionic camera-based polarization navigation sensor. This sensor has two work modes: one is a single-point measurement mode and the other is a multi-point measurement mode. An indoor calibration experiment of the sensor has been done under a beam of standard polarized light. The experiment results show that after noise reduction the accuracy of the sensor can reach up to 0.3256°. It is also compared with GPS and INS (Inertial Navigation System) in the single-point measurement mode through an outdoor experiment. Through time compensation and location compensation, the sensor can be a useful alternative to GPS and INS. In addition, the sensor also can measure the polarization distribution pattern when it works in multi-point measurement mode. PMID:25051029
Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning
NASA Astrophysics Data System (ADS)
Evennou, Frédéric; Marx, François
2006-12-01
This paper presents an aided dead-reckoning navigation structure and signal processing algorithms for self localization of an autonomous mobile device by fusing pedestrian dead reckoning and WiFi signal strength measurements. WiFi and inertial navigation systems (INS) are used for positioning and attitude determination in a wide range of applications. Over the last few years, a number of low-cost inertial sensors have become available. Although they exhibit large errors, WiFi measurements can be used to correct the drift weakening the navigation based on this technology. On the other hand, INS sensors can interact with the WiFi positioning system as they provide high-accuracy real-time navigation. A structure based on a Kalman filter and a particle filter is proposed. It fuses the heterogeneous information coming from those two independent technologies. Finally, the benefits of the proposed architecture are evaluated and compared with the pure WiFi and INS positioning systems.
INSIGHT: RFID and Bluetooth enabled automated space for the blind and visually impaired.
Ganz, Aura; Gandhi, Siddhesh Rajan; Wilson, Carole; Mullett, Gary
2010-01-01
In this paper we introduce INSIGHT, an indoor location tracking and navigation system to help the blind and visually impaired to easily navigate to their chosen destination in a public building. INSIGHT makes use of RFID and Bluetooth technology deployed within the building to locate and track the users. The PDA based user device interacts with INSIGHT server and provides the user navigation instructions in an audio form. The proposed system provides multi-resolution localization of the users, facilitating the provision of accurate navigation instructions when the user is in the vicinity of the RFID tags as well as accommodating a PANIC button which provides navigation instructions when the user is anywhere in the building. Moreover, the system will continuously monitor the zone in which the user walks. This will enable the system to identify if the user is located in the wrong zone of the building which may not lead to the desired destination.
Navigation system for a mobile robot with a visual sensor using a fish-eye lens
NASA Astrophysics Data System (ADS)
Kurata, Junichi; Grattan, Kenneth T. V.; Uchiyama, Hironobu
1998-02-01
Various position sensing and navigation systems have been proposed for the autonomous control of mobile robots. Some of these systems have been installed with an omnidirectional visual sensor system that proved very useful in obtaining information on the environment around the mobile robot for position reckoning. In this article, this type of navigation system is discussed. The sensor is composed of one TV camera with a fish-eye lens, using a reference target on a ceiling and hybrid image processing circuits. The position of the robot, with respect to the floor, is calculated by integrating the information obtained from a visual sensor and a gyroscope mounted in the mobile robot, and the use of a simple algorithm based on PTP control for guidance is discussed. An experimental trial showed that the proposed system was both valid and useful for the navigation of an indoor vehicle.
Plants for Sustainable Improvement of Indoor Air Quality.
Brilli, Federico; Fares, Silvano; Ghirardo, Andrea; de Visser, Pieter; Calatayud, Vicent; Muñoz, Amalia; Annesi-Maesano, Isabella; Sebastiani, Federico; Alivernini, Alessandro; Varriale, Vincenzo; Menghini, Flavio
2018-06-01
Indoor pollution poses a serious threat to human health. Plants represent a sustainable but underexploited solution to enhance indoor air quality. However, the current selection of plants suitable for indoors fails to consider the physiological processes and mechanisms involved in phytoremediation. Therefore, the capacity of plants to remove indoor air pollutants through stomatal uptake (absorption) and non-stomatal deposition (adsorption) remains largely unknown. Moreover, the effects of the indoor plant-associated microbiome still need to be fully analyzed. Here, we discuss how a combination of the enhanced phytoremediation capacity of plants together with cutting-edge air-cleaning and smart sensor technologies can improve indoor life while reducing energy consumption. Copyright © 2018 Elsevier Ltd. All rights reserved.
2010-01-01
open garage leading to the building interior. The UAV is positioned north of a potential ingress to the building. As the mission begins, the UAV...camera, the difficulty in detecting and navigating around obstacles using this non- stereo camera necessitated a precomputed map of all obstacles and
Investigation of practical and theoretical accuracy of wireless indoor-positioning system UBISENSE
NASA Astrophysics Data System (ADS)
Wozniak, Marek; Odziemczyk, Waldemar; Nagorski, Kamil
2013-04-01
The development of Real Time Locating Systems has become an important add-on to many existing location aware systems. While Global Navigation Satelite System has solved most of the outdoor problems, it fails to repeat this success indoors. Wireless indoor positioning systems have become very popular in recent years. One of them is UBISENSE system. This system requires to carry an identity tag that is detected by sensors, which typically use triangulation to determine location. This paper presents the results of the investigation of accuracy of tag position using precise geodetic measurements and geometric analysis. Experimental measurements were carried out on the field polygon using precise tacheometer TCRP 1201+ and complete equipment of Ubisense. Results of experimental measurements were analyzed and presented graphically using Surfer 8. The paper presents the results of the investigation the teoretical and practical positioning accuracy according to the various working conditions.
Sensors integration for smartphone navigation: performances and future challenges
NASA Astrophysics Data System (ADS)
Aicardi, I.; Dabove, P.; Lingua, A.; Piras, M.
2014-08-01
Nowadays the modern smartphones include several sensors which are usually adopted in geomatic application, as digital camera, GNSS (Global Navigation Satellite System) receivers, inertial platform, RFID and Wi-Fi systems. In this paper the authors would like to testing the performances of internal sensors (Inertial Measurement Unit, IMU) of three modern smartphones (Samsung GalaxyS4, Samsung GalaxyS5 and iPhone4) compared to external mass-market IMU platform in order to verify their accuracy levels, in terms of positioning. Moreover, the Image Based Navigation (IBN) approach is also investigated: this approach can be very useful in hard-urban environment or for indoor positioning, as alternative to GNSS positioning. IBN allows to obtain a sub-metrical accuracy, but a special database of georeferenced images (Image DataBase, IDB) is needed, moreover it is necessary to use dedicated algorithm to resizing the images which are collected by smartphone, in order to share it with the server where is stored the IDB. Moreover, it is necessary to characterize smartphone camera lens in terms of focal length and lens distortions. The authors have developed an innovative method with respect to those available today, which has been tested in a covered area, adopting a special support where all sensors under testing have been installed. Geomatic instrument have been used to define the reference trajectory, with purpose to compare this one, with the path obtained with IBN solution. First results leads to have an horizontal and vertical accuracies better than 60 cm, respect to the reference trajectories. IBN method, sensors, test and result will be described in the paper.
NASA Astrophysics Data System (ADS)
Endo, Yoichiro; Balloch, Jonathan C.; Grushin, Alexander; Lee, Mun Wai; Handelman, David
2016-05-01
Control of current tactical unmanned ground vehicles (UGVs) is typically accomplished through two alternative modes of operation, namely, low-level manual control using joysticks and high-level planning-based autonomous control. Each mode has its own merits as well as inherent mission-critical disadvantages. Low-level joystick control is vulnerable to communication delay and degradation, and high-level navigation often depends on uninterrupted GPS signals and/or energy-emissive (non-stealth) range sensors such as LIDAR for localization and mapping. To address these problems, we have developed a mid-level control technique where the operator semi-autonomously drives the robot relative to visible landmarks that are commonly recognizable by both humans and machines such as closed contours and structured lines. Our novel solution relies solely on optical and non-optical passive sensors and can be operated under GPS-denied, communication-degraded environments. To control the robot using these landmarks, we developed an interactive graphical user interface (GUI) that allows the operator to select landmarks in the robot's view and direct the robot relative to one or more of the landmarks. The integrated UGV control system was evaluated based on its ability to robustly navigate through indoor environments. The system was successfully field tested with QinetiQ North America's TALON UGV and Tactical Robot Controller (TRC), a ruggedized operator control unit (OCU). We found that the proposed system is indeed robust against communication delay and degradation, and provides the operator with steady and reliable control of the UGV in realistic tactical scenarios.
Chen, Guoliang; Meng, Xiaolin; Wang, Yunjia; Zhang, Yanzhe; Tian, Peng; Yang, Huachao
2015-09-23
Because of the high calculation cost and poor performance of a traditional planar map when dealing with complicated indoor geographic information, a WiFi fingerprint indoor positioning system cannot be widely employed on a smartphone platform. By making full use of the hardware sensors embedded in the smartphone, this study proposes an integrated approach to a three-dimensional (3D) indoor positioning system. First, an improved K-means clustering method is adopted to reduce the fingerprint database retrieval time and enhance positioning efficiency. Next, with the mobile phone's acceleration sensor, a new step counting method based on auto-correlation analysis is proposed to achieve cell phone inertial navigation positioning. Furthermore, the integration of WiFi positioning with Pedestrian Dead Reckoning (PDR) obtains higher positional accuracy with the help of the Unscented Kalman Filter algorithm. Finally, a hybrid 3D positioning system based on Unity 3D, which can carry out real-time positioning for targets in 3D scenes, is designed for the fluent operation of mobile terminals.
Integrated WiFi/PDR/Smartphone Using an Unscented Kalman Filter Algorithm for 3D Indoor Localization
Chen, Guoliang; Meng, Xiaolin; Wang, Yunjia; Zhang, Yanzhe; Tian, Peng; Yang, Huachao
2015-01-01
Because of the high calculation cost and poor performance of a traditional planar map when dealing with complicated indoor geographic information, a WiFi fingerprint indoor positioning system cannot be widely employed on a smartphone platform. By making full use of the hardware sensors embedded in the smartphone, this study proposes an integrated approach to a three-dimensional (3D) indoor positioning system. First, an improved K-means clustering method is adopted to reduce the fingerprint database retrieval time and enhance positioning efficiency. Next, with the mobile phone’s acceleration sensor, a new step counting method based on auto-correlation analysis is proposed to achieve cell phone inertial navigation positioning. Furthermore, the integration of WiFi positioning with Pedestrian Dead Reckoning (PDR) obtains higher positional accuracy with the help of the Unscented Kalman Filter algorithm. Finally, a hybrid 3D positioning system based on Unity 3D, which can carry out real-time positioning for targets in 3D scenes, is designed for the fluent operation of mobile terminals. PMID:26404314
Towards the automatic scanning of indoors with robots.
Adán, Antonio; Quintana, Blanca; Vázquez, Andres S; Olivares, Alberto; Parra, Eduardo; Prieto, Samuel
2015-05-19
This paper is framed in both 3D digitization and 3D data intelligent processing research fields. Our objective is focused on developing a set of techniques for the automatic creation of simple three-dimensional indoor models with mobile robots. The document presents the principal steps of the process, the experimental setup and the results achieved. We distinguish between the stages concerning intelligent data acquisition and 3D data processing. This paper is focused on the first stage. We show how the mobile robot, which carries a 3D scanner, is able to, on the one hand, make decisions about the next best scanner position and, on the other hand, navigate autonomously in the scene with the help of the data collected from earlier scans. After this stage, millions of 3D data are converted into a simplified 3D indoor model. The robot imposes a stopping criterion when the whole point cloud covers the essential parts of the scene. This system has been tested under real conditions indoors with promising results. The future is addressed to extend the method in much more complex and larger scenarios.
Towards the Automatic Scanning of Indoors with Robots
Adán, Antonio; Quintana, Blanca; Vázquez, Andres S.; Olivares, Alberto; Parra, Eduardo; Prieto, Samuel
2015-01-01
This paper is framed in both 3D digitization and 3D data intelligent processing research fields. Our objective is focused on developing a set of techniques for the automatic creation of simple three-dimensional indoor models with mobile robots. The document presents the principal steps of the process, the experimental setup and the results achieved. We distinguish between the stages concerning intelligent data acquisition and 3D data processing. This paper is focused on the first stage. We show how the mobile robot, which carries a 3D scanner, is able to, on the one hand, make decisions about the next best scanner position and, on the other hand, navigate autonomously in the scene with the help of the data collected from earlier scans. After this stage, millions of 3D data are converted into a simplified 3D indoor model. The robot imposes a stopping criterion when the whole point cloud covers the essential parts of the scene. This system has been tested under real conditions indoors with promising results. The future is addressed to extend the method in much more complex and larger scenarios. PMID:25996513
Real-time door detection for indoor autonomous vehicle
NASA Astrophysics Data System (ADS)
He, Zhihao; Zhu, Ming
2017-07-01
Indoor Autonomous Vehicle(IAV) is used in many indoor scenes. Such as hotels and hospitals. Door detection is a key issue to guide the IAV into rooms. In this paper, we consider door detection in the use of indoor navigation of IAV. Since real-time properties are important for real-world IAV, the detection algorithm must be fast enough. Most monocular-camera based door detection model need a perfect detection of the four line segments of the door or the four corners. But in many situations, line segments could be extended or cut off. And there could be many false detected corners. And few of them can distinguish doors from door-like objects with door-like shape effectively. We proposed a 2-D vision model of the door that is made up of line segments. The number of parts detected is used to determine the possibility of a door. Our algorithm is tested on a database of doors.1 The robustness and real-time are verified. The precision is 89.4%. Average time consumed for processing a 640x320 figure is 44.73ms.
iParking: An Intelligent Indoor Location-Based Smartphone Parking Service
Liu, Jingbin; Chen, Ruizhi; Chen, Yuwei; Pei, Ling; Chen, Liang
2012-01-01
Indoor positioning technologies have been widely studied with a number of solutions being proposed, yet substantial applications and services are still fairly primitive. Taking advantage of the emerging concept of the connected car, the popularity of smartphones and mobile Internet, and precise indoor locations, this study presents the development of a novel intelligent parking service called iParking. With the iParking service, multiple parties such as users, parking facilities and service providers are connected through Internet in a distributed architecture. The client software is a light-weight application running on a smartphone, and it works essentially based on a precise indoor positioning solution, which fuses Wireless Local Area Network (WLAN) signals and the measurements of the built-in sensors of the smartphones. The positioning accuracy, availability and reliability of the proposed positioning solution are adequate for facilitating the novel parking service. An iParking prototype has been developed and demonstrated in a real parking environment at a shopping mall. The demonstration showed how the iParking service could improve the parking experience and increase the efficiency of parking facilities. The iParking is a novel service in terms of cost- and energy-efficient solution. PMID:23202179
iParking: an intelligent indoor location-based smartphone parking service.
Liu, Jingbin; Chen, Ruizhi; Chen, Yuwei; Pei, Ling; Chen, Liang
2012-10-31
Indoor positioning technologies have been widely studied with a number of solutions being proposed, yet substantial applications and services are still fairly primitive. Taking advantage of the emerging concept of the connected car, the popularity of smartphones and mobile Internet, and precise indoor locations, this study presents the development of a novel intelligent parking service called iParking. With the iParking service, multiple parties such as users, parking facilities and service providers are connected through Internet in a distributed architecture. The client software is a light-weight application running on a smartphone, and it works essentially based on a precise indoor positioning solution, which fuses Wireless Local Area Network (WLAN) signals and the measurements of the built-in sensors of the smartphones. The positioning accuracy, availability and reliability of the proposed positioning solution are adequate for facilitating the novel parking service. An iParking prototype has been developed and demonstrated in a real parking environment at a shopping mall. The demonstration showed how the iParking service could improve the parking experience and increase the efficiency of parking facilities. The iParking is a novel service in terms of cost- and energy-efficient solution.
PDR with a Foot-Mounted IMU and Ramp Detection
Jiménez, Antonio R.; Seco, Fernando; Zampella, Francisco; Prieto, José C.; Guevara, Jorge
2011-01-01
The localization of persons in indoor environments is nowadays an open problem. There are partial solutions based on the deployment of a network of sensors (Local Positioning Systems or LPS). Other solutions only require the installation of an inertial sensor on the person’s body (Pedestrian Dead-Reckoning or PDR). PDR solutions integrate the signals coming from an Inertial Measurement Unit (IMU), which usually contains 3 accelerometers and 3 gyroscopes. The main problem of PDR is the accumulation of positioning errors due to the drift caused by the noise in the sensors. This paper presents a PDR solution that incorporates a drift correction method based on detecting the access ramps usually found in buildings. The ramp correction method is implemented over a PDR framework that uses an Inertial Navigation algorithm (INS) and an IMU attached to the person’s foot. Unlike other approaches that use external sensors to correct the drift error, we only use one IMU on the foot. To detect a ramp, the slope of the terrain on which the user is walking, and the change in height sensed when moving forward, are estimated from the IMU. After detection, the ramp is checked for association with one of the existing in a database. For each associated ramp, a position correction is fed into the Kalman Filter in order to refine the INS-PDR solution. Drift-free localization is achieved with positioning errors below 2 meters for 1,000-meter-long routes in a building with a few ramps. PMID:22163701
3D modeling of building indoor spaces and closed doors from imagery and point clouds.
Díaz-Vilariño, Lucía; Khoshelham, Kourosh; Martínez-Sánchez, Joaquín; Arias, Pedro
2015-02-03
3D models of indoor environments are increasingly gaining importance due to the wide range of applications to which they can be subjected: from redesign and visualization to monitoring and simulation. These models usually exist only for newly constructed buildings; therefore, the development of automatic approaches for reconstructing 3D indoors from imagery and/or point clouds can make the process easier, faster and cheaper. Among the constructive elements defining a building interior, doors are very common elements and their detection can be very useful either for knowing the environment structure, to perform an efficient navigation or to plan appropriate evacuation routes. The fact that doors are topologically connected to walls by being coplanar, together with the unavoidable presence of clutter and occlusions indoors, increases the inherent complexity of the automation of the recognition process. In this work, we present a pipeline of techniques used for the reconstruction and interpretation of building interiors based on point clouds and images. The methodology analyses the visibility problem of indoor environments and goes in depth with door candidate detection. The presented approach is tested in real data sets showing its potential with a high door detection rate and applicability for robust and efficient envelope reconstruction.
Technical Solutions to Common Indoor Air Quality Issues in Schools
Indoor Air Quality (IAQ) Design Tools for Schools provides voluntary guidance for school personnel, architects, engineers, builders and contractors, parents, and the community on key school construction and renovation issues.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Czejdo, Bogdan; Bhattacharya, Sambit; Ferragut, Erik M
2012-01-01
This paper describes the syntax and semantics of multi-level state diagrams to support probabilistic behavior of cooperating robots. The techniques are presented to analyze these diagrams by querying combined robots behaviors. It is shown how to use state abstraction and transition abstraction to create, verify and process large probabilistic state diagrams.
An Indoor Location-Based Control System Using Bluetooth Beacons for IoT Systems.
Huh, Jun-Ho; Seo, Kyungryong
2017-12-19
The indoor location-based control system estimates the indoor position of a user to provide the service he/she requires. The major elements involved in the system are the localization server, service-provision client, user application positioning technology. The localization server controls access of terminal devices (e.g., Smart Phones and other wireless devices) to determine their locations within a specified space first and then the service-provision client initiates required services such as indoor navigation and monitoring/surveillance. The user application provides necessary data to let the server to localize the devices or allow the user to receive various services from the client. The major technological elements involved in this system are indoor space partition method, Bluetooth 4.0, RSSI (Received Signal Strength Indication) and trilateration. The system also employs the BLE communication technology when determining the position of the user in an indoor space. The position information obtained is then used to control a specific device(s). These technologies are fundamental in achieving a "Smart Living". An indoor location-based control system that provides services by estimating user's indoor locations has been implemented in this study (First scenario). The algorithm introduced in this study (Second scenario) is effective in extracting valid samples from the RSSI dataset but has it has some drawbacks as well. Although we used a range-average algorithm that measures the shortest distance, there are some limitations because the measurement results depend on the sample size and the sample efficiency depends on sampling speeds and environmental changes. However, the Bluetooth system can be implemented at a relatively low cost so that once the problem of precision is solved, it can be applied to various fields.
An Indoor Location-Based Control System Using Bluetooth Beacons for IoT Systems
Huh, Jun-Ho; Seo, Kyungryong
2017-01-01
The indoor location-based control system estimates the indoor position of a user to provide the service he/she requires. The major elements involved in the system are the localization server, service-provision client, user application positioning technology. The localization server controls access of terminal devices (e.g., Smart Phones and other wireless devices) to determine their locations within a specified space first and then the service-provision client initiates required services such as indoor navigation and monitoring/surveillance. The user application provides necessary data to let the server to localize the devices or allow the user to receive various services from the client. The major technological elements involved in this system are indoor space partition method, Bluetooth 4.0, RSSI (Received Signal Strength Indication) and trilateration. The system also employs the BLE communication technology when determining the position of the user in an indoor space. The position information obtained is then used to control a specific device(s). These technologies are fundamental in achieving a “Smart Living”. An indoor location-based control system that provides services by estimating user’s indoor locations has been implemented in this study (First scenario). The algorithm introduced in this study (Second scenario) is effective in extracting valid samples from the RSSI dataset but has it has some drawbacks as well. Although we used a range-average algorithm that measures the shortest distance, there are some limitations because the measurement results depend on the sample size and the sample efficiency depends on sampling speeds and environmental changes. However, the Bluetooth system can be implemented at a relatively low cost so that once the problem of precision is solved, it can be applied to various fields. PMID:29257044
Flow-based ammonia gas analyzer with an open channel scrubber for indoor environments.
Ohira, Shin-Ichi; Heima, Minako; Yamasaki, Takayuki; Tanaka, Toshinori; Koga, Tomoko; Toda, Kei
2013-11-15
A robust and fully automated indoor ammonia gas monitoring system with an open channel scrubber (OCS) was developed. The sample gas channel dimensions, hydrophilic surface treatment to produce a thin absorbing solution layer, and solution flow rate of the OCS were optimized to connect the OCS as in-line gas collector and avoid sample humidity effects. The OCS effluent containing absorbed ammonia in sample gas was injected into a derivatization solution flow. Derivatization was achieved with o-phthalaldehyde and sulfite in pH 11 buffer solution. The product, 1-sulfonateisoindole, is detected with a home-made fluorescence detector. The limit of detection of the analyzer based on three times the standard deviation of baseline noise was 0.9 ppbv. Sample gas could be analyzed 40 times per hour. Furthermore, relative humidity of up to 90% did not interfere considerably with the analyzer. Interference from amines was not observed. The developed gas analysis system was calibrated using a solution-based method. The system was used to analyze ammonia in an indoor environment along with an off-site method, traditional impinger gas collection followed by ion chromatographic analysis, for comparison. The results obtained using both methods agreed well. Therefore, the developed system can perform on-site monitoring of ammonia in indoor environments with improved time resolution compared with that of other methods. Crown Copyright © 2013 Published by Elsevier B.V. All rights reserved.
Visual Positioning Indoors: Human Eyes vs. Smartphone Cameras
Wu, Dewen; Chen, Ruizhi; Chen, Liang
2017-01-01
Artificial Intelligence (AI) technologies and their related applications are now developing at a rapid pace. Indoor positioning will be one of the core technologies that enable AI applications because people spend 80% of their time indoors. Humans can locate themselves related to a visually well-defined object, e.g., a door, based on their visual observations. Can a smartphone camera do a similar job when it points to an object? In this paper, a visual positioning solution was developed based on a single image captured from a smartphone camera pointing to a well-defined object. The smartphone camera simulates the process of human eyes for the purpose of relatively locating themselves against a well-defined object. Extensive experiments were conducted with five types of smartphones on three different indoor settings, including a meeting room, a library, and a reading room. Experimental results shown that the average positioning accuracy of the solution based on five smartphone cameras is 30.6 cm, while that for the human-observed solution with 300 samples from 10 different people is 73.1 cm. PMID:29144420
Visual Positioning Indoors: Human Eyes vs. Smartphone Cameras.
Wu, Dewen; Chen, Ruizhi; Chen, Liang
2017-11-16
Artificial Intelligence (AI) technologies and their related applications are now developing at a rapid pace. Indoor positioning will be one of the core technologies that enable AI applications because people spend 80% of their time indoors. Humans can locate themselves related to a visually well-defined object, e.g., a door, based on their visual observations. Can a smartphone camera do a similar job when it points to an object? In this paper, a visual positioning solution was developed based on a single image captured from a smartphone camera pointing to a well-defined object. The smartphone camera simulates the process of human eyes for the purpose of relatively locating themselves against a well-defined object. Extensive experiments were conducted with five types of smartphones on three different indoor settings, including a meeting room, a library, and a reading room. Experimental results shown that the average positioning accuracy of the solution based on five smartphone cameras is 30.6 cm, while that for the human-observed solution with 300 samples from 10 different people is 73.1 cm.
Regionalized Lunar South Pole Surface Navigation System Analysis
NASA Technical Reports Server (NTRS)
Welch, Bryan W.
2008-01-01
Apollo missions utilized Earth-based assets for navigation because the landings took place at lunar locations in constant view from the Earth. The new exploration campaign to the lunar south pole region will have limited Earth visibility, but the extent to which a navigation system comprised solely of Earth-based tracking stations will provide adequate navigation solutions in this region is unknown. This report presents a dilution-of-precision (DoP)-based, stationary surface navigation analysis of the performance of multiple lunar satellite constellations, Earth-based deep space network assets, and combinations thereof. Results show that kinematic and integrated solutions cannot be provided by the Earth-based deep space network stations. Also, the stationary surface navigation system needs to be operated either as a two-way navigation system or as a one-way navigation system with local terrain information, while the position solution is integrated over a short duration of time with navigation signals being provided by a lunar satellite constellation.
NASA Astrophysics Data System (ADS)
Ikeda, Takeshi; Kawamoto, Mitsuru; Sashima, Akio; Suzuki, Keiji; Kurumatani, Koichi
In the field of the ubiquitous computing, positioning systems which can provide users' location information have paid attention as an important technical element which can be applied to various services, for example, indoor navigation services, evacuation services, market research services, guidance services, and so on. A lot of researchers have proposed various outdoor and indoor positioning systems. In this paper, we deal with indoor positioning systems. Many conventional indoor positioning systems use expensive infrastructures, because the propagated times of radio waves are used to measure users' positions with high accuracy. In this paper, we propose an indoor autonomous positioning system using radio signal strengths (RSSs) based on ISM band communications. In order to estimate users' positions, the proposed system utilizes a particle filter that is one of the Monte Carlo methods. Because the RSS information is used in the proposed system, the equipments configuring the system are not expensive compared with the conventional indoor positioning systems and it can be installed easily. Moreover, because the particle filter is used to estimate user's position, even if the RSS fluctuates due to, for example, multi-paths, the system can carry out position estimation robustly. We install the proposed system in one floor of a building and carry out some experiments in order to verify the validity of the proposed system. As a result, we confirmed that the average of the estimation errors of the proposed system was about 1.8 m, where the result is enough accuracy for achieving the services mentioned above.
A Vision-Based Relative Navigation Approach for Autonomous Multirotor Aircraft
NASA Astrophysics Data System (ADS)
Leishman, Robert C.
Autonomous flight in unstructured, confined, and unknown GPS-denied environments is a challenging problem. Solutions could be tremendously beneficial for scenarios that require information about areas that are difficult to access and that present a great amount of risk. The goal of this research is to develop a new framework that enables improved solutions to this problem and to validate the approach with experiments using a hardware prototype. In Chapter 2 we examine the consequences and practical aspects of using an improved dynamic model for multirotor state estimation, using only IMU measurements. The improved model correctly explains the measurements available from the accelerometers on a multirotor. We provide hardware results demonstrating the improved attitude, velocity and even position estimates that can be achieved through the use of this model. We propose a new architecture to simplify some of the challenges that constrain GPS-denied aerial flight in Chapter 3. At the core, the approach combines visual graph-SLAM with a multiplicative extended Kalman filter (MEKF). More importantly, we depart from the common practice of estimating global states and instead keep the position and yaw states of the MEKF relative to the current node in the map. This relative navigation approach provides a tremendous benefit compared to maintaining estimates with respect to a single global coordinate frame. We discuss the architecture of this new system and provide important details for each component. We verify the approach with goal-directed autonomous flight-test results. The MEKF is the basis of the new relative navigation approach and is detailed in Chapter 4. We derive the relative filter and show how the states must be augmented and marginalized each time a new node is declared. The relative estimation approach is verified using hardware flight test results accompanied by comparisons to motion capture truth. Additionally, flight results with estimates in the control loop are provided. We believe that the relative, vision-based framework described in this work is an important step in furthering the capabilities of indoor aerial navigation in confined, unknown environments. Current approaches incur challenging problems by requiring globally referenced states. Utilizing a relative approach allows more flexibility as the critical, real-time processes of localization and control do not depend on computationally-demanding optimization and loop-closure processes.
On-off keying transmitter design for navigation by visible light communication
NASA Astrophysics Data System (ADS)
Louro, P.; Vieira, M.; Costa, J.; Vieira, M. A.
2018-02-01
White LEDS revolutionized the field of illumination technology mainly due to the energy saving effects. Besides lighting purposes LEDs can also be used in wireless communication systems when integrated in Visible Light Communication (VLC) systems. Indoor positioning for navigation in large buildings is currently under research to overcome the difficulties associated with the use of GPS in such environments. The motivation for this application is also supported by the possibility of taking advantage of an existing lighting and WiFi infrastructure. In this work it is proposed an indoor navigation system based on the use of VLC technology. The proposed system includes trichromatic white LEDs with the red and blue chips modulated at different frequencies and a pinpin photodetector with selective spectral sensitivity. Optoelectronic features of both optical sources and photodetector device are analyzed. The photodetector device consists two pin structures based on a-SiC:H and a-Si:H with geometrical configuration optimized for the detection of short and large wavelengths in the visible range. Its sensitivity is externally tuned by steady state optical bias. The localization algorithm makes use of the Fourier transform to identify the frequencies present in the photocurrent signal and the wavelength filtering properties of the sensor under front and back optical bias to detect the existing red and blue signals. The viability of the system was demonstrated through the implementation of an automatic algorithm to infer the photodetector cardinal direction. A capacitive optoelectronic model supports the experimental results and explains the device operation.
An IMM-Aided ZUPT Methodology for an INS/DVL Integrated Navigation System.
Yao, Yiqing; Xu, Xiaosu; Xu, Xiang
2017-09-05
Inertial navigation system (INS)/Doppler velocity log (DVL) integration is the most common navigation solution for underwater vehicles. Due to the complex underwater environment, the velocity information provided by DVL always contains some errors. To improve navigation accuracy, zero velocity update (ZUPT) technology is considered, which is an effective algorithm for land vehicles to mitigate the navigation error during the pure INS mode. However, in contrast to ground vehicles, the ZUPT solution cannot be used directly for underwater vehicles because of the existence of the water current. In order to leverage the strengths of the ZUPT method and the INS/DVL solution, an interactive multiple model (IMM)-aided ZUPT methodology for the INS/DVL-integrated underwater navigation system is proposed. Both the INS/DVL and INS/ZUPT models are constructed and operated in parallel, with weights calculated according to their innovations and innovation covariance matrices. Simulations are conducted to evaluate the proposed algorithm. The results indicate that the IMM-aided ZUPT solution outperforms both the INS/DVL solution and the INS/ZUPT solution in the underwater environment, which can properly distinguish between the ZUPT and non-ZUPT conditions. In addition, during DVL outage, the effectiveness of the proposed algorithm is also verified.
Assessment of Indoor Route-finding Technology for People with Visual Impairment
Kalia, Amy A.; Legge, Gordon E.; Roy, Rudrava; Ogale, Advait
2010-01-01
This study investigated navigation with route instructions generated by digital-map software and synthetic speech. Participants, either visually impaired or sighted wearing blind folds, successfully located rooms in an unfamiliar building. Users with visual impairment demonstrated better route-finding performance when the technology provided distance information in number of steps rather than walking time or number of feet. PMID:21869851
Synergies in Astrometry: Predicting Navigational Error of Visual Binary Stars
NASA Astrophysics Data System (ADS)
Gessner Stewart, Susan
2015-08-01
Celestial navigation can employ a number of bright stars which are in binary systems. Often these are unresolved, appearing as a single, center-of-light object. A number of these systems are, however, in wide systems which could introduce a margin of error in the navigation solution if not handled properly. To illustrate the importance of good orbital solutions for binary systems - as well as good astrometry in general - the relationship between the center-of-light versus individual catalog position of celestial bodies and the error in terrestrial position derived via celestial navigation is demonstrated. From the list of navigational binary stars, fourteen such binary systems with at least 3.0 arcseconds apparent separation are explored. Maximum navigational error is estimated under the assumption that the bright star in the pair is observed at maximum separation, but the center-of-light is employed in the navigational solution. The relationships between navigational error and separation, orbital periods, and observers' latitude are discussed.
Strategies and Challenges in Preventing Violence Against Canadian Indoor Sex Workers
Guta, Adrian
2018-01-01
Objectives. To examine indoor sex workers’ strategies in preventing workplace violence and influential socio-structural conditions. Methods. Data included qualitative interviews with 85 sex workers in British Columbia, Canada, from 2014 through 2016. For analyses, we used interpretive thematic techniques informed by World Health Organization position statements on violence. Results. Robbery, nonpayment, financial exploitation, and privacy violations were frequent types of violence perpetrated by clients, landlords, and neighbors. We identified 2 themes that depicted how sex workers prevented violence and mitigated its effects: (1) navigating physical spaces and (2) navigating client relationships. Conclusions. Sex workers’ diverse strategies to prevent violence and mitigate its effects are creative and effective in many circumstances. These are limited, however, by the absence of legal and public health regulations governing occupational health and safety and stigma associated with sex work. Public Health Implications. Occupational health and safety regulatory policies that set conditions for clients’ substance and condom use within commercial sex transactions are required. Revisions to the current legal regulations governing prostitution are critical to support optimal work environments that reduce the likelihood of violence. These revisions must recognize sex work as a form of labor versus victimization. PMID:29346001
Huang, Wei Pin; Wang, Chia Cheng; Hung, Jo Hua; Chien, Kai Chun; Liu, Wen-Yu; Cheng, Chih-Hsiu; Ng, How-Hing; Lin, Yang-Hua
2015-02-01
[Purpose] This study aimed to determine the effectiveness of joystick-controlled video console games in enhancing subjects' ability to control power wheelchairs. [Subjects and Methods] Twenty healthy young adults without prior experience of driving power wheelchairs were recruited. Four commercially available video games were used as training programs to practice joystick control in catching falling objects, crossing a river, tracing the route while floating on a river, and navigating through a garden maze. An indoor power wheelchair driving test, including straight lines, and right and left turns, was completed before and after the video game practice, during which electromyographic signals of the upper limbs were recorded. The paired t-test was used to compare the differences in driving performance and muscle activities before and after the intervention. [Results] Following the video game intervention, participants took significantly less time to complete the course, with less lateral deviation when turning the indoor power wheelchair. However, muscle activation in the upper limbs was not significantly affected. [Conclusion] This study demonstrates the feasibility of using joystick-controlled commercial video games to train individuals in the control of indoor power wheelchairs.
Doing Your Homework on Indoor Air Quality Issues.
ERIC Educational Resources Information Center
Caldwell, Rick
2000-01-01
Explains how administrators at the Georgia Institute of Technology were able to build a new residence hall that included a cost-effective ventilation system providing high quality indoor air. Project considerations, design solutions, and project economies are discussed. (GR)
Visible light communication technology for fine-grained indoor localization
NASA Astrophysics Data System (ADS)
Vieira, M.; Vieira, M. A.; Louro, P.; Fantoni, A.; Vieira, P.
2018-02-01
This paper focuses on designing and analysing a visible light based communication and positioning system. The indoor positioning system uses trichromatic white Light Emitting Diodes (LEDs), both for illumination purposes and as transmitters, and an optical processor, based on a-SiC:H technology, as mobile receiver. On-Off Keying (OOK) modulation scheme is used, proving a good trade-off between system performance and implementation complexity. In the following, the relationship between the transmitted data and the received output levels is decoded. LED bulbs work as transmitters, sending information together with different identifiers, IDs, related to their physical locations. Square and diamond topologies for the unit cell are analyzed, and a 2D localization design, demonstrated by a prototype implementation, is presented. Fine-grained indoor localization is tested. The received signal is used in coded multiplexing techniques for supporting communications and navigation concomitantly on the same channel. The location and motion information is found by mapping the position and estimating the location areas.
An IMM-Aided ZUPT Methodology for an INS/DVL Integrated Navigation System
Yao, Yiqing
2017-01-01
Inertial navigation system (INS)/Doppler velocity log (DVL) integration is the most common navigation solution for underwater vehicles. Due to the complex underwater environment, the velocity information provided by DVL always contains some errors. To improve navigation accuracy, zero velocity update (ZUPT) technology is considered, which is an effective algorithm for land vehicles to mitigate the navigation error during the pure INS mode. However, in contrast to ground vehicles, the ZUPT solution cannot be used directly for underwater vehicles because of the existence of the water current. In order to leverage the strengths of the ZUPT method and the INS/DVL solution, an interactive multiple model (IMM)-aided ZUPT methodology for the INS/DVL-integrated underwater navigation system is proposed. Both the INS/DVL and INS/ZUPT models are constructed and operated in parallel, with weights calculated according to their innovations and innovation covariance matrices. Simulations are conducted to evaluate the proposed algorithm. The results indicate that the IMM-aided ZUPT solution outperforms both the INS/DVL solution and the INS/ZUPT solution in the underwater environment, which can properly distinguish between the ZUPT and non-ZUPT conditions. In addition, during DVL outage, the effectiveness of the proposed algorithm is also verified. PMID:28872602
Indoor Photogrammetry Aided with Uwb Navigation
NASA Astrophysics Data System (ADS)
Masiero, A.; Fissore, F.; Guarnieri, A.; Vettore, A.
2018-05-01
The subject of photogrammetric surveying with mobile devices, in particular smartphones, is becoming of significant interest in the research community. Nowadays, the process of providing 3D point clouds with photogrammetric procedures is well known. However, external information is still typically needed in order to move from the point cloud obtained from images to a 3D metric reconstruction. This paper investigates the integration of information provided by an UWB positioning system with visual based reconstruction to produce a metric reconstruction. Furthermore, the orientation (with respect to North-East directions) of the obtained model is assessed thanks to the use of inertial sensors included in the considered UWB devices. Results of this integration are shown on two case studies in indoor environments.
UGV navigation in wireless sensor and actuator network environments
NASA Astrophysics Data System (ADS)
Zhang, Guyu; Li, Jianfeng; Duncan, Christian A.; Kanno, Jinko; Selmic, Rastko R.
2012-06-01
We consider a navigation problem in a distributed, self-organized and coordinate-free Wireless Sensor and Ac- tuator Network (WSAN). We rst present navigation algorithms that are veried using simulation results. Con- sidering more than one destination and multiple mobile Unmanned Ground Vehicles (UGVs), we introduce a distributed solution to the Multi-UGV, Multi-Destination navigation problem. The objective of the solution to this problem is to eciently allocate UGVs to dierent destinations and carry out navigation in the network en- vironment that minimizes total travel distance. The main contribution of this paper is to develop a solution that does not attempt to localize either the UGVs or the sensor and actuator nodes. Other than some connectivity as- sumptions about the communication graph, we consider that no prior information about the WSAN is available. The solution presented here is distributed, and the UGV navigation is solely based on feedback from neigh- boring sensor and actuator nodes. One special case discussed in the paper, the Single-UGV, Multi-Destination navigation problem, is essentially equivalent to the well-known and dicult Traveling Salesman Problem (TSP). Simulation results are presented that illustrate the navigation distance traveled through the network. We also introduce an experimental testbed for the realization of coordinate-free and localization-free UGV navigation. We use the Cricket platform as the sensor and actuator network and a Pioneer 3-DX robot as the UGV. The experiments illustrate the UGV navigation in a coordinate-free WSAN environment where the UGV successfully arrives at the assigned destinations.
Liu, Zhijian; Li, Hao; Cao, Guoqing
2017-07-30
Indoor airborne culturable bacteria are sometimes harmful to human health. Therefore, a quick estimation of their concentration is particularly necessary. However, measuring the indoor microorganism concentration (e.g., bacteria) usually requires a large amount of time, economic cost, and manpower. In this paper, we aim to provide a quick solution: using knowledge-based machine learning to provide quick estimation of the concentration of indoor airborne culturable bacteria only with the inputs of several measurable indoor environmental indicators, including: indoor particulate matter (PM 2.5 and PM 10 ), temperature, relative humidity, and CO₂ concentration. Our results show that a general regression neural network (GRNN) model can sufficiently provide a quick and decent estimation based on the model training and testing using an experimental database with 249 data groups.
A hybrid data fusion method for GNSS/INS integration navigation system
NASA Astrophysics Data System (ADS)
Yang, Ling; Li, Bofeng; Shen, Yunzhong; Li, Haojun
2017-04-01
Although DGNSS is widely used and PPP-GNSS is nowadays a viable precise positioning technology option, the major disadvantage of GNSS still remains: signal blockage due to obstructions in urban and built up environments, and extreme power attenuation of the signals when operated indoors. The combination of GNSS with other sensors, such as a self-contained inertial navigation system (INS), provides an ideal position and attitude determination solution which can not only mitigate the weakness of GNSS, but also bound the INS error that otherwise would grow with time when the INS operates alone. However, the navigation accuracy provided by GNSS/INS strongly depends on the quality and geometry of the GNSS observations, the quality of the INS technology used, and the integration model applied. There are two main types of coupled schemes for integration systems: loosely coupled integration and tightly coupled integration. In loosely coupled integration, position measurements are taken from both systems and combined optimally, usually in a Kalman filter. Tightly coupled integration directly combines the raw pseudorange or carrier phase measurements of GNSS with inertial measurements in an extended Kalman filter. The latter technique improves the ability to resolve ambiguities, i.e. allows a quicker recovery from outage events such as a loss of signal under vegetation. In recent years, tightly coupled differential carrier phase GNSS/INS integration has become popular, because it has the advantage of providing accurate position information even when GPS measurements are rank-deficient in stand-alone processing and is theoretically optimal in a filtering sense, especially in urban navigation applications. However, the heavier computational burden and sensor communication usually complicate the tightly coupled integration and reduce the system efficiency, compared with the loosely coupled integration. In this paper, it has been proved that the loosely coupled and tightly coupled algorithms are equivalent when following conditions are satisfied: 1) there is enough redundancy on the GNSS raw measurements; 2) only pseudorange measurements are used; 3) If differential carrier phase measurements are used, only the float solutions of the ambiguities are considered; 4) the covariance of the loosely coupled measurement model should come from the GNSS standalone solution instead of conventional pre-determined values. Based on the equivalence proof, a dual-step loosely coupled procedure is proposed to regenerate the equal ambiguity fixing solutions in tightly coupled procedure. Accordingly, the tightly coupled differential carrier phase or pseudorange GNSS/INS integration can be simplified, which will degrade to an equivalent loosely coupled integration when there are enough measurement redundancy and recover to a tightly coupled integration when GNSS measurements are rank-deficient. By this hybrid data fusion method, both the optimality of the tightly coupled algorithm and the efficiency of the loosely coupled algorithm can be conserved. Field test results confirm the effectiveness of the proposed method.
A navigation system for the visually impaired an intelligent white cane.
Fukasawa, A Jin; Magatani, Kazusihge
2012-01-01
In this paper, we describe about a developed navigation system that supports the independent walking of the visually impaired in the indoor space. Our developed instrument consists of a navigation system and a map information system. These systems are installed on a white cane. Our navigation system can follow a colored navigation line that is set on the floor. In this system, a color sensor installed on the tip of a white cane, this sensor senses a color of navigation line and the system informs the visually impaired that he/she is walking along the navigation line by vibration. This color recognition system is controlled by a one-chip microprocessor. RFID tags and a receiver for these tags are used in the map information system. RFID tags are set on the colored navigation line. An antenna for RFID tags and a tag receiver are also installed on a white cane. The receiver receives the area information as a tag-number and notifies map information to the user by mp3 formatted pre-recorded voice. And now, we developed the direction identification technique. Using this technique, we can detect a user's walking direction. A triaxiality acceleration sensor is used in this system. Three normal subjects who were blindfolded with an eye mask were tested with our developed navigation system. All of them were able to walk along the navigation line perfectly. We think that the performance of the system is good. Therefore, our system will be extremely valuable in supporting the activities of the visually impaired.
Precise visual navigation using multi-stereo vision and landmark matching
NASA Astrophysics Data System (ADS)
Zhu, Zhiwei; Oskiper, Taragay; Samarasekera, Supun; Kumar, Rakesh
2007-04-01
Traditional vision-based navigation system often drifts over time during navigation. In this paper, we propose a set of techniques which greatly reduce the long term drift and also improve its robustness to many failure conditions. In our approach, two pairs of stereo cameras are integrated to form a forward/backward multi-stereo camera system. As a result, the Field-Of-View of the system is extended significantly to capture more natural landmarks from the scene. This helps to increase the pose estimation accuracy as well as reduce the failure situations. Secondly, a global landmark matching technique is used to recognize the previously visited locations during navigation. Using the matched landmarks, a pose correction technique is used to eliminate the accumulated navigation drift. Finally, in order to further improve the robustness of the system, measurements from low-cost Inertial Measurement Unit (IMU) and Global Positioning System (GPS) sensors are integrated with the visual odometry in an extended Kalman Filtering framework. Our system is significantly more accurate and robust than previously published techniques (1~5% localization error) over long-distance navigation both indoors and outdoors. Real world experiments on a human worn system show that the location can be estimated within 1 meter over 500 meters (around 0.1% localization error averagely) without the use of GPS information.
EPA Science Matters Newsletter: Working with Navajo Nation for Cleaner, Healthier Heat
EPA researchers and partners are teaming up to explore how to improve indoor air and health for Navajo Nation. Read about the results of the study and the proposed solutions to minimize indoor air pollution for the Navajo.
Connors, Erin C; Chrastil, Elizabeth R; Sánchez, Jaime; Merabet, Lotfi B
2014-01-01
For individuals who are blind, navigating independently in an unfamiliar environment represents a considerable challenge. Inspired by the rising popularity of video games, we have developed a novel approach to train navigation and spatial cognition skills in adolescents who are blind. Audio-based Environment Simulator (AbES) is a software application that allows for the virtual exploration of an existing building set in an action video game metaphor. Using this ludic-based approach to learning, we investigated the ability and efficacy of adolescents with early onset blindness to acquire spatial information gained from the exploration of a target virtual indoor environment. Following game play, participants were assessed on their ability to transfer and mentally manipulate acquired spatial information on a set of navigation tasks carried out in the real environment. Success in transfer of navigation skill performance was markedly high suggesting that interacting with AbES leads to the generation of an accurate spatial mental representation. Furthermore, there was a positive correlation between success in game play and navigation task performance. The role of virtual environments and gaming in the development of mental spatial representations is also discussed. We conclude that this game based learning approach can facilitate the transfer of spatial knowledge and further, can be used by individuals who are blind for the purposes of navigation in real-world environments.
Connors, Erin C.; Chrastil, Elizabeth R.; Sánchez, Jaime; Merabet, Lotfi B.
2014-01-01
For individuals who are blind, navigating independently in an unfamiliar environment represents a considerable challenge. Inspired by the rising popularity of video games, we have developed a novel approach to train navigation and spatial cognition skills in adolescents who are blind. Audio-based Environment Simulator (AbES) is a software application that allows for the virtual exploration of an existing building set in an action video game metaphor. Using this ludic-based approach to learning, we investigated the ability and efficacy of adolescents with early onset blindness to acquire spatial information gained from the exploration of a target virtual indoor environment. Following game play, participants were assessed on their ability to transfer and mentally manipulate acquired spatial information on a set of navigation tasks carried out in the real environment. Success in transfer of navigation skill performance was markedly high suggesting that interacting with AbES leads to the generation of an accurate spatial mental representation. Furthermore, there was a positive correlation between success in game play and navigation task performance. The role of virtual environments and gaming in the development of mental spatial representations is also discussed. We conclude that this game based learning approach can facilitate the transfer of spatial knowledge and further, can be used by individuals who are blind for the purposes of navigation in real-world environments. PMID:24653690
Connors, Erin C; Yazzolino, Lindsay A; Sánchez, Jaime; Merabet, Lotfi B
2013-03-27
Audio-based Environment Simulator (AbES) is virtual environment software designed to improve real world navigation skills in the blind. Using only audio based cues and set within the context of a video game metaphor, users gather relevant spatial information regarding a building's layout. This allows the user to develop an accurate spatial cognitive map of a large-scale three-dimensional space that can be manipulated for the purposes of a real indoor navigation task. After game play, participants are then assessed on their ability to navigate within the target physical building represented in the game. Preliminary results suggest that early blind users were able to acquire relevant information regarding the spatial layout of a previously unfamiliar building as indexed by their performance on a series of navigation tasks. These tasks included path finding through the virtual and physical building, as well as a series of drop off tasks. We find that the immersive and highly interactive nature of the AbES software appears to greatly engage the blind user to actively explore the virtual environment. Applications of this approach may extend to larger populations of visually impaired individuals.
Open-Loop Flight Testing of COBALT Navigation and Sensor Technologies for Precise Soft Landing
NASA Technical Reports Server (NTRS)
Carson, John M., III; Restrepo, Caroline I.; Seubert, Carl R.; Amzajerdian, Farzin; Pierrottet, Diego F.; Collins, Steven M.; O'Neal, Travis V.; Stelling, Richard
2017-01-01
An open-loop flight test campaign of the NASA COBALT (CoOperative Blending of Autonomous Landing Technologies) payload was conducted onboard the Masten Xodiac suborbital rocket testbed. The payload integrates two complementary sensor technologies that together provide a spacecraft with knowledge during planetary descent and landing to precisely navigate and softly touchdown in close proximity to targeted surface locations. The two technologies are the Navigation Doppler Lidar (NDL), for high-precision velocity and range measurements, and the Lander Vision System (LVS) for map-relative state esti- mates. A specialized navigation filter running onboard COBALT fuses the NDL and LVS data in real time to produce a very precise Terrain Relative Navigation (TRN) solution that is suitable for future, autonomous planetary landing systems that require precise and soft landing capabilities. During the open-loop flight campaign, the COBALT payload acquired measurements and generated a precise navigation solution, but the Xodiac vehicle planned and executed its maneuvers based on an independent, GPS-based navigation solution. This minimized the risk to the vehicle during the integration and testing of the new navigation sensing technologies within the COBALT payload.
Acoustic Sensors for Air and Surface Navigation Applications
Kapoor, Rohan; Ramasamy, Subramanian; Schyndel, Ron Van
2018-01-01
This paper presents the state-of-the-art and reviews the state-of-research of acoustic sensors used for a variety of navigation and guidance applications on air and surface vehicles. In particular, this paper focuses on echolocation, which is widely utilized in nature by certain mammals (e.g., cetaceans and bats). Although acoustic sensors have been extensively adopted in various engineering applications, their use in navigation and guidance systems is yet to be fully exploited. This technology has clear potential for applications in air and surface navigation/guidance for intelligent transport systems (ITS), especially considering air and surface operations indoors and in other environments where satellite positioning is not available. Propagation of sound in the atmosphere is discussed in detail, with all potential attenuation sources taken into account. The errors introduced in echolocation measurements due to Doppler, multipath and atmospheric effects are discussed, and an uncertainty analysis method is presented for ranging error budget prediction in acoustic navigation applications. Considering the design challenges associated with monostatic and multi-static sensor implementations and looking at the performance predictions for different possible configurations, acoustic sensors show clear promises in navigation, proximity sensing, as well as obstacle detection and tracking. The integration of acoustic sensors in multi-sensor navigation systems is also considered towards the end of the paper and a low Size, Weight and Power, and Cost (SWaP-C) sensor integration architecture is presented for possible introduction in air and surface navigation systems. PMID:29414894
Liu, Zhijian; Li, Hao; Cao, Guoqing
2017-01-01
Indoor airborne culturable bacteria are sometimes harmful to human health. Therefore, a quick estimation of their concentration is particularly necessary. However, measuring the indoor microorganism concentration (e.g., bacteria) usually requires a large amount of time, economic cost, and manpower. In this paper, we aim to provide a quick solution: using knowledge-based machine learning to provide quick estimation of the concentration of indoor airborne culturable bacteria only with the inputs of several measurable indoor environmental indicators, including: indoor particulate matter (PM2.5 and PM10), temperature, relative humidity, and CO2 concentration. Our results show that a general regression neural network (GRNN) model can sufficiently provide a quick and decent estimation based on the model training and testing using an experimental database with 249 data groups. PMID:28758941
Sensitivity of planetary cruise navigation to earth orientation calibration errors
NASA Technical Reports Server (NTRS)
Estefan, J. A.; Folkner, W. M.
1995-01-01
A detailed analysis was conducted to determine the sensitivity of spacecraft navigation errors to the accuracy and timeliness of Earth orientation calibrations. Analyses based on simulated X-band (8.4-GHz) Doppler and ranging measurements acquired during the interplanetary cruise segment of the Mars Pathfinder heliocentric trajectory were completed for the nominal trajectory design and for an alternative trajectory with a longer transit time. Several error models were developed to characterize the effect of Earth orientation on navigational accuracy based on current and anticipated Deep Space Network calibration strategies. The navigational sensitivity of Mars Pathfinder to calibration errors in Earth orientation was computed for each candidate calibration strategy with the Earth orientation parameters included as estimated parameters in the navigation solution. In these cases, the calibration errors contributed 23 to 58% of the total navigation error budget, depending on the calibration strategy being assessed. Navigation sensitivity calculations were also performed for cases in which Earth orientation calibration errors were not adjusted in the navigation solution. In these cases, Earth orientation calibration errors contributed from 26 to as much as 227% of the total navigation error budget. The final analysis suggests that, not only is the method used to calibrate Earth orientation vitally important for precision navigation of Mars Pathfinder, but perhaps equally important is the method for inclusion of the calibration errors in the navigation solutions.
Ravankar, Abhijeet; Ravankar, Ankit A.; Kobayashi, Yukinori; Emaru, Takanori
2017-01-01
Hitchhiking is a means of transportation gained by asking other people for a (free) ride. We developed a multi-robot system which is the first of its kind to incorporate hitchhiking in robotics, and discuss its advantages. Our method allows the hitchhiker robot to skip redundant computations in navigation like path planning, localization, obstacle avoidance, and map update by completely relying on the driver robot. This allows the hitchhiker robot, which performs only visual servoing, to save computation while navigating on the common path with the driver robot. The driver robot, in the proposed system performs all the heavy computations in navigation and updates the hitchhiker about the current localized positions and new obstacle positions in the map. The proposed system is robust to recover from ‘driver-lost’ scenario which occurs due to visual servoing failure. We demonstrate robot hitchhiking in real environments considering factors like service-time and task priority with different start and goal configurations of the driver and hitchhiker robots. We also discuss the admissible characteristics of the hitchhiker, when hitchhiking should be allowed and when not, through experimental results. PMID:28809803
Ravankar, Abhijeet; Ravankar, Ankit A; Kobayashi, Yukinori; Emaru, Takanori
2017-08-15
Hitchhiking is a means of transportation gained by asking other people for a (free) ride. We developed a multi-robot system which is the first of its kind to incorporate hitchhiking in robotics, and discuss its advantages. Our method allows the hitchhiker robot to skip redundant computations in navigation like path planning, localization, obstacle avoidance, and map update by completely relying on the driver robot. This allows the hitchhiker robot, which performs only visual servoing, to save computation while navigating on the common path with the driver robot. The driver robot, in the proposed system performs all the heavy computations in navigation and updates the hitchhiker about the current localized positions and new obstacle positions in the map. The proposed system is robust to recover from `driver-lost' scenario which occurs due to visual servoing failure. We demonstrate robot hitchhiking in real environments considering factors like service-time and task priority with different start and goal configurations of the driver and hitchhiker robots. We also discuss the admissible characteristics of the hitchhiker, when hitchhiking should be allowed and when not, through experimental results.
CONCRETE BLOCKS' ADVERSE EFFECTS ON INDOOR AIR AND RECOMMENDED SOLUTIONS
Air infiltration through highly permeable concrete blocks can allow entry of various serious indoor air pollutants. An easy approach to avoiding these pollutants is to select a less–air-permeable concrete block. Tests show that air permeability of concrete blocks can vary by a fa...
Statistical Sensor Fusion of a 9-DOF Mems Imu for Indoor Navigation
NASA Astrophysics Data System (ADS)
Chow, J. C. K.
2017-09-01
Sensor fusion of a MEMS IMU with a magnetometer is a popular system design, because such 9-DoF (degrees of freedom) systems are capable of achieving drift-free 3D orientation tracking. However, these systems are often vulnerable to ambient magnetic distortions and lack useful position information; in the absence of external position aiding (e.g. satellite/ultra-wideband positioning systems) the dead-reckoned position accuracy from a 9-DoF MEMS IMU deteriorates rapidly due to unmodelled errors. Positioning information is valuable in many satellite-denied geomatics applications (e.g. indoor navigation, location-based services, etc.). This paper proposes an improved 9-DoF IMU indoor pose tracking method using batch optimization. By adopting a robust in-situ user self-calibration approach to model the systematic errors of the accelerometer, gyroscope, and magnetometer simultaneously in a tightly-coupled post-processed least-squares framework, the accuracy of the estimated trajectory from a 9-DoF MEMS IMU can be improved. Through a combination of relative magnetic measurement updates and a robust weight function, the method is able to tolerate a high level of magnetic distortions. The proposed auto-calibration method was tested in-use under various heterogeneous magnetic field conditions to mimic a person walking with the sensor in their pocket, a person checking their phone, and a person walking with a smartwatch. In these experiments, the presented algorithm improved the in-situ dead-reckoning orientation accuracy by 79.8-89.5 % and the dead-reckoned positioning accuracy by 72.9-92.8 %, thus reducing the relative positioning error from metre-level to decimetre-level after ten seconds of integration, without making assumptions about the user's dynamics.
Autonomous Relative Navigation for Formation-Flying Satellites Using GPS
NASA Technical Reports Server (NTRS)
Gramling, Cheryl; Carpenter, J. Russell; Long, Anne; Kelbel, David; Lee, Taesul
2000-01-01
The Goddard Space Flight Center is currently developing advanced spacecraft systems to provide autonomous navigation and control of formation flyers. This paper discusses autonomous relative navigation performance for a formation of four eccentric, medium-altitude Earth-orbiting satellites using Global Positioning System (GPS) Standard Positioning Service (SPS) and "GPS-like " intersatellite measurements. The performance of several candidate relative navigation approaches is evaluated. These analyses indicate that an autonomous relative navigation position accuracy of 1meter root-mean-square can be achieved by differencing high-accuracy filtered solutions if only measurements from common GPS space vehicles are used in the independently estimated solutions.
The Application of Downdraught Cooling in Vernacular Skywell Dwellings in China
NASA Astrophysics Data System (ADS)
Xuan, H.; Lv, A. M.
2017-05-01
Traditional skywell dwellings in the hot climate regions of China represent an important cultural heritage. Achieving indoor comfort meeting occupants’ expectations, can contribute to the preservation of this unique traditional architecture. Improvement of ventilation and indoor temperatures through natural, sustainable and low impact solutions is an opportunity in achieving building thermal comfort in these traditional dwellings. The existence of skywells provides a good opportunity for the incorporation of downdraught cooling with minor interventions, and thus by avoiding extensive ductwork, saving energy and improving indoor temperatures, it can contribute to the preservation of traditional dwellings. Applicability of downdraught cooling, the history of traditional ventilation solutions, layout and space features of skywell dwelling are discussed and the way of incorporating downdraught cooling as an alternative to air-conditioning into these buildings is investigated.
Fusion of WiFi, smartphone sensors and landmarks using the Kalman filter for indoor localization.
Chen, Zhenghua; Zou, Han; Jiang, Hao; Zhu, Qingchang; Soh, Yeng Chai; Xie, Lihua
2015-01-05
Location-based services (LBS) have attracted a great deal of attention recently. Outdoor localization can be solved by the GPS technique, but how to accurately and efficiently localize pedestrians in indoor environments is still a challenging problem. Recent techniques based on WiFi or pedestrian dead reckoning (PDR) have several limiting problems, such as the variation of WiFi signals and the drift of PDR. An auxiliary tool for indoor localization is landmarks, which can be easily identified based on specific sensor patterns in the environment, and this will be exploited in our proposed approach. In this work, we propose a sensor fusion framework for combining WiFi, PDR and landmarks. Since the whole system is running on a smartphone, which is resource limited, we formulate the sensor fusion problem in a linear perspective, then a Kalman filter is applied instead of a particle filter, which is widely used in the literature. Furthermore, novel techniques to enhance the accuracy of individual approaches are adopted. In the experiments, an Android app is developed for real-time indoor localization and navigation. A comparison has been made between our proposed approach and individual approaches. The results show significant improvement using our proposed framework. Our proposed system can provide an average localization accuracy of 1 m.
Fusion of WiFi, Smartphone Sensors and Landmarks Using the Kalman Filter for Indoor Localization
Chen, Zhenghua; Zou, Han; Jiang, Hao; Zhu, Qingchang; Soh, Yeng Chai; Xie, Lihua
2015-01-01
Location-based services (LBS) have attracted a great deal of attention recently. Outdoor localization can be solved by the GPS technique, but how to accurately and efficiently localize pedestrians in indoor environments is still a challenging problem. Recent techniques based on WiFi or pedestrian dead reckoning (PDR) have several limiting problems, such as the variation of WiFi signals and the drift of PDR. An auxiliary tool for indoor localization is landmarks, which can be easily identified based on specific sensor patterns in the environment, and this will be exploited in our proposed approach. In this work, we propose a sensor fusion framework for combining WiFi, PDR and landmarks. Since the whole system is running on a smartphone, which is resource limited, we formulate the sensor fusion problem in a linear perspective, then a Kalman filter is applied instead of a particle filter, which is widely used in the literature. Furthermore, novel techniques to enhance the accuracy of individual approaches are adopted. In the experiments, an Android app is developed for real-time indoor localization and navigation. A comparison has been made between our proposed approach and individual approaches. The results show significant improvement using our proposed framework. Our proposed system can provide an average localization accuracy of 1 m. PMID:25569750
Liu, Zhijian; Cheng, Kewei; Li, Hao; Cao, Guoqing; Wu, Di; Shi, Yunjie
2018-02-01
Indoor airborne culturable fungi exposure has been closely linked to occupants' health. However, conventional measurement of indoor airborne fungal concentration is complicated and usually requires around one week for fungi incubation in laboratory. To provide an ultra-fast solution, here, for the first time, a knowledge-based machine learning model is developed with the inputs of indoor air quality data for estimating the concentration of indoor airborne culturable fungi. To construct a database for statistical analysis and model training, 249 data groups of air quality indicators (concentration of indoor airborne culturable fungi, indoor/outdoor PM 2.5 and PM 10 concentrations, indoor temperature, indoor relative humidity, and indoor CO 2 concentration) were measured from 85 residential buildings of Baoding (China) during the period of 2016.11.15-2017.03.15. Our results show that artificial neural network (ANN) with one hidden layer has good prediction performances, compared to a support vector machine (SVM). With the tolerance of ± 30%, the prediction accuracy of the ANN model with ten hidden nodes can at highest reach 83.33% in the testing set. Most importantly, we here provide a quick method for estimating the concentration of indoor airborne fungi that can be applied to real-time evaluation.
Indoor localization using pedestrian dead reckoning updated with RFID-based fiducials.
House, Samuel; Connell, Sean; Milligan, Ian; Austin, Daniel; Hayes, Tamara L; Chiang, Patrick
2011-01-01
We describe a low-cost wearable system that tracks the location of individuals indoors using commonly available inertial navigation sensors fused with radio frequency identification (RFID) tags placed around the smart environment. While conventional pedestrian dead reckoning (PDR) calculated with an inertial measurement unit (IMU) is susceptible to sensor drift inaccuracies, the proposed wearable prototype fuses the drift-sensitive IMU with a RFID tag reader. Passive RFID tags placed throughout the smart-building then act as fiducial markers that update the physical locations of each user, thereby correcting positional errors and sensor inaccuracy. Experimental measurements taken for a 55 m × 20 m 2D floor space indicate an over 1200% improvement in average error rate of the proposed RFID-fused system over dead reckoning alone.
Benchmarking real-time RGBD odometry for light-duty UAVs
NASA Astrophysics Data System (ADS)
Willis, Andrew R.; Sahawneh, Laith R.; Brink, Kevin M.
2016-06-01
This article describes the theoretical and implementation challenges associated with generating 3D odometry estimates (delta-pose) from RGBD sensor data in real-time to facilitate navigation in cluttered indoor environments. The underlying odometry algorithm applies to general 6DoF motion; however, the computational platforms, trajectories, and scene content are motivated by their intended use on indoor, light-duty UAVs. Discussion outlines the overall software pipeline for sensor processing and details how algorithm choices for the underlying feature detection and correspondence computation impact the real-time performance and accuracy of the estimated odometry and associated covariance. This article also explores the consistency of odometry covariance estimates and the correlation between successive odometry estimates. The analysis is intended to provide users information needed to better leverage RGBD odometry within the constraints of their systems.
Indoor 3D Route Modeling Based On Estate Spatial Data
NASA Astrophysics Data System (ADS)
Zhang, H.; Wen, Y.; Jiang, J.; Huang, W.
2014-04-01
Indoor three-dimensional route model is essential for space intelligence navigation and emergency evacuation. This paper is motivated by the need of constructing indoor route model automatically and as far as possible. By comparing existing building data sources, this paper firstly explained the reason why the estate spatial management data is chosen as the data source. Then, an applicable method of construction three-dimensional route model in a building is introduced by establishing the mapping relationship between geographic entities and their topological expression. This data model is a weighted graph consist of "node" and "path" to express the spatial relationship and topological structure of a building components. The whole process of modelling internal space of a building is addressed by two key steps: (1) each single floor route model is constructed, including path extraction of corridor using Delaunay triangulation algorithm with constrained edge, fusion of room nodes into the path; (2) the single floor route model is connected with stairs and elevators and the multi-floor route model is eventually generated. In order to validate the method in this paper, a shopping mall called "Longjiang New City Plaza" in Nanjing is chosen as a case of study. And the whole building space is constructed according to the modelling method above. By integrating of existing path finding algorithm, the usability of this modelling method is verified, which shows the indoor three-dimensional route modelling method based on estate spatial data in this paper can support indoor route planning and evacuation route design very well.
A Novel Real-Time Reference Key Frame Scan Matching Method.
Mohamed, Haytham; Moussa, Adel; Elhabiby, Mohamed; El-Sheimy, Naser; Sesay, Abu
2017-05-07
Unmanned aerial vehicles represent an effective technology for indoor search and rescue operations. Typically, most indoor missions' environments would be unknown, unstructured, and/or dynamic. Navigation of UAVs in such environments is addressed by simultaneous localization and mapping approach using either local or global approaches. Both approaches suffer from accumulated errors and high processing time due to the iterative nature of the scan matching method. Moreover, point-to-point scan matching is prone to outlier association processes. This paper proposes a low-cost novel method for 2D real-time scan matching based on a reference key frame (RKF). RKF is a hybrid scan matching technique comprised of feature-to-feature and point-to-point approaches. This algorithm aims at mitigating errors accumulation using the key frame technique, which is inspired from video streaming broadcast process. The algorithm depends on the iterative closest point algorithm during the lack of linear features which is typically exhibited in unstructured environments. The algorithm switches back to the RKF once linear features are detected. To validate and evaluate the algorithm, the mapping performance and time consumption are compared with various algorithms in static and dynamic environments. The performance of the algorithm exhibits promising navigational, mapping results and very short computational time, that indicates the potential use of the new algorithm with real-time systems.
Deng, Zhi-An; Wang, Guofeng; Hu, Ying; Cui, Yang
2016-01-01
This paper proposes a novel heading estimation approach for indoor pedestrian navigation using the built-in inertial sensors on a smartphone. Unlike previous approaches constraining the carrying position of a smartphone on the user’s body, our approach gives the user a larger freedom by implementing automatic recognition of the device carrying position and subsequent selection of an optimal strategy for heading estimation. We firstly predetermine the motion state by a decision tree using an accelerometer and a barometer. Then, to enable accurate and computational lightweight carrying position recognition, we combine a position classifier with a novel position transition detection algorithm, which may also be used to avoid the confusion between position transition and user turn during pedestrian walking. For a device placed in the trouser pockets or held in a swinging hand, the heading estimation is achieved by deploying a principal component analysis (PCA)-based approach. For a device held in the hand or against the ear during a phone call, user heading is directly estimated by adding the yaw angle of the device to the related heading offset. Experimental results show that our approach can automatically detect carrying positions with high accuracy, and outperforms previous heading estimation approaches in terms of accuracy and applicability. PMID:27187391
A Framework for Mining Actionable Navigation Patterns from In-Store RFID Datasets via Indoor Mapping
Shen, Bin; Zheng, Qiuhua; Li, Xingsen; Xu, Libo
2015-01-01
With the quick development of RFID technology and the decreasing prices of RFID devices, RFID is becoming widely used in various intelligent services. Especially in the retail application domain, RFID is increasingly adopted to capture the shopping tracks and behavior of in-store customers. To further enhance the potential of this promising application, in this paper, we propose a unified framework for RFID-based path analytics, which uses both in-store shopping paths and RFID-based purchasing data to mine actionable navigation patterns. Four modules of this framework are discussed, which are: (1) mapping from the physical space to the cyber space, (2) data preprocessing, (3) pattern mining and (4) knowledge understanding and utilization. In the data preprocessing module, the critical problem of how to capture the mainstream shopping path sequences while wiping out unnecessary redundant and repeated details is addressed in detail. To solve this problem, two types of redundant patterns, i.e., loop repeat pattern and palindrome-contained pattern are recognized and the corresponding processing algorithms are proposed. The experimental results show that the redundant pattern filtering functions are effective and scalable. Overall, this work builds a bridge between indoor positioning and advanced data mining technologies, and provides a feasible way to study customers’ shopping behaviors via multi-source RFID data. PMID:25751076
Hellmers, Hendrik; Kasmi, Zakaria; Norrdine, Abdelmoumen; Eichhorn, Andreas
2018-01-04
In recent years, a variety of real-time applications benefit from services provided by localization systems due to the advent of sensing and communication technologies. Since the Global Navigation Satellite System (GNSS) enables localization only outside buildings, applications for indoor positioning and navigation use alternative technologies. Ultra Wide Band Signals (UWB), Wireless Local Area Network (WLAN), ultrasonic or infrared are common examples. However, these technologies suffer from fading and multipath effects caused by objects and materials in the building. In contrast, magnetic fields are able to pass through obstacles without significant propagation errors, i.e. in Non-Line of Sight Scenarios (NLoS). The aim of this work is to propose a novel indoor positioning system based on artificially generated magnetic fields in combination with Inertial Measurement Units (IMUs). In order to reach a better coverage, multiple coils are used as reference points. A basic algorithm for three-dimensional applications is demonstrated as well as evaluated in this article. The established system is then realized by a sensor fusion principle as well as a kinematic motion model on the basis of a Kalman filter. Furthermore, a pressure sensor is used in combination with an adaptive filtering method to reliably estimate the platform's altitude.
Yi, Dong-Hoon; Lee, Tae-Jae; Cho, Dong-Il Dan
2015-05-13
This paper introduces a novel afocal optical flow sensor (OFS) system for odometry estimation in indoor robotic navigation. The OFS used in computer optical mouse has been adopted for mobile robots because it is not affected by wheel slippage. Vertical height variance is thought to be a dominant factor in systematic error when estimating moving distances in mobile robots driving on uneven surfaces. We propose an approach to mitigate this error by using an afocal (infinite effective focal length) system. We conducted experiments in a linear guide on carpet and three other materials with varying sensor heights from 30 to 50 mm and a moving distance of 80 cm. The same experiments were repeated 10 times. For the proposed afocal OFS module, a 1 mm change in sensor height induces a 0.1% systematic error; for comparison, the error for a conventional fixed-focal-length OFS module is 14.7%. Finally, the proposed afocal OFS module was installed on a mobile robot and tested 10 times on a carpet for distances of 1 m. The average distance estimation error and standard deviation are 0.02% and 17.6%, respectively, whereas those for a conventional OFS module are 4.09% and 25.7%, respectively.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fisk, William J.; Destaillats, H.; Apte, M.G.
Heating, ventilating, and cooling classrooms in California consume substantial electrical energy. Indoor air quality (IAQ) in classrooms affects studenthealth and performance. In addition to airborne pollutants that are emitted directly by indoor sources and those generated outdoors, secondary pollutants can be formed indoors by chemical reaction of ozone with other chemicals and materials. Filters are used in nearly all classroom heating, ventilation and air?conditioning (HVAC) systems to maintain energy-efficient HVAC performance and improve indoor air quality; however, recent evidence indicates that ozone reactions with filters may, in fact, be a source of secondary pollutants. This project quantitatively evaluated ozone depositionmore » in HVAC filters and byproduct formation, and provided a preliminary assessment of the extent towhich filter systems are degrading indoor air quality. The preliminary information obtained will contribute to the design of subsequent research efforts and the identification of energy efficient solutions that improve indoor air quality in classrooms and the health and performance of students.« less
Vision Based Navigation for Autonomous Cooperative Docking of CubeSats
NASA Astrophysics Data System (ADS)
Pirat, Camille; Ankersen, Finn; Walker, Roger; Gass, Volker
2018-05-01
A realistic rendezvous and docking navigation solution applicable to CubeSats is investigated. The scalability analysis of the ESA Autonomous Transfer Vehicle Guidance, Navigation & Control (GNC) performances and the Russian docking system, shows that the docking of two CubeSats would require a lateral control performance of the order of 1 cm. Line of sight constraints and multipath effects affecting Global Navigation Satellite System (GNSS) measurements in close proximity prevent the use of this sensor for the final approach. This consideration and the high control accuracy requirement led to the use of vision sensors for the final 10 m of the rendezvous and docking sequence. A single monocular camera on the chaser satellite and various sets of Light-Emitting Diodes (LEDs) on the target vehicle ensure the observability of the system throughout the approach trajectory. The simple and novel formulation of the measurement equations allows differentiating unambiguously rotations from translations between the target and chaser docking port and allows a navigation performance better than 1 mm at docking. Furthermore, the non-linear measurement equations can be solved in order to provide an analytic navigation solution. This solution can be used to monitor the navigation filter solution and ensure its stability, adding an extra layer of robustness for autonomous rendezvous and docking. The navigation filter initialization is addressed in detail. The proposed method is able to differentiate LEDs signals from Sun reflections as demonstrated by experimental data. The navigation filter uses a comprehensive linearised coupled rotation/translation dynamics, describing the chaser to target docking port motion. The handover, between GNSS and vision sensor measurements, is assessed. The performances of the navigation function along the approach trajectory is discussed.
Design and Implementation of a Smart Home System Using Multisensor Data Fusion Technology.
Hsu, Yu-Liang; Chou, Po-Huan; Chang, Hsing-Cheng; Lin, Shyan-Lung; Yang, Shih-Chin; Su, Heng-Yi; Chang, Chih-Chien; Cheng, Yuan-Sheng; Kuo, Yu-Chen
2017-07-15
This paper aims to develop a multisensor data fusion technology-based smart home system by integrating wearable intelligent technology, artificial intelligence, and sensor fusion technology. We have developed the following three systems to create an intelligent smart home environment: (1) a wearable motion sensing device to be placed on residents' wrists and its corresponding 3D gesture recognition algorithm to implement a convenient automated household appliance control system; (2) a wearable motion sensing device mounted on a resident's feet and its indoor positioning algorithm to realize an effective indoor pedestrian navigation system for smart energy management; (3) a multisensor circuit module and an intelligent fire detection and alarm algorithm to realize a home safety and fire detection system. In addition, an intelligent monitoring interface is developed to provide in real-time information about the smart home system, such as environmental temperatures, CO concentrations, communicative environmental alarms, household appliance status, human motion signals, and the results of gesture recognition and indoor positioning. Furthermore, an experimental testbed for validating the effectiveness and feasibility of the smart home system was built and verified experimentally. The results showed that the 3D gesture recognition algorithm could achieve recognition rates for automated household appliance control of 92.0%, 94.8%, 95.3%, and 87.7% by the 2-fold cross-validation, 5-fold cross-validation, 10-fold cross-validation, and leave-one-subject-out cross-validation strategies. For indoor positioning and smart energy management, the distance accuracy and positioning accuracy were around 0.22% and 3.36% of the total traveled distance in the indoor environment. For home safety and fire detection, the classification rate achieved 98.81% accuracy for determining the conditions of the indoor living environment.
Design and Implementation of a Smart Home System Using Multisensor Data Fusion Technology
Chou, Po-Huan; Chang, Hsing-Cheng; Lin, Shyan-Lung; Yang, Shih-Chin; Su, Heng-Yi; Chang, Chih-Chien; Cheng, Yuan-Sheng; Kuo, Yu-Chen
2017-01-01
This paper aims to develop a multisensor data fusion technology-based smart home system by integrating wearable intelligent technology, artificial intelligence, and sensor fusion technology. We have developed the following three systems to create an intelligent smart home environment: (1) a wearable motion sensing device to be placed on residents’ wrists and its corresponding 3D gesture recognition algorithm to implement a convenient automated household appliance control system; (2) a wearable motion sensing device mounted on a resident’s feet and its indoor positioning algorithm to realize an effective indoor pedestrian navigation system for smart energy management; (3) a multisensor circuit module and an intelligent fire detection and alarm algorithm to realize a home safety and fire detection system. In addition, an intelligent monitoring interface is developed to provide in real-time information about the smart home system, such as environmental temperatures, CO concentrations, communicative environmental alarms, household appliance status, human motion signals, and the results of gesture recognition and indoor positioning. Furthermore, an experimental testbed for validating the effectiveness and feasibility of the smart home system was built and verified experimentally. The results showed that the 3D gesture recognition algorithm could achieve recognition rates for automated household appliance control of 92.0%, 94.8%, 95.3%, and 87.7% by the 2-fold cross-validation, 5-fold cross-validation, 10-fold cross-validation, and leave-one-subject-out cross-validation strategies. For indoor positioning and smart energy management, the distance accuracy and positioning accuracy were around 0.22% and 3.36% of the total traveled distance in the indoor environment. For home safety and fire detection, the classification rate achieved 98.81% accuracy for determining the conditions of the indoor living environment. PMID:28714884
Moreira, Adriano; Lungenstrass, Tomás; Lu, Wei-Chung; Seco, Fernando; Nicolau, Maria João; Farina, Joaquín; Morales, Juan Pablo; Lu, Wen-Chen; Cheng, Ho-Ti; Yang, Shi-Shen
2018-01-01
The development of indoor positioning solutions using smartphones is a growing activity with an enormous potential for everyday life and professional applications. The research activities on this topic concentrate on the development of new positioning solutions that are tested in specific environments under their own evaluation metrics. To explore the real positioning quality of smartphone-based solutions and their capabilities for seamlessly adapting to different scenarios, it is needed to find fair evaluation frameworks. The design of competitions using extensive pre-recorded datasets is a valid way to generate open data for comparing the different solutions created by research teams. In this paper, we discuss the details of the 2017 IPIN indoor localization competition, the different datasets created, the teams participating in the event, and the results they obtained. We compare these results with other competition-based approaches (Microsoft and Perf-loc) and on-line evaluation web sites. The lessons learned by organising these competitions and the benefits for the community are addressed along the paper. Our analysis paves the way for future developments on the standardization of evaluations and for creating a widely-adopted benchmark strategy for researchers and companies in the field. PMID:29415508
Torres-Sospedra, Joaquín; Jiménez, Antonio R; Moreira, Adriano; Lungenstrass, Tomás; Lu, Wei-Chung; Knauth, Stefan; Mendoza-Silva, Germán Martín; Seco, Fernando; Pérez-Navarro, Antoni; Nicolau, Maria João; Costa, António; Meneses, Filipe; Farina, Joaquín; Morales, Juan Pablo; Lu, Wen-Chen; Cheng, Ho-Ti; Yang, Shi-Shen; Fang, Shih-Hau; Chien, Ying-Ren; Tsao, Yu
2018-02-06
The development of indoor positioning solutions using smartphones is a growing activity with an enormous potential for everyday life and professional applications. The research activities on this topic concentrate on the development of new positioning solutions that are tested in specific environments under their own evaluation metrics. To explore the real positioning quality of smartphone-based solutions and their capabilities for seamlessly adapting to different scenarios, it is needed to find fair evaluation frameworks. The design of competitions using extensive pre-recorded datasets is a valid way to generate open data for comparing the different solutions created by research teams. In this paper, we discuss the details of the 2017 IPIN indoor localization competition, the different datasets created, the teams participating in the event, and the results they obtained. We compare these results with other competition-based approaches (Microsoft and Perf-loc) and on-line evaluation web sites. The lessons learned by organising these competitions and the benefits for the community are addressed along the paper. Our analysis paves the way for future developments on the standardization of evaluations and for creating a widely-adopted benchmark strategy for researchers and companies in the field.
The use of modern technologies in carbon dioxide monitoring
NASA Astrophysics Data System (ADS)
Komínek, Petr; Weyr, Jan; Hirš, Jiří
2017-12-01
Indoor environment has huge influence on person's health and overall comfort. It is of great importance that we realize how essential indoor air quality is, considering we spend on average as much as 90% of our time indoors. There are many factors that affect indoor air quality: specifically, inside air temperature, relative humidity, and odors to name the most important factors. One of the key factors indicating indoor air quality is carbon dioxide (CO2) level. The CO2 levels, measured in prefab apartment buildings, indicates substantial indoor air quality issues. Therefore, a proper education of the occupants is of utmost importance. Also, great care should be directed towards technical and technological solutions that would ensure meeting the normative indoor environment criteria, especially indoor air CO2 levels. Thanks to the implementation of new emerging autonomous technologies, such as Internet of Things (IoT), monitoring in real-time is enhanced. An area where IoT plays a major role is in the monitoring of indoor environment. IoT technology (e.g. smart meters and sensors) provide awareness of information about the quality of indoor environment. There is a huge potential for influencing behaviour of the users. Through the web application, it is possible to educate people and ensure fresh air supply.
Tawk, Youssef; Tomé, Phillip; Botteron, Cyril; Stebler, Yannick; Farine, Pierre-André
2014-01-01
The use of global navigation satellite system receivers for navigation still presents many challenges in urban canyon and indoor environments, where satellite availability is typically reduced and received signals are attenuated. To improve the navigation performance in such environments, several enhancement methods can be implemented. For instance, external aid provided through coupling with other sensors has proven to contribute substantially to enhancing navigation performance and robustness. Within this context, coupling a very simple GPS receiver with an Inertial Navigation System (INS) based on low-cost micro-electro-mechanical systems (MEMS) inertial sensors is considered in this paper. In particular, we propose a GPS/INS Tightly Coupled Assisted PLL (TCAPLL) architecture, and present most of the associated challenges that need to be addressed when dealing with very-low-performance MEMS inertial sensors. In addition, we propose a data monitoring system in charge of checking the quality of the measurement flow in the architecture. The implementation of the TCAPLL is discussed in detail, and its performance under different scenarios is assessed. Finally, the architecture is evaluated through a test campaign using a vehicle that is driven in urban environments, with the purpose of highlighting the pros and cons of combining MEMS inertial sensors with GPS over GPS alone. PMID:24569773
NASA Technical Reports Server (NTRS)
Fitz-Coy, Norman; Liu, Ming-Cheng
1995-01-01
A two-phase proportional navigation scheme is developed for the case of two rigid bodies engaged in a rendezvous/docking maneuver. The target vehicle is nonmaneuvering, but does have constant nonzero angular and linear velocities. Under these conditions, it is shown that previously obtained solutions are not applicable. Analytical solutions are obtained leading to relationships between the transverse and LOS navigation constants. It is shown that the transverse navigation constant for the second phase of the maneuver must be 2. Also, initial conditions necessary for rendezvous are presented.
Integration of a Star Tracker and Inertial Sensors Using an Attitude Update
2014-09-18
and civilian applications because of its precision navigation capability. Unfortunately, GPS is not available in all environments (e.g., indoors...under sea, underground, or jamming environment ). The motivation of this research is to address the limitations of GPS by using star trackers as an...from him. In addition, I thank my thesis committee members, Dr. Meir Pachter and Dr. Kyle Kauffman for their teachings throughout my courses and
FPGA-based real-time embedded system for RISS/GPS integrated navigation.
Abdelfatah, Walid Farid; Georgy, Jacques; Iqbal, Umar; Noureldin, Aboelmagd
2012-01-01
Navigation algorithms integrating measurements from multi-sensor systems overcome the problems that arise from using GPS navigation systems in standalone mode. Algorithms which integrate the data from 2D low-cost reduced inertial sensor system (RISS), consisting of a gyroscope and an odometer or wheel encoders, along with a GPS receiver via a Kalman filter has proved to be worthy in providing a consistent and more reliable navigation solution compared to standalone GPS receivers. It has been also shown to be beneficial, especially in GPS-denied environments such as urban canyons and tunnels. The main objective of this paper is to narrow the idea-to-implementation gap that follows the algorithm development by realizing a low-cost real-time embedded navigation system capable of computing the data-fused positioning solution. The role of the developed system is to synchronize the measurements from the three sensors, relative to the pulse per second signal generated from the GPS, after which the navigation algorithm is applied to the synchronized measurements to compute the navigation solution in real-time. Employing a customizable soft-core processor on an FPGA in the kernel of the navigation system, provided the flexibility for communicating with the various sensors and the computation capability required by the Kalman filter integration algorithm.
FPGA-Based Real-Time Embedded System for RISS/GPS Integrated Navigation
Abdelfatah, Walid Farid; Georgy, Jacques; Iqbal, Umar; Noureldin, Aboelmagd
2012-01-01
Navigation algorithms integrating measurements from multi-sensor systems overcome the problems that arise from using GPS navigation systems in standalone mode. Algorithms which integrate the data from 2D low-cost reduced inertial sensor system (RISS), consisting of a gyroscope and an odometer or wheel encoders, along with a GPS receiver via a Kalman filter has proved to be worthy in providing a consistent and more reliable navigation solution compared to standalone GPS receivers. It has been also shown to be beneficial, especially in GPS-denied environments such as urban canyons and tunnels. The main objective of this paper is to narrow the idea-to-implementation gap that follows the algorithm development by realizing a low-cost real-time embedded navigation system capable of computing the data-fused positioning solution. The role of the developed system is to synchronize the measurements from the three sensors, relative to the pulse per second signal generated from the GPS, after which the navigation algorithm is applied to the synchronized measurements to compute the navigation solution in real-time. Employing a customizable soft-core processor on an FPGA in the kernel of the navigation system, provided the flexibility for communicating with the various sensors and the computation capability required by the Kalman filter integration algorithm. PMID:22368460
Open-Loop Flight Testing of COBALT GN&C Technologies for Precise Soft Landing
NASA Technical Reports Server (NTRS)
Carson, John M., III; Amzajerdian, Farzin; Seubert, Carl R.; Restrepo, Carolina I.
2017-01-01
A terrestrial, open-loop (OL) flight test campaign of the NASA COBALT (CoOperative Blending of Autonomous Landing Technologies) platform was conducted onboard the Masten Xodiac suborbital rocket testbed, with support through the NASA Advanced Exploration Systems (AES), Game Changing Development (GCD), and Flight Opportunities (FO) Programs. The COBALT platform integrates NASA Guidance, Navigation and Control (GN&C) sensing technologies for autonomous, precise soft landing, including the Navigation Doppler Lidar (NDL) velocity and range sensor and the Lander Vision System (LVS) Terrain Relative Navigation (TRN) system. A specialized navigation filter running onboard COBALT fuzes the NDL and LVS data in real time to produce a precise navigation solution that is independent of the Global Positioning System (GPS) and suitable for future, autonomous planetary landing systems. The OL campaign tested COBALT as a passive payload, with COBALT data collection and filter execution, but with the Xodiac vehicle Guidance and Control (G&C) loops closed on a Masten GPS-based navigation solution. The OL test was performed as a risk reduction activity in preparation for an upcoming 2017 closed-loop (CL) flight campaign in which Xodiac G&C will act on the COBALT navigation solution and the GPS-based navigation will serve only as a backup monitor.
Indoor localization using magnetic fields
NASA Astrophysics Data System (ADS)
Pathapati Subbu, Kalyan Sasidhar
Indoor localization consists of locating oneself inside new buildings. GPS does not work indoors due to multipath reflection and signal blockage. WiFi based systems assume ubiquitous availability and infrastructure based systems require expensive installations, hence making indoor localization an open problem. This dissertation consists of solving the problem of indoor localization by thoroughly exploiting the indoor ambient magnetic fields comprising mainly of disturbances termed as anomalies in the Earth's magnetic field caused by pillars, doors and elevators in hallways which are ferromagnetic in nature. By observing uniqueness in magnetic signatures collected from different campus buildings, the work presents the identification of landmarks and guideposts from these signatures and further develops magnetic maps of buildings - all of which can be used to locate and navigate people indoors. To understand the reason behind these anomalies, first a comparison between the measured and model generated Earth's magnetic field is made, verifying the presence of a constant field without any disturbances. Then by modeling the magnetic field behavior of different pillars such as steel reinforced concrete, solid steel, and other structures like doors and elevators, the interaction of the Earth's field with the ferromagnetic fields is described thereby explaining the causes of the uniqueness in the signatures that comprise these disturbances. Next, by employing the dynamic time warping algorithm to account for time differences in signatures obtained from users walking at different speeds, an indoor localization application capable of classifying locations using the magnetic signatures is developed solely on the smart phone. The application required users to walk short distances of 3-6 m anywhere in hallway to be located with accuracies of 80-99%. The classification framework was further validated with over 90% accuracies using model generated magnetic signatures representing hallways with different kinds of pillars, doors and elevators. All in all, this dissertation contributes the following: 1) provides a framework for understanding the presence of ambient magnetic fields indoors and utilizing them to solve the indoor localization problem; 2) develops an application that is independent of the user and the smart phones and 3) requires no other infrastructure since it is deployed on a device that encapsulates the sensing, computing and inferring functionalities, thereby making it a novel contribution to the mobile and pervasive computing domain.
Challenges and issues of geolocation in clinical environment.
Issom, David-Zacharie; Hagry, Claire; Wodia Mendo, Laetitia; Seng, Henry; Ehrler, Frederic; Lovis, Christian
2012-01-01
Reaching a good indoor geolocation without deploying extensive and expensive infrastructure is a challenge, because satellite positioning system is not available indoors. Geolocation could be of major use in healthcare facilities; to help care providers, visitors and patients to navigate, to improve movements and flows efficiency or to implement location-awareness systems. A system able to provide the location of a person in a hospital requires precision, multi-floors and obstacles management and should also perform in basements and outdoors. Such system needs also to be insensitive to environmental variations occurring in a hospital. These changes may be various kinds of obstacles. These can be the displacement of metallic objects, metallic machines, strong magnetic fields or simply human displacement. A system conforming to the above requirements can also answer various security questions, operational workflow management but also assist movement of people.
D Topological Indoor Building Modeling Integrated with Open Street Map
NASA Astrophysics Data System (ADS)
Jamali, A.; Rahman, A. Abdul; Boguslawski, P.
2016-09-01
Considering various fields of applications for building surveying and various demands, geometry representation of a building is the most crucial aspect of a building survey. The interiors of the buildings need to be described along with the relative locations of the rooms, corridors, doors and exits in many kinds of emergency response, such as fire, bombs, smoke, and pollution. Topological representation is a challenging task within the Geography Information Science (GIS) environment, as the data structures required to express these relationships are particularly difficult to develop. Even within the Computer Aided Design (CAD) community, the structures for expressing the relationships between adjacent building parts are complex and often incomplete. In this paper, an integration of 3D topological indoor building modeling in Dual Half Edge (DHE) data structure and outdoor navigation network from Open Street Map (OSM) is presented.
Kohoutek, Tobias K.; Mautz, Rainer; Wegner, Jan D.
2013-01-01
We present a novel approach for autonomous location estimation and navigation in indoor environments using range images and prior scene knowledge from a GIS database (CityGML). What makes this task challenging is the arbitrary relative spatial relation between GIS and Time-of-Flight (ToF) range camera further complicated by a markerless configuration. We propose to estimate the camera's pose solely based on matching of GIS objects and their detected location in image sequences. We develop a coarse-to-fine matching strategy that is able to match point clouds without any initial parameters. Experiments with a state-of-the-art ToF point cloud show that our proposed method delivers an absolute camera position with decimeter accuracy, which is sufficient for many real-world applications (e.g., collision avoidance). PMID:23435055
Real-time locating systems (RTLS) in healthcare: a condensed primer
2012-01-01
Real-time locating systems (RTLS, also known as real-time location systems) have become an important component of many existing ubiquitous location aware systems. While GPS (global positioning system) has been quite successful as an outdoor real-time locating solution, it fails to repeat this success indoors. A number of RTLS technologies have been used to solve indoor tracking problems. The ability to accurately track the location of assets and individuals indoors has many applications in healthcare. This paper provides a condensed primer of RTLS in healthcare, briefly covering the many options and technologies that are involved, as well as the various possible applications of RTLS in healthcare facilities and their potential benefits, including capital expenditure reduction and workflow and patient throughput improvements. The key to a successful RTLS deployment lies in picking the right RTLS option(s) and solution(s) for the application(s) or problem(s) at hand. Where this application-technology match has not been carefully thought of, any technology will be doomed to failure or to achieving less than optimal results. PMID:22741760
Real-time locating systems (RTLS) in healthcare: a condensed primer.
Kamel Boulos, Maged N; Berry, Geoff
2012-06-28
Real-time locating systems (RTLS, also known as real-time location systems) have become an important component of many existing ubiquitous location aware systems. While GPS (global positioning system) has been quite successful as an outdoor real-time locating solution, it fails to repeat this success indoors. A number of RTLS technologies have been used to solve indoor tracking problems. The ability to accurately track the location of assets and individuals indoors has many applications in healthcare. This paper provides a condensed primer of RTLS in healthcare, briefly covering the many options and technologies that are involved, as well as the various possible applications of RTLS in healthcare facilities and their potential benefits, including capital expenditure reduction and workflow and patient throughput improvements. The key to a successful RTLS deployment lies in picking the right RTLS option(s) and solution(s) for the application(s) or problem(s) at hand. Where this application-technology match has not been carefully thought of, any technology will be doomed to failure or to achieving less than optimal results.
NASA Astrophysics Data System (ADS)
Nagel, Markus; Hoheisel, Martin; Petzold, Ralf; Kalender, Willi A.; Krause, Ulrich H. W.
2007-03-01
Integrated solutions for navigation systems with CT, MR or US systems become more and more popular for medical products. Such solutions improve the medical workflow, reduce hardware, space and costs requirements. The purpose of our project was to develop a new electromagnetic navigation system for interventional radiology which is integrated into C-arm CT systems. The application is focused on minimally invasive percutaneous interventions performed under local anaesthesia. Together with a vacuum-based patient immobilization device and newly developed navigation tools (needles, panels) we developed a safe and fully automatic navigation system. The radiologist can directly start with navigated interventions after loading images without any prior user interaction. The complete system is adapted to the requirements of the radiologist and to the clinical workflow. For evaluation of the navigation system we performed different phantom studies and achieved an average accuracy of better than 2.0 mm.
Indoor Map Aided Wi-Fi Integrated Lbs on Smartphone Platforms
NASA Astrophysics Data System (ADS)
Yu, C.; El-Sheimy, N.
2017-09-01
In this research, an indoor map aided INS/Wi-Fi integrated location based services (LBS) applications is proposed and implemented on smartphone platforms. Indoor map information together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value from Wi-Fi are collected to obtain an accurate, continuous, and low-cost position solution. The main challenge of this research is to make effective use of various measurements that complement each other without increasing the computational burden of the system. The integrated system in this paper includes three modules: INS, Wi-Fi (if signal available) and indoor maps. A cascade structure Particle/Kalman filter framework is applied to combine the different modules. Firstly, INS position and Wi-Fi fingerprint position integrated through Kalman filter for estimating positioning information. Then, indoor map information is applied to correct the error of INS/Wi-Fi estimated position through particle filter. Indoor tests show that the proposed method can effectively reduce the accumulation positioning errors of stand-alone INS systems, and provide stable, continuous and reliable indoor location service.
Does RAIM with Correct Exclusion Produce Unbiased Positions?
Teunissen, Peter J. G.; Imparato, Davide; Tiberius, Christian C. J. M.
2017-01-01
As the navigation solution of exclusion-based RAIM follows from a combination of least-squares estimation and a statistically based exclusion-process, the computation of the integrity of the navigation solution has to take the propagated uncertainty of the combined estimation-testing procedure into account. In this contribution, we analyse, theoretically as well as empirically, the effect that this combination has on the first statistical moment, i.e., the mean, of the computed navigation solution. It will be shown, although statistical testing is intended to remove biases from the data, that biases will always remain under the alternative hypothesis, even when the correct alternative hypothesis is properly identified. The a posteriori exclusion of a biased satellite range from the position solution will therefore never remove the bias in the position solution completely. PMID:28672862
Indoor Modelling from Slam-Based Laser Scanner: Door Detection to Envelope Reconstruction
NASA Astrophysics Data System (ADS)
Díaz-Vilariño, L.; Verbree, E.; Zlatanova, S.; Diakité, A.
2017-09-01
Updated and detailed indoor models are being increasingly demanded for various applications such as emergency management or navigational assistance. The consolidation of new portable and mobile acquisition systems has led to a higher availability of 3D point cloud data from indoors. In this work, we explore the combined use of point clouds and trajectories from SLAM-based laser scanner to automate the reconstruction of building indoors. The methodology starts by door detection, since doors represent transitions from one indoor space to other, which constitutes an initial approach about the global configuration of the point cloud into building rooms. For this purpose, the trajectory is used to create a vertical point cloud profile in which doors are detected as local minimum of vertical distances. As point cloud and trajectory are related by time stamp, this feature is used to subdivide the point cloud into subspaces according to the location of the doors. The correspondence between subspaces and building rooms is not unambiguous. One subspace always corresponds to one room, but one room is not necessarily depicted by just one subspace, for example, in case of a room containing several doors and in which the acquisition is performed in a discontinue way. The labelling problem is formulated as combinatorial approach solved as a minimum energy optimization. Once the point cloud is subdivided into building rooms, envelop (conformed by walls, ceilings and floors) is reconstructed for each space. The connectivity between spaces is included by adding the previously detected doors to the reconstructed model. The methodology is tested in a real case study.
Teaching the blind to find their way by playing video games.
Merabet, Lotfi B; Connors, Erin C; Halko, Mark A; Sánchez, Jaime
2012-01-01
Computer based video games are receiving great interest as a means to learn and acquire new skills. As a novel approach to teaching navigation skills in the blind, we have developed Audio-based Environment Simulator (AbES); a virtual reality environment set within the context of a video game metaphor. Despite the fact that participants were naïve to the overall purpose of the software, we found that early blind users were able to acquire relevant information regarding the spatial layout of a previously unfamiliar building using audio based cues alone. This was confirmed by a series of behavioral performance tests designed to assess the transfer of acquired spatial information to a large-scale, real-world indoor navigation task. Furthermore, learning the spatial layout through a goal directed gaming strategy allowed for the mental manipulation of spatial information as evidenced by enhanced navigation performance when compared to an explicit route learning strategy. We conclude that the immersive and highly interactive nature of the software greatly engages the blind user to actively explore the virtual environment. This in turn generates an accurate sense of a large-scale three-dimensional space and facilitates the learning and transfer of navigation skills to the physical world.
NASA Astrophysics Data System (ADS)
Markov, Detelin
2012-11-01
This paper presents an easy-to-understand procedure for prediction of indoor air composition time variation in air-tight occupied spaces during the night periods. The mathematical model is based on the assumptions for homogeneity and perfect mixing of the indoor air, the ideal gas model for non-reacting gas mixtures, mass conservation equations for the entire system and for each species, a model for prediction of basal metabolic rate of humans as well as a model for prediction of O2 consumption rate and both CO2 and H2O generation rates by breathing. Time variation of indoor air composition is predicted at constant indoor air temperature for three scenarios based on the analytical solution of the mathematical model. The results achieved reveal both the most probable scenario for indoor air time variation in air-tight occupied spaces as well as the cause for morning tiredness after having a sleep in a modern energy efficient space.
NASA Astrophysics Data System (ADS)
Er, C. M.; Sunar, N. M.; Leman, A. M.; Khalid, A.; Ali, R.; Zaidi, E.; Azhar, A. T. S.
2018-04-01
Surface-growing indoor and outdoor fungi were assessed using swabbing method to investigate the indoor contamination. The painted wall surface samples were collected from two institutional buildings (B1 and B2) of a university in southern Peninsular Malaysia; indoors and outdoors. The mould concentrations varied widely between indoor and outdoor surface samples of both buildings. The total indoor surface-growing mould concentration (8776.49 CFU/cm2) is significantly higher (p<0.05) than the total concentration of outdoor surface growing mould (209.91 CFU/cm2). Respectively, the mean concentration of indoor surface-growing mould (18920.13 CFU/cm2 for B1 and 3704.67 CFU/cm2 for B2) is significantly higher than their outdoor counterparts (99.95 CFU/cm2 for b1 and for 319.86 CFU/cm2 b2) at these buildings. Besides, various air quality parameters (relative humidity, temperature and air velocity) were also measured indoors and outdoors during the study and violation of the guideline provided by ICOP-IAQ 2010 were proven in indoor environment in both buildings. The results of this assessment showed that the indoor environments of both institutional buildings were contaminated by the surface-growing mould. It also suggested the faulty designs and/or usages of building material in these institutional buildings contributed toward the contamination. An innovative solution is needed to correct the problems.
NASA Astrophysics Data System (ADS)
Hanford, Scott D.
Most unmanned vehicles used for civilian and military applications are remotely operated or are designed for specific applications. As these vehicles are used to perform more difficult missions or a larger number of missions in remote environments, there will be a great need for these vehicles to behave intelligently and autonomously. Cognitive architectures, computer programs that define mechanisms that are important for modeling and generating domain-independent intelligent behavior, have the potential for generating intelligent and autonomous behavior in unmanned vehicles. The research described in this presentation explored the use of the Soar cognitive architecture for cognitive robotics. The Cognitive Robotic System (CRS) has been developed to integrate software systems for motor control and sensor processing with Soar for unmanned vehicle control. The CRS has been tested using two mobile robot missions: outdoor navigation and search in an indoor environment. The use of the CRS for the outdoor navigation mission demonstrated that a Soar agent could autonomously navigate to a specified location while avoiding obstacles, including cul-de-sacs, with only a minimal amount of knowledge about the environment. While most systems use information from maps or long-range perceptual capabilities to avoid cul-de-sacs, a Soar agent in the CRS was able to recognize when a simple approach to avoiding obstacles was unsuccessful and switch to a different strategy for avoiding complex obstacles. During the indoor search mission, the CRS autonomously and intelligently searches a building for an object of interest and common intersection types. While searching the building, the Soar agent builds a topological map of the environment using information about the intersections the CRS detects. The agent uses this topological model (along with Soar's reasoning, planning, and learning mechanisms) to make intelligent decisions about how to effectively search the building. Once the object of interest has been detected, the Soar agent uses the topological map to make decisions about how to efficiently return to the location where the mission began. Additionally, the CRS can send an email containing step-by-step directions using the intersections in the environment as landmarks that describe a direct path from the mission's start location to the object of interest. The CRS has displayed several characteristics of intelligent behavior, including reasoning, planning, learning, and communication of learned knowledge, while autonomously performing two missions. The CRS has also demonstrated how Soar can be integrated with common robotic motor and perceptual systems that complement the strengths of Soar for unmanned vehicles and is one of the few systems that use perceptual systems such as occupancy grid, computer vision, and fuzzy logic algorithms with cognitive architectures for robotics. The use of these perceptual systems to generate symbolic information about the environment during the indoor search mission allowed the CRS to use Soar's planning and learning mechanisms, which have rarely been used by agents to control mobile robots in real environments. Additionally, the system developed for the indoor search mission represents the first known use of a topological map with a cognitive architecture on a mobile robot. The ability to learn both a topological map and production rules allowed the Soar agent used during the indoor search mission to make intelligent decisions and behave more efficiently as it learned about its environment. While the CRS has been applied to two different missions, it has been developed with the intention that it be extended in the future so it can be used as a general system for mobile robot control. The CRS can be expanded through the addition of new sensors and sensor processing algorithms, development of Soar agents with more production rules, and the use of new architectural mechanisms in Soar.
Sex differences in navigation strategy and efficiency.
Boone, Alexander P; Gong, Xinyi; Hegarty, Mary
2018-05-22
Research on human navigation has indicated that males and females differ in self-reported navigation strategy as well as objective measures of navigation efficiency. In two experiments, we investigated sex differences in navigation strategy and efficiency using an objective measure of strategy, the dual-solution paradigm (DSP; Marchette, Bakker, & Shelton, 2011). Although navigation by shortcuts and learned routes were the primary strategies used in both experiments, as in previous research on the DSP, individuals also utilized route reversals and sometimes found the goal location as a result of wandering. Importantly, sex differences were found in measures of both route selection and navigation efficiency. In particular, males were more likely to take shortcuts and reached their goal location faster than females, while females were more likely to follow learned routes and wander. Self-report measures of strategy were only weakly correlated with objective measures of strategy, casting doubt on their usefulness. This research indicates that the sex difference in navigation efficiency is large, and only partially related to an individual's navigation strategy as measured by the dual-solution paradigm.
Visual Tour Based on Panaromic Images for Indoor Places in Campus
NASA Astrophysics Data System (ADS)
Bakirman, T.
2012-07-01
In this paper, it is aimed to create a visual tour based on panoramic images for Civil Engineering Faculty in Yildiz Technical University. For this purpose, panoramic images should be obtained. Thus, photos taken with a tripod to have the same angle of view in every photo and panoramic images were created with stitching photos. Two different cameras with different focal length were used. With the panoramic images, visual tour with navigation tools created.
Programmable near-infrared ranging system
Everett, Jr., Hobart R.
1989-01-01
A high angular resolution ranging system particularly suitable for indoor plications involving mobile robot navigation and collision avoidance uses a programmable array of light emitters that can be sequentially incremented by a microprocessor. A plurality of adjustable level threshold detectors are used in an optical receiver for detecting the threshold level of the light echoes produced when light emitted from one or more of the emitters is reflected by a target or object in the scan path of the ranging system.
A Novel Real-Time Reference Key Frame Scan Matching Method
Mohamed, Haytham; Moussa, Adel; Elhabiby, Mohamed; El-Sheimy, Naser; Sesay, Abu
2017-01-01
Unmanned aerial vehicles represent an effective technology for indoor search and rescue operations. Typically, most indoor missions’ environments would be unknown, unstructured, and/or dynamic. Navigation of UAVs in such environments is addressed by simultaneous localization and mapping approach using either local or global approaches. Both approaches suffer from accumulated errors and high processing time due to the iterative nature of the scan matching method. Moreover, point-to-point scan matching is prone to outlier association processes. This paper proposes a low-cost novel method for 2D real-time scan matching based on a reference key frame (RKF). RKF is a hybrid scan matching technique comprised of feature-to-feature and point-to-point approaches. This algorithm aims at mitigating errors accumulation using the key frame technique, which is inspired from video streaming broadcast process. The algorithm depends on the iterative closest point algorithm during the lack of linear features which is typically exhibited in unstructured environments. The algorithm switches back to the RKF once linear features are detected. To validate and evaluate the algorithm, the mapping performance and time consumption are compared with various algorithms in static and dynamic environments. The performance of the algorithm exhibits promising navigational, mapping results and very short computational time, that indicates the potential use of the new algorithm with real-time systems. PMID:28481285
Indoor radon problem in energy efficient multi-storey buildings.
Yarmoshenko, I V; Vasilyev, A V; Onishchenko, A D; Kiselev, S M; Zhukovsky, M V
2014-07-01
Modern energy-efficient architectural solutions and building construction technologies such as monolithic concrete structures in combination with effective insulation reduce air permeability of building envelope. As a result, air exchange rate is significantly reduced and conditions for increased radon accumulation in indoor air are created. Based on radon survey in Ekaterinburg, Russia, remarkable increase in indoor radon concentration level in energy-efficient multi-storey buildings was found in comparison with similar buildings constructed before the-energy-saving era. To investigate the problem of indoor radon in energy-efficient multi-storey buildings, the measurements of radon concentration have been performed in seven modern buildings using radon monitoring method. Values of air exchange rate and other parameters of indoor climate in energy-efficient buildings have been estimated. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Gravity Gradiometry and Map Matching: An Aid to Aircraft Inertial Navigation Systems
2010-03-01
improve its performance. In all of these cases, because information from two or more different navigation systems feeds into a navigation solution...GRAVITY GRADIOMETRY AND MAP MATCHING: AN AID TO AIRCRAFT INERTIAL NAVIGATION SYSTEMS THESIS...M06 GRAVITY GRADIOMETRY AND MAP MATCHING: AN AID TO AIRCRAFT INERTIAL NAVIGATION SYSTEMS THESIS Presented to the Faculty Department of
Real-time synthetic vision cockpit display for general aviation
NASA Astrophysics Data System (ADS)
Hansen, Andrew J.; Smith, W. Garth; Rybacki, Richard M.
1999-07-01
Low cost, high performance graphics solutions based on PC hardware platforms are now capable of rendering synthetic vision of a pilot's out-the-window view during all phases of flight. When coupled to a GPS navigation payload the virtual image can be fully correlated to the physical world. In particular, differential GPS services such as the Wide Area Augmentation System WAAS will provide all aviation users with highly accurate 3D navigation. As well, short baseline GPS attitude systems are becoming a viable and inexpensive solution. A glass cockpit display rendering geographically specific imagery draped terrain in real-time can be coupled with high accuracy (7m 95% positioning, sub degree pointing), high integrity (99.99999% position error bound) differential GPS navigation/attitude solutions to provide both situational awareness and 3D guidance to (auto) pilots throughout en route, terminal area, and precision approach phases of flight. This paper describes the technical issues addressed when coupling GPS and glass cockpit displays including the navigation/display interface, real-time 60 Hz rendering of terrain with multiple levels of detail under demand paging, and construction of verified terrain databases draped with geographically specific satellite imagery. Further, on-board recordings of the navigation solution and the cockpit display provide a replay facility for post-flight simulation based on live landings as well as synchronized multiple display channels with different views from the same flight. PC-based solutions which integrate GPS navigation and attitude determination with 3D visualization provide the aviation community, and general aviation in particular, with low cost high performance guidance and situational awareness in all phases of flight.
Integration of Cold Atom Interferometry INS with Other Sensors
2012-03-22
Kalman filtering 2.6.1 Linear Kalman filtering . Kalman filtering is used to estimate the solution to a linear... Kalman Filter . This filter will estimate the errors in the navigation grade measurement. Whenever an outage occurs the mechanization must be done using ...navigation solution, with periodic GPS measurements being brought into a Kalman Filter to estimate the errors in the INS solution. The results of
An INS/WiFi Indoor Localization System Based on the Weighted Least Squares.
Chen, Jian; Ou, Gang; Peng, Ao; Zheng, Lingxiang; Shi, Jianghong
2018-05-07
For smartphone indoor localization, an INS/WiFi hybrid localization system is proposed in this paper. Acceleration and angular velocity are used to estimate step lengths and headings. The problem with INS is that positioning errors grow with time. Using radio signal strength as a fingerprint is a widely used technology. The main problem with fingerprint matching is mismatching due to noise. Taking into account the different shortcomings and advantages, inertial sensors and WiFi from smartphones are integrated into indoor positioning. For a hybrid localization system, pre-processing techniques are used to enhance the WiFi signal quality. An inertial navigation system limits the range of WiFi matching. A Multi-dimensional Dynamic Time Warping (MDTW) is proposed to calculate the distance between the measured signals and the fingerprint in the database. A MDTW-based weighted least squares (WLS) is proposed for fusing multiple fingerprint localization results to improve positioning accuracy and robustness. Using four modes (calling, dangling, handheld and pocket), we carried out walking experiments in a corridor, a study room and a library stack room. Experimental results show that average localization accuracy for the hybrid system is about 2.03 m.
An INS/WiFi Indoor Localization System Based on the Weighted Least Squares
Chen, Jian; Ou, Gang; Zheng, Lingxiang; Shi, Jianghong
2018-01-01
For smartphone indoor localization, an INS/WiFi hybrid localization system is proposed in this paper. Acceleration and angular velocity are used to estimate step lengths and headings. The problem with INS is that positioning errors grow with time. Using radio signal strength as a fingerprint is a widely used technology. The main problem with fingerprint matching is mismatching due to noise. Taking into account the different shortcomings and advantages, inertial sensors and WiFi from smartphones are integrated into indoor positioning. For a hybrid localization system, pre-processing techniques are used to enhance the WiFi signal quality. An inertial navigation system limits the range of WiFi matching. A Multi-dimensional Dynamic Time Warping (MDTW) is proposed to calculate the distance between the measured signals and the fingerprint in the database. A MDTW-based weighted least squares (WLS) is proposed for fusing multiple fingerprint localization results to improve positioning accuracy and robustness. Using four modes (calling, dangling, handheld and pocket), we carried out walking experiments in a corridor, a study room and a library stack room. Experimental results show that average localization accuracy for the hybrid system is about 2.03 m. PMID:29735960
3D indoor modeling using a hand-held embedded system with multiple laser range scanners
NASA Astrophysics Data System (ADS)
Hu, Shaoxing; Wang, Duhu; Xu, Shike
2016-10-01
Accurate three-dimensional perception is a key technology for many engineering applications, including mobile mapping, obstacle detection and virtual reality. In this article, we present a hand-held embedded system designed for constructing 3D representation of structured indoor environments. Different from traditional vehicle-borne mobile mapping methods, the system presented here is capable of efficiently acquiring 3D data while an operator carrying the device traverses through the site. It consists of a simultaneous localization and mapping(SLAM) module, a 3D attitude estimate module and a point cloud processing module. The SLAM is based on a scan matching approach using a modern LIDAR system, and the 3D attitude estimate is generated by a navigation filter using inertial sensors. The hardware comprises three 2D time-flight laser range finders and an inertial measurement unit(IMU). All the sensors are rigidly mounted on a body frame. The algorithms are developed on the frame of robot operating system(ROS). The 3D model is constructed using the point cloud library(PCL). Multiple datasets have shown robust performance of the presented system in indoor scenarios.
Analysis of Sources of Large Positioning Errors in Deterministic Fingerprinting
2017-01-01
Wi-Fi fingerprinting is widely used for indoor positioning and indoor navigation due to the ubiquity of wireless networks, high proliferation of Wi-Fi-enabled mobile devices, and its reasonable positioning accuracy. The assumption is that the position can be estimated based on the received signal strength intensity from multiple wireless access points at a given point. The positioning accuracy, within a few meters, enables the use of Wi-Fi fingerprinting in many different applications. However, it has been detected that the positioning error might be very large in a few cases, which might prevent its use in applications with high accuracy positioning requirements. Hybrid methods are the new trend in indoor positioning since they benefit from multiple diverse technologies (Wi-Fi, Bluetooth, and Inertial Sensors, among many others) and, therefore, they can provide a more robust positioning accuracy. In order to have an optimal combination of technologies, it is crucial to identify when large errors occur and prevent the use of extremely bad positioning estimations in hybrid algorithms. This paper investigates why large positioning errors occur in Wi-Fi fingerprinting and how to detect them by using the received signal strength intensities. PMID:29186921
Door recognition in cluttered building interiors using imagery and lidar data
NASA Astrophysics Data System (ADS)
Díaz-Vilariño, L.; Martínez-Sánchez, J.; Lagüela, S.; Armesto, J.; Khoshelham, K.
2014-06-01
Building indoors reconstruction is an active research topic due to the importance of the wide range of applications to which they can be subjected, from architecture and furniture design, to movies and video games editing, or even crime scene investigation. Among the constructive elements defining the inside of a building, doors are important entities in applications like routing and navigation, and their automated recognition is advantageous e.g. in case of large multi-storey buildings with many office rooms. The inherent complexity of the automation of the recognition process is increased by the presence of clutter and occlusions, difficult to avoid in indoor scenes. In this work, we present a pipeline of techniques used for the reconstruction and interpretation of building interiors using information acquired in the form of point clouds and images. The methodology goes in depth with door detection and labelling as either opened, closed or furniture (false positive)
NASA Astrophysics Data System (ADS)
Peng, Qi; Guan, Weipeng; Wu, Yuxiang; Cai, Ye; Xie, Canyu; Wang, Pengfei
2018-01-01
This paper proposes a three-dimensional (3-D) high-precision indoor positioning strategy using Tabu search based on visible light communication. Tabu search is a powerful global optimization algorithm, and the 3-D indoor positioning can be transformed into an optimal solution problem. Therefore, in the 3-D indoor positioning, the optimal receiver coordinate can be obtained by the Tabu search algorithm. For all we know, this is the first time the Tabu search algorithm is applied to visible light positioning. Each light-emitting diode (LED) in the system broadcasts a unique identity (ID) and transmits the ID information. When the receiver detects optical signals with ID information from different LEDs, using the global optimization of the Tabu search algorithm, the 3-D high-precision indoor positioning can be realized when the fitness value meets certain conditions. Simulation results show that the average positioning error is 0.79 cm, and the maximum error is 5.88 cm. The extended experiment of trajectory tracking also shows that 95.05% positioning errors are below 1.428 cm. It can be concluded from the data that the 3-D indoor positioning based on the Tabu search algorithm achieves the requirements of centimeter level indoor positioning. The algorithm used in indoor positioning is very effective and practical and is superior to other existing methods for visible light indoor positioning.
Open-Loop Performance of COBALT Precision Landing Payload on a Commercial Sub-Orbital Rocket
NASA Technical Reports Server (NTRS)
Restrepo, Carolina I.; Carson, John M., III; Amzajerdian, Farzin; Seubert, Carl R.; Lovelace, Ronney S.; McCarthy, Megan M.; Tse, Teming; Stelling, Richard; Collins, Steven M.
2018-01-01
An open-loop flight test campaign of the NASA COBALT (CoOperative Blending of Autonomous Landing Technologies) platform was conducted onboard the Masten Xodiac suborbital rocket testbed. The COBALT platform integrates NASA Guidance, Navigation and Control (GN&C) sensing technologies for autonomous, precise soft landing, including the Navigation Doppler Lidar (NDL) velocity and range sensor and the Lander Vision System (LVS) Terrain Relative Navigation (TRN) system. A specialized navigation filter running onboard COBALT fuses the NDL and LVS data in real time to produce a navigation solution that is independent of GPS and suitable for future, autonomous, planetary, landing systems. COBALT was a passive payload during the open loop tests. COBALT's sensors were actively taking data and processing it in real time, but the Xodiac rocket flew with its own GPS-navigation system as a risk reduction activity in the maturation of the technologies towards space flight. A future closed-loop test campaign is planned where the COBALT navigation solution will be used to fly its host vehicle.
MODELING SMALL-SCALE SPILLS OF AQUEOUS SOLUTIONS IN THE INDOOR ENVIRONMENT
A mass transfer model is proposed to estimate the rates of chemical emissions from aqueous solutions spilled on hard surfaces inside buildings. The model is presented in two forms: a set of four ordinary differential equations and a simplified exact solution. The latter can be ...
A positioning system with no line-of-sight restrictions for cluttered environments
NASA Astrophysics Data System (ADS)
Prigge, Eric A.
Accurate sensing of vehicle location and attitude is a fundamental requirement in many mobile-robot applications, but is a very challenging problem in the cluttered and unstructured environment of the real world. Many existing indoor positioning systems are limited in workspace and robustness because they require clear lines of sight or do not provide absolute, drift-free measurements. Examples include overhead vision systems, where an unobstructed view must be maintained between robot and camera, and inertial systems, where the measurements drift over time. The research presented in this dissertation provides a new location- and attitude-sensing system designed specifically to meet the challenges of operation in a realistic, cluttered indoor environment, such as that of an office building or warehouse. The system is not limited by line-of-sight restrictions and produces drift-free measurements throughout a three-dimensional operating volume that can span a large building. Accuracy of several centimeters and a few degrees is delivered at 10 Hz, and any number of the small sensor units can be in operation, all providing estimates in a common reference frame. This positioning system is based on extremely-low-frequency magnetic fields, which have excellent characteristics for penetrating line-of-sight obstructions. Beacons located throughout the workspace create the low-level fields. A sensor unit on the mobile robot samples the local magnetic field and processes the measurements to determine its location and attitude. This research overcomes limitations in existing magnetic-based systems. The design of the signal structure, based on pseudorandom codes, enables the use of multiple, distributed L-beacons and greatly expands coverage volume. The development of real-time identification and correction methods mitigates the impact of distortions caused by materials in the environment. A novel solution algorithm combats both challenges, providing increased coverage volume and reduced sensitivity to materials. This dissertation examines the concept for the system, the challenges encountered during its development, the research solutions that enable the system, the design of a prototype, and results from experimental demonstrations. The positioning system developed through this research provides an effective solution not only for mobile robots navigating cluttered environments, but has application in other areas such as object tracking, augmented reality, and construction.
Team VaCAS Design and Development of Cooperative UGV System
2011-02-04
Mapping ( SLAM ) [24]. Similar to such work, the technique to be used in the project will also (1) use the last reliably available data as the reference...Losada1, D., Matia1, F., Pedraza1, L., Jimenez A. and Galan, R., Consistency of SLAM -EKF Algorithms for Indoor Environments, Journal of Intelligent and...mounted on the UGV 1 include GPS for outdoor navigation, LiDAR for obstacle avoidance and mapping and camera for OOI detection and localization. UGVs 2
Mobile robot exploration and navigation of indoor spaces using sonar and vision
NASA Technical Reports Server (NTRS)
Kortenkamp, David; Huber, Marcus; Koss, Frank; Belding, William; Lee, Jaeho; Wu, Annie; Bidlack, Clint; Rodgers, Seth
1994-01-01
Integration of skills into an autonomous robot that performs a complex task is described. Time constraints prevented complete integration of all the described skills. The biggest problem was tuning the sensor-based region-finding algorithm to the environment involved. Since localization depended on matching regions found with the a priori map, the robot became lost very quickly. If the low level sensing of the world is not working, then high level reasoning or map making will be unsuccessful.
Polarized skylight navigation.
Hamaoui, Moshe
2017-01-20
Vehicle state estimation is an essential prerequisite for navigation. The present approach seeks to use skylight polarization to facilitate state estimation under autonomous unconstrained flight conditions. Atmospheric scattering polarizes incident sunlight such that solar position is mathematically encoded in the resulting skylight polarization pattern. Indeed, several species of insects are able to sense skylight polarization and are believed to navigate polarimetrically. Sun-finding methodologies for polarized skylight navigation (PSN) have been proposed in the literature but typically rely on calibration updates to account for changing atmospheric conditions and/or are limited to 2D operation. To address this technology gap, a gradient-based PSN solution is developed based upon the Rayleigh sky model. The solution is validated in simulation, and effects of measurement error and changing atmospheric conditions are investigated. Finally, an experimental effort is described wherein polarimetric imagery is collected, ground-truth is established through independent imager-attitude measurement, the gradient-based PSN solution is applied, and results are analyzed.
Sign detection for autonomous navigation
NASA Astrophysics Data System (ADS)
Goodsell, Thomas G.; Snorrason, Magnus S.; Cartwright, Dustin; Stube, Brian; Stevens, Mark R.; Ablavsky, Vitaly X.
2003-09-01
Mobile robots currently cannot detect and read arbitrary signs. This is a major hindrance to mobile robot usability, since they cannot be tasked using directions that are intuitive to humans. It also limits their ability to report their position relative to intuitive landmarks. Other researchers have demonstrated some success on traffic sign recognition, but using template based methods limits the set of recognizable signs. There is a clear need for a sign detection and recognition system that can process a much wider variety of signs: traffic signs, street signs, store-name signs, building directories, room signs, etc. We are developing a system for Sign Understanding in Support of Autonomous Navigation (SUSAN), that detects signs from various cues common to most signs: vivid colors, compact shape, and text. We have demonstrated the feasibility of our approach on a variety of signs in both indoor and outdoor locations.
Two-Graph Building Interior Representation for Emergency Response Applications
NASA Astrophysics Data System (ADS)
Boguslawski, P.; Mahdjoubi, L.; Zverovich, V.; Fadli, F.
2016-06-01
Nowadays, in a rapidly developing urban environment with bigger and higher public buildings, disasters causing emergency situations and casualties are unavoidable. Preparedness and quick response are crucial issues saving human lives. Available information about an emergency scene, such as a building structure, helps for decision making and organizing rescue operations. Models supporting decision-making should be available in real, or near-real, time. Thus, good quality models that allow implementation of automated methods are highly desirable. This paper presents details of the recently developed method for automated generation of variable density navigable networks in a 3D indoor environment, including a full 3D topological model, which may be used not only for standard navigation but also for finding safe routes and simulating hazard and phenomena associated with disasters such as fire spread and heat transfer.
A Navigation System for the Visually Impaired: A Fusion of Vision and Depth Sensor
Kanwal, Nadia; Bostanci, Erkan; Currie, Keith; Clark, Adrian F.
2015-01-01
For a number of years, scientists have been trying to develop aids that can make visually impaired people more independent and aware of their surroundings. Computer-based automatic navigation tools are one example of this, motivated by the increasing miniaturization of electronics and the improvement in processing power and sensing capabilities. This paper presents a complete navigation system based on low cost and physically unobtrusive sensors such as a camera and an infrared sensor. The system is based around corners and depth values from Kinect's infrared sensor. Obstacles are found in images from a camera using corner detection, while input from the depth sensor provides the corresponding distance. The combination is both efficient and robust. The system not only identifies hurdles but also suggests a safe path (if available) to the left or right side and tells the user to stop, move left, or move right. The system has been tested in real time by both blindfolded and blind people at different indoor and outdoor locations, demonstrating that it operates adequately. PMID:27057135
Development of the navigation system for visually impaired.
Harada, Tetsuya; Kaneko, Yuki; Hirahara, Yoshiaki; Yanashima, Kenji; Magatani, Kazushige
2004-01-01
A white cane is a typical support instrument for the visually impaired. They use a white cane for the detection of obstacles while walking. So, the area where they have a mental map, they can walk using white cane without the help of others. However, they cannot walk independently in the unknown area, even if they use a white cane. Because, a white cane is a detecting device for obstacles and not a navigation device for their correct route. Now, we are developing the navigation system for the visually impaired which uses indoor space. In Japan, sometimes colored guide lines to the destination is used for a normal person. These lines are attached on the floor, we can reach the destination, if we walk along one of these line. In our system, a developed new white cane senses one colored guide line, and make notice to an user by vibration. This system recognizes the line of the color stuck on the floor by the optical sensor attached in the white cane. And in order to guide still more smoothly, infrared beacons (optical beacon), which can perform voice guidance, are also used.
Design and Implementation of a Novel Portable 360° Stereo Camera System with Low-Cost Action Cameras
NASA Astrophysics Data System (ADS)
Holdener, D.; Nebiker, S.; Blaser, S.
2017-11-01
The demand for capturing indoor spaces is rising with the digitalization trend in the construction industry. An efficient solution for measuring challenging indoor environments is mobile mapping. Image-based systems with 360° panoramic coverage allow a rapid data acquisition and can be processed to georeferenced 3D images hosted in cloud-based 3D geoinformation services. For the multiview stereo camera system presented in this paper, a 360° coverage is achieved with a layout consisting of five horizontal stereo image pairs in a circular arrangement. The design is implemented as a low-cost solution based on a 3D printed camera rig and action cameras with fisheye lenses. The fisheye stereo system is successfully calibrated with accuracies sufficient for the applied measurement task. A comparison of 3D distances with reference data delivers maximal deviations of 3 cm on typical distances in indoor space of 2-8 m. Also the automatic computation of coloured point clouds from the stereo pairs is demonstrated.
Rand, Kristina M.; Creem-Regehr, Sarah H.; Thompson, William B.
2015-01-01
The ability to navigate without getting lost is an important aspect of quality of life. In five studies, we evaluated how spatial learning is affected by the increased demands of keeping oneself safe while walking with degraded vision (mobility monitoring). We proposed that safe low-vision mobility requires attentional resources, providing competition for those needed to learn a new environment. In Experiments 1 and 2 participants navigated along paths in a real-world indoor environment with simulated degraded vision or normal vision. Memory for object locations seen along the paths was better with normal compared to degraded vision. With degraded vision, memory was better when participants were guided by an experimenter (low monitoring demands) versus unguided (high monitoring demands). In Experiments 3 and 4, participants walked while performing an auditory task. Auditory task performance was superior with normal compared to degraded vision. With degraded vision, auditory task performance was better when guided compared to unguided. In Experiment 5, participants performed both the spatial learning and auditory tasks under degraded vision. Results showed that attention mediates the relationship between mobility-monitoring demands and spatial learning. These studies suggest that more attention is required and spatial learning is impaired when navigating with degraded viewing. PMID:25706766
Teaching the Blind to Find Their Way by Playing Video Games
Merabet, Lotfi B.; Connors, Erin C.; Halko, Mark A.; Sánchez, Jaime
2012-01-01
Computer based video games are receiving great interest as a means to learn and acquire new skills. As a novel approach to teaching navigation skills in the blind, we have developed Audio-based Environment Simulator (AbES); a virtual reality environment set within the context of a video game metaphor. Despite the fact that participants were naïve to the overall purpose of the software, we found that early blind users were able to acquire relevant information regarding the spatial layout of a previously unfamiliar building using audio based cues alone. This was confirmed by a series of behavioral performance tests designed to assess the transfer of acquired spatial information to a large-scale, real-world indoor navigation task. Furthermore, learning the spatial layout through a goal directed gaming strategy allowed for the mental manipulation of spatial information as evidenced by enhanced navigation performance when compared to an explicit route learning strategy. We conclude that the immersive and highly interactive nature of the software greatly engages the blind user to actively explore the virtual environment. This in turn generates an accurate sense of a large-scale three-dimensional space and facilitates the learning and transfer of navigation skills to the physical world. PMID:23028703
Prol, Fabricio dos Santos; El Issaoui, Aimad; Hakala, Teemu
2018-01-01
The use of Personal Mobile Terrestrial System (PMTS) has increased considerably for mobile mapping applications because these systems offer dynamic data acquisition with ground perspective in places where the use of wheeled platforms is unfeasible, such as forests and indoor buildings. PMTS has become more popular with emerging technologies, such as miniaturized navigation sensors and off-the-shelf omnidirectional cameras, which enable low-cost mobile mapping approaches. However, most of these sensors have not been developed for high-accuracy metric purposes and therefore require rigorous methods of data acquisition and data processing to obtain satisfactory results for some mapping applications. To contribute to the development of light, low-cost PMTS and potential applications of these off-the-shelf sensors for forest mapping, this paper presents a low-cost PMTS approach comprising an omnidirectional camera with off-the-shelf navigation systems and its evaluation in a forest environment. Experimental assessments showed that the integrated sensor orientation approach using navigation data as the initial information can increase the trajectory accuracy, especially in covered areas. The point cloud generated with the PMTS data had accuracy consistent with the Ground Sample Distance (GSD) range of omnidirectional images (3.5–7 cm). These results are consistent with those obtained for other PMTS approaches. PMID:29522467
InPRO: Automated Indoor Construction Progress Monitoring Using Unmanned Aerial Vehicles
NASA Astrophysics Data System (ADS)
Hamledari, Hesam
In this research, an envisioned automated intelligent robotic solution for automated indoor data collection and inspection that employs a series of unmanned aerial vehicles (UAV), entitled "InPRO", is presented. InPRO consists of four stages, namely: 1) automated path planning; 2) autonomous UAV-based indoor inspection; 3) automated computer vision-based assessment of progress; and, 4) automated updating of 4D building information models (BIM). The works presented in this thesis address the third stage of InPRO. A series of computer vision-based methods that automate the assessment of construction progress using images captured at indoor sites are introduced. The proposed methods employ computer vision and machine learning techniques to detect the components of under-construction indoor partitions. In particular, framing (studs), insulation, electrical outlets, and different states of drywall sheets (installing, plastering, and painting) are automatically detected using digital images. High accuracy rates, real-time performance, and operation without a priori information are indicators of the methods' promising performance.
Monitoring of pyrocatechol indoor air pollution
NASA Astrophysics Data System (ADS)
Eškinja, I.; Grabarić, Z.; Grabarić, B. S.
Spectrophotometric and electrochemical methods for monitoring of pyrocatechol (PC) indoor air pollution have been investigated. Spectrophotometric determination was performed using Fe(III) and iodine methods. The adherence to Beer's law was found in the concentration range between 0 and 12 μg ml - for iodine method at pH = 5.7 measuring absorbance at 725 nm, and in the range 0-30 μg ml - for Fe(III) method at pH = 9.5 measuring absorbance at 510 nm. The former method showed greater sensitivity than the latter one. Differential pulse voltammetry (DPV) and chronoamperometric (CA) detection in flow injection analysis (FIA) using carbon paste electrode in phosphate buffer solution of pH = 6.5 was also used for pyrocatechol determination. The electrochemical methods allowed pyrocatechol quantitation in submicromolar concentration level with an overall reproducibility of ± 1%. The efficiency of pyrocatechol sampling collection was investigated at two temperatures (27 and 40°C) in water, 0.1 M NaOH and 0.1 M HCl solutions. Solution of 0.1 M HCl gave the best collection efficiency (95.5-98.5%). A chamber testing simulating the indoor pollution has been performed. In order to check the reliability of the proposed methods for monitoring of the indoor pyrocatechol pollution, the air in working premises with pyrocatechol released from meteorological charts during mapping and paper drying was analyzed using proposed methods. The concentration of pyrocatechol in the air during mapping was found to be 1.8 mg m -3 which is below the hygienic standard of permissible exposure of 20 mg m -3 (≈ 5 ppm). The release of pyrocatechol from the paper impregnated with pyrocatechol standing at room temperature during one year was also measured. The proposed methods can be used for indoor pyrocatechol pollution monitoring in working premises of photographic, rubber, oil and dye industries, fur and furniture dyeing and cosmetic or pharmaceutical premises where pyrocatechol and related compounds are in use.
Multidimensional Optimization of Signal Space Distance Parameters in WLAN Positioning
Brković, Milenko; Simić, Mirjana
2014-01-01
Accurate indoor localization of mobile users is one of the challenging problems of the last decade. Besides delivering high speed Internet, Wireless Local Area Network (WLAN) can be used as an effective indoor positioning system, being competitive both in terms of accuracy and cost. Among the localization algorithms, nearest neighbor fingerprinting algorithms based on Received Signal Strength (RSS) parameter have been extensively studied as an inexpensive solution for delivering indoor Location Based Services (LBS). In this paper, we propose the optimization of the signal space distance parameters in order to improve precision of WLAN indoor positioning, based on nearest neighbor fingerprinting algorithms. Experiments in a real WLAN environment indicate that proposed optimization leads to substantial improvements of the localization accuracy. Our approach is conceptually simple, is easy to implement, and does not require any additional hardware. PMID:24757443
Navigation Concepts for the James Webb Space Telescope
NASA Technical Reports Server (NTRS)
Long, Anne; Leung, Dominic; Kelbel, David; Beckman, Mark; Grambling, Cheryl
2003-01-01
This paper evaluates the performance that can be achieved using candidate ground and onboard navigation approaches for operation of the James Webb Space Telescope, which will be in an orbit about the Sun-Earth L2 libration point. The ground navigation approach processes standard range and Doppler measurements from the Deep Space Network The onboard navigation approach processes celestial object measurements and/or ground-to- spacecraft Doppler measurements to autonomously estimate the spacecraft s position and velocity and Doppler reference frequency. Particular attention is given to assessing the absolute position and velocity accuracy that can be achieved in the presence of the frequent spacecraft reorientations and momentum unloads planned for this mission. The ground navigation approach provides stable navigation solutions using a tracking schedule of one 30-minute contact per day. The onboard navigation approach that uses only optical quality celestial object measurements provides stable autonomous navigation solutions. This study indicates that unmodeled changes in the solar radiation pressure cross-sectional area and modeled momentum unload velocity changes are the major error sources. These errors can be mitigated by modeling these changes, by estimating corrections to compensate for the changes, or by including acceleration measurements.
VCSELs in short-pulse operation for time-of-flight applications
NASA Astrophysics Data System (ADS)
Moench, Holger; Gronenborn, Stephan; Gu, Xi; Gudde, Ralph; Herper, Markus; Kolb, Johanna; Miller, Michael; Smeets, Michael; Weigl, Alexander
2018-02-01
VCSEL arrays are the ideal light source for 3D imaging applications. The narrow emission spectrum and the ability for short pulses make them superior to LEDs. Combined with fast photodiodes or special camera chips spatial information can be obtained which is needed in diverse applications like camera autofocus, indoor navigation, 3D-object recognition, augmented reality or autonomously driving vehicles. Pulse operation at the ns scale and at low duty cycle can work with significantly higher current than traditionally used for VCSELs in continuous wave operation. With reduced thermal limitations at low average heat dissipation very high currents become feasible and tens of Watts output power have been realized with small VCSEL chips. The optical emission pattern of VCSELs can be tailored to the desired field of view using beam shaping elements. Such optical elements also enable laser safe class 1 products. A detailed analysis of the complete system and the operation mode is required to calculate the maximum permitted power for a safe system. The good VCSEL properties like robustness, stability over temperature and the potential for integrated solutions open a huge potential for VCSELs in new mass applications in the consumer and automotive markets.
Integration of Models of Building Interiors with Cadastral Data
NASA Astrophysics Data System (ADS)
Gotlib, Dariusz; Karabin, Marcin
2017-12-01
Demands for applications which use models of building interiors is growing and highly diversified. Those models are applied at the stage of designing and construction of a building, in applications which support real estate management, in navigation and marketing systems and, finally, in crisis management and security systems. They are created on the basis of different data: architectural and construction plans, both, in the analogue form, as well as CAD files, BIM data files, by means of laser scanning (TLS) and conventional surveys. In this context the issue of searching solutions which would integrate the existing models and lead to elimination of data redundancy is becoming more important. The authors analysed the possible input- of cadastral data (legal extent of premises) at the stage of the creation and updating different models of building's interiors. The paper focuses on one issue - the way of describing the geometry of premises basing on the most popular source data, i.e. architectural and construction plans. However, the described rules may be considered as universal and also may be applied in practice concerned may be used during the process of creation and updating indoor models based on BIM dataset or laser scanning clouds
Cognitive object recognition system (CORS)
NASA Astrophysics Data System (ADS)
Raju, Chaitanya; Varadarajan, Karthik Mahesh; Krishnamurthi, Niyant; Xu, Shuli; Biederman, Irving; Kelley, Troy
2010-04-01
We have developed a framework, Cognitive Object Recognition System (CORS), inspired by current neurocomputational models and psychophysical research in which multiple recognition algorithms (shape based geometric primitives, 'geons,' and non-geometric feature-based algorithms) are integrated to provide a comprehensive solution to object recognition and landmarking. Objects are defined as a combination of geons, corresponding to their simple parts, and the relations among the parts. However, those objects that are not easily decomposable into geons, such as bushes and trees, are recognized by CORS using "feature-based" algorithms. The unique interaction between these algorithms is a novel approach that combines the effectiveness of both algorithms and takes us closer to a generalized approach to object recognition. CORS allows recognition of objects through a larger range of poses using geometric primitives and performs well under heavy occlusion - about 35% of object surface is sufficient. Furthermore, geon composition of an object allows image understanding and reasoning even with novel objects. With reliable landmarking capability, the system improves vision-based robot navigation in GPS-denied environments. Feasibility of the CORS system was demonstrated with real stereo images captured from a Pioneer robot. The system can currently identify doors, door handles, staircases, trashcans and other relevant landmarks in the indoor environment.
Stand-Alone and Hybrid Positioning Using Asynchronous Pseudolites
Gioia, Ciro; Borio, Daniele
2015-01-01
global navigation satellite system (GNSS) receivers are usually unable to achieve satisfactory performance in difficult environments, such as open-pit mines, urban canyons and indoors. Pseudolites have the potential to extend GNSS usage and significantly improve receiver performance in such environments by providing additional navigation signals. This also applies to asynchronous pseudolite systems, where different pseudolites operate in an independent way. Asynchronous pseudolite systems require, however, dedicated strategies in order to properly integrate GNSS and pseudolite measurements. In this paper, several asynchronous pseudolite/GNSS integration strategies are considered: loosely- and tightly-coupled approaches are developed and combined with pseudolite proximity and receiver signal strength (RSS)-based positioning. The performance of the approaches proposed has been tested in different scenarios, including static and kinematic conditions. The tests performed demonstrate that the methods developed are effective techniques for integrating heterogeneous measurements from different sources, such as asynchronous pseudolites and GNSS. PMID:25609041
A Context-Recognition-Aided PDR Localization Method Based on the Hidden Markov Model
Lu, Yi; Wei, Dongyan; Lai, Qifeng; Li, Wen; Yuan, Hong
2016-01-01
Indoor positioning has recently become an important field of interest because global navigation satellite systems (GNSS) are usually unavailable in indoor environments. Pedestrian dead reckoning (PDR) is a promising localization technique for indoor environments since it can be implemented on widely used smartphones equipped with low cost inertial sensors. However, the PDR localization severely suffers from the accumulation of positioning errors, and other external calibration sources should be used. In this paper, a context-recognition-aided PDR localization model is proposed to calibrate PDR. The context is detected by employing particular human actions or characteristic objects and it is matched to the context pre-stored offline in the database to get the pedestrian’s location. The Hidden Markov Model (HMM) and Recursive Viterbi Algorithm are used to do the matching, which reduces the time complexity and saves the storage. In addition, the authors design the turn detection algorithm and take the context of corner as an example to illustrate and verify the proposed model. The experimental results show that the proposed localization method can fix the pedestrian’s starting point quickly and improves the positioning accuracy of PDR by 40.56% at most with perfect stability and robustness at the same time. PMID:27916922
Delay Tracking of Spread-Spectrum Signals for Indoor Optical Ranging
Salido-Monzú, David; Martín-Gorostiza, Ernesto; Lázaro-Galilea, José Luis; Martos-Naya, Eduardo; Wieser, Andreas
2014-01-01
Delay tracking of spread-spectrum signals is widely used for ranging in radio frequency based navigation. Its use in non-coherent optical ranging, however, has not been extensively studied since optical channels are less subject to narrowband interference situations where these techniques become more useful. In this work, an early-late delay-locked loop adapted to indoor optical ranging is presented and analyzed. The specific constraints of free-space infrared channels in this context substantially differ from those typically considered in radio frequency applications. The tracking stage is part of an infrared differential range measuring system with application to mobile target indoor localization. Spread-spectrum signals are used in this context to provide accurate ranging while reducing the effect of multipath interferences. The performance of the stage regarding noise and dynamic errors is analyzed and validated, providing expressions that allow an adequate selection of the design parameters depending on the expected input signal characteristics. The behavior of the stage in a general multipath scenario is also addressed to estimate the multipath error bounds. The results, evaluated under realistic conditions corresponding to an 870 nm link with 25 MHz chip-rate, built with low-cost up-to-date devices, show that an overall error below 6% of a chip time can be achieved. PMID:25490585
Object Detection Applied to Indoor Environments for Mobile Robot Navigation.
Hernández, Alejandra Carolina; Gómez, Clara; Crespo, Jonathan; Barber, Ramón
2016-07-28
To move around the environment, human beings depend on sight more than their other senses, because it provides information about the size, shape, color and position of an object. The increasing interest in building autonomous mobile systems makes the detection and recognition of objects in indoor environments a very important and challenging task. In this work, a vision system to detect objects considering usual human environments, able to work on a real mobile robot, is developed. In the proposed system, the classification method used is Support Vector Machine (SVM) and as input to this system, RGB and depth images are used. Different segmentation techniques have been applied to each kind of object. Similarly, two alternatives to extract features of the objects are explored, based on geometric shape descriptors and bag of words. The experimental results have demonstrated the usefulness of the system for the detection and location of the objects in indoor environments. Furthermore, through the comparison of two proposed methods for extracting features, it has been determined which alternative offers better performance. The final results have been obtained taking into account the proposed problem and that the environment has not been changed, that is to say, the environment has not been altered to perform the tests.
Object Detection Applied to Indoor Environments for Mobile Robot Navigation
Hernández, Alejandra Carolina; Gómez, Clara; Crespo, Jonathan; Barber, Ramón
2016-01-01
To move around the environment, human beings depend on sight more than their other senses, because it provides information about the size, shape, color and position of an object. The increasing interest in building autonomous mobile systems makes the detection and recognition of objects in indoor environments a very important and challenging task. In this work, a vision system to detect objects considering usual human environments, able to work on a real mobile robot, is developed. In the proposed system, the classification method used is Support Vector Machine (SVM) and as input to this system, RGB and depth images are used. Different segmentation techniques have been applied to each kind of object. Similarly, two alternatives to extract features of the objects are explored, based on geometric shape descriptors and bag of words. The experimental results have demonstrated the usefulness of the system for the detection and location of the objects in indoor environments. Furthermore, through the comparison of two proposed methods for extracting features, it has been determined which alternative offers better performance. The final results have been obtained taking into account the proposed problem and that the environment has not been changed, that is to say, the environment has not been altered to perform the tests. PMID:27483264
Spatial Cognition and Range Use in Free-Range Laying Hens.
Campbell, Dana L M; Talk, Andrew C; Loh, Ziyang A; Dyall, Tim R; Lee, Caroline
2018-02-08
Radio-frequency identification tracking shows individual free-range laying hens vary in range use, with some never going outdoors. The range is typically more environmentally complex, requiring navigation to return to the indoor resources. Outdoor-preferring hens may have improved spatial abilities compared to indoor-preferring hens. Experiment 1 tested 32 adult ISA Brown hens in a T-maze learning task that showed exclusively-indoor birds were slowest to reach the learning success criterion ( p < 0.05). Experiment 2 tested 117 pullets from enriched or non-enriched early rearing treatments (1 pen replicate per treatment) in the same maze at 15-16 or 17-18 weeks. Enriched birds reached learning success criterion faster at 15-16 weeks ( p < 0.05) but not at 17-18 weeks ( p > 0.05), the age that coincided with the onset of lay. Enriched birds that were faster to learn the maze task showed more range visits in the first 4 weeks of range access. Enriched and non-enriched birds showed no differences in telencephalon or hippocampal volume ( p > 0.05). Fear may reduce spatial abilities but further testing with more pen replicates per early rearing treatments would improve our understanding of the relationship between spatial cognitive abilities and range use.
Development of voice navigation system for the visually impaired by using IC tags.
Takatori, Norihiko; Nojima, Kengo; Matsumoto, Masashi; Yanashima, Kenji; Magatani, Kazushige
2006-01-01
There are about 300,000 visually impaired persons in Japan. Most of them are old persons and, cannot become skillful in using a white cane, even if they make effort to learn how to use a white cane. Therefore, some guiding system that supports the independent activities of the visually impaired are required. In this paper, we will describe about a developed white cane system that supports the independent walking of the visually impaired in the indoor space. This system is composed of colored navigation lines that include IC tags and an intelligent white cane that has a navigation computer. In our system colored navigation lines that are put on the floor of the target space from the start point to the destination and IC tags that are set at the landmark point are used for indication of the route to the destination. The white cane has a color sensor, an IC tag transceiver and a computer system that includes a voice processor. This white cane senses the navigation line that has target color by a color sensor. When a color sensor finds the target color, the white cane informs a white cane user that he/she is on the navigation line by vibration. So, only following this vibration, the user can reach the destination. However, at some landmark points, guidance is necessary. At these points, an IC tag is set under the navigation line. The cane makes communication with the tag and informs the user about the land mark pint by pre recorded voice. Ten normal subjects who were blindfolded were tested with our developed system. All of them could walk along navigation line. And the IC tag information system worked well. Therefore, we have concluded that our system will be a very valuable one to support activities of the visually impaired.
Research of cartographer laser SLAM algorithm
NASA Astrophysics Data System (ADS)
Xu, Bo; Liu, Zhengjun; Fu, Yiran; Zhang, Changsai
2017-11-01
As the indoor is a relatively closed and small space, total station, GPS, close-range photogrammetry technology is difficult to achieve fast and accurate indoor three-dimensional space reconstruction task. LIDAR SLAM technology does not rely on the external environment a priori knowledge, only use their own portable lidar, IMU, odometer and other sensors to establish an independent environment map, a good solution to this problem. This paper analyzes the Google Cartographer laser SLAM algorithm from the point cloud matching and closed loop detection. Finally, the algorithm is presented in the 3D visualization tool RViz from the data acquisition and processing to create the environment map, complete the SLAM technology and realize the process of indoor threedimensional space reconstruction
Lee, In Yong; Park, Seong Joon; Seo, Jang Hoon; Sim, Seobo; Kim, Jin-Hwan; Gwon, Young Gon; Yong, Tai-Soon
2017-01-01
The ghost ant Tapinoma melanocephalum is a common household pest worldwide. The present study examined the occurrence of the species in urban homes in Korea. During the period of September 2014 to January 2016, T. melanocephalum workers were collected from 58 homes at 29 different localities using bait traps with 10% sugar solution. The species was widely distributed throughout urban homes at 29 different localities, and the indoor occurrence of T. melanocephalum was highest in Seoul (32.7%) and metropolitan areas of Gyeonggi-do (Province) (29.3%). The indoor incidence rate of T. melanocephalum peaked in September (22.8%), remained moderate from October through April, and peaked again in May (15.7%). In contrast, a low incidence was observed from June to August (7.0%). The present study provides evidence that native ants, such as T. melanocephalum, are potential indoor pests of homes in Korea throughout the year. PMID:28506048
Zou, Han; Jiang, Hao; Luo, Yiwen; Zhu, Jianjie; Lu, Xiaoxuan; Xie, Lihua
2016-01-01
The location and contextual status (indoor or outdoor) is fundamental and critical information for upper-layer applications, such as activity recognition and location-based services (LBS) for individuals. In addition, optimizations of building management systems (BMS), such as the pre-cooling or heating process of the air-conditioning system according to the human traffic entering or exiting a building, can utilize the information, as well. The emerging mobile devices, which are equipped with various sensors, become a feasible and flexible platform to perform indoor-outdoor (IO) detection. However, power-hungry sensors, such as GPS and WiFi, should be used with caution due to the constrained battery storage on mobile device. We propose BlueDetect: an accurate, fast response and energy-efficient scheme for IO detection and seamless LBS running on the mobile device based on the emerging low-power iBeacon technology. By leveraging the on-broad Bluetooth module and our proposed algorithms, BlueDetect provides a precise IO detection service that can turn on/off on-board power-hungry sensors smartly and automatically, optimize their performances and reduce the power consumption of mobile devices simultaneously. Moreover, seamless positioning and navigation services can be realized by it, especially in a semi-outdoor environment, which cannot be achieved by GPS or an indoor positioning system (IPS) easily. We prototype BlueDetect on Android mobile devices and evaluate its performance comprehensively. The experimental results have validated the superiority of BlueDetect in terms of IO detection accuracy, localization accuracy and energy consumption. PMID:26907295
Miniaturized GPS/MEMS IMU integrated board
NASA Technical Reports Server (NTRS)
Lin, Ching-Fang (Inventor)
2012-01-01
This invention documents the efforts on the research and development of a miniaturized GPS/MEMS IMU integrated navigation system. A miniaturized GPS/MEMS IMU integrated navigation system is presented; Laser Dynamic Range Imager (LDRI) based alignment algorithm for space applications is discussed. Two navigation cameras are also included to measure the range and range rate which can be integrated into the GPS/MEMS IMU system to enhance the navigation solution.
Qian, Jun; Zi, Bin; Ma, Yangang; Zhang, Dan
2017-01-01
In order to transport materials flexibly and smoothly in a tight plant environment, an omni-directional mobile robot based on four Mecanum wheels was designed. The mechanical system of the mobile robot is made up of three separable layers so as to simplify its combination and reorganization. Each modularized wheel was installed on a vertical suspension mechanism, which ensures the moving stability and keeps the distances of four wheels invariable. The control system consists of two-level controllers that implement motion control and multi-sensor data processing, respectively. In order to make the mobile robot navigate in an unknown semi-structured indoor environment, the data from a Kinect visual sensor and four wheel encoders were fused to localize the mobile robot using an extended Kalman filter with specific processing. Finally, the mobile robot was integrated in an intelligent manufacturing system for material conveying. Experimental results show that the omni-directional mobile robot can move stably and autonomously in an indoor environment and in industrial fields. PMID:28891964
Espinosa, Felipe; Santos, Carlos; Marrón-Romera, Marta; Pizarro, Daniel; Valdés, Fernando; Dongil, Javier
2011-01-01
This paper describes a relative localization system used to achieve the navigation of a convoy of robotic units in indoor environments. This positioning system is carried out fusing two sensorial sources: (a) an odometric system and (b) a laser scanner together with artificial landmarks located on top of the units. The laser source allows one to compensate the cumulative error inherent to dead-reckoning; whereas the odometry source provides less pose uncertainty in short trajectories. A discrete Extended Kalman Filter, customized for this application, is used in order to accomplish this aim under real time constraints. Different experimental results with a convoy of Pioneer P3-DX units tracking non-linear trajectories are shown. The paper shows that a simple setup based on low cost laser range systems and robot built-in odometry sensors is able to give a high degree of robustness and accuracy to the relative localization problem of convoy units for indoor applications. PMID:22164079
Espinosa, Felipe; Santos, Carlos; Marrón-Romera, Marta; Pizarro, Daniel; Valdés, Fernando; Dongil, Javier
2011-01-01
This paper describes a relative localization system used to achieve the navigation of a convoy of robotic units in indoor environments. This positioning system is carried out fusing two sensorial sources: (a) an odometric system and (b) a laser scanner together with artificial landmarks located on top of the units. The laser source allows one to compensate the cumulative error inherent to dead-reckoning; whereas the odometry source provides less pose uncertainty in short trajectories. A discrete Extended Kalman Filter, customized for this application, is used in order to accomplish this aim under real time constraints. Different experimental results with a convoy of Pioneer P3-DX units tracking non-linear trajectories are shown. The paper shows that a simple setup based on low cost laser range systems and robot built-in odometry sensors is able to give a high degree of robustness and accuracy to the relative localization problem of convoy units for indoor applications.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hollinger, Geoffrey
This document presents results from tests to demonstrate underwater mapping capabilities of an underwater vehicle in conditions typically found in marine renewable energy arrays. These tests were performed with a tethered Seabotix vLBV300 underwater vehicle. The vehicle is equipped with an inertial navigation system (INS) based on a Gladiator Landmark 40 IMU and Teledyne Explorer Doppler Velocity Log, as well as a Gemini 720i scanning sonar acquired from Tritech. The results presented include both indoor pool and offshore deployments. The indoor pool deployments were performed on October 7, 2016 and February 3, 2017 in Corvallis, OR. The offshore deployment wasmore » performed on April 20, 2016 off the coast of Newport, OR (44.678 degrees N, 124.109 degrees W). During the mission period, the sea state varied between 3 and 4, with an average significant wave height of 1.6 m. Data was recorded from both the INS and the sonar.« less
Qian, Jun; Zi, Bin; Wang, Daoming; Ma, Yangang; Zhang, Dan
2017-09-10
In order to transport materials flexibly and smoothly in a tight plant environment, an omni-directional mobile robot based on four Mecanum wheels was designed. The mechanical system of the mobile robot is made up of three separable layers so as to simplify its combination and reorganization. Each modularized wheel was installed on a vertical suspension mechanism, which ensures the moving stability and keeps the distances of four wheels invariable. The control system consists of two-level controllers that implement motion control and multi-sensor data processing, respectively. In order to make the mobile robot navigate in an unknown semi-structured indoor environment, the data from a Kinect visual sensor and four wheel encoders were fused to localize the mobile robot using an extended Kalman filter with specific processing. Finally, the mobile robot was integrated in an intelligent manufacturing system for material conveying. Experimental results show that the omni-directional mobile robot can move stably and autonomously in an indoor environment and in industrial fields.
Balbach, Edith D.
2011-01-01
Objectives. We studied tobacco industry efforts during the 1980s and 1990s to promote the National Energy Management Institute (NEMI), a nonprofit organization, as an authority on indoor air quality as part of the industry's strategy to oppose smoke-free worksite policies. Methods. We analyzed tobacco industry documents, conducted literature searches in Lexis–Nexis for background and historical literature, and reviewed relevant public health and policy literature. Results. The tobacco industry provided more than US $6 million to NEMI to establish it as an authority on indoor air quality and to work with it to undermine support for smoke-free air policies by promoting ventilation as a solution to indoor air quality problems. Tobacco industry support for NEMI was not publicly disclosed. Conclusions. NEMI was a valuable ally for the tobacco industry through NEMI's ties to organized labor, its technical background, and its status as a third-party actor. NEMI also helped the industry to portray ventilation to improve overall indoor air quality and smoke-free worksites as an either–or choice; in fact, both can improve worker health. PMID:21233427
Campbell, Richard B; Balbach, Edith D
2011-03-01
We studied tobacco industry efforts during the 1980s and 1990s to promote the National Energy Management Institute (NEMI), a nonprofit organization, as an authority on indoor air quality as part of the industry's strategy to oppose smoke-free worksite policies. We analyzed tobacco industry documents, conducted literature searches in Lexis-Nexis for background and historical literature, and reviewed relevant public health and policy literature. The tobacco industry provided more than US $6 million to NEMI to establish it as an authority on indoor air quality and to work with it to undermine support for smoke-free air policies by promoting ventilation as a solution to indoor air quality problems. Tobacco industry support for NEMI was not publicly disclosed. NEMI was a valuable ally for the tobacco industry through NEMI's ties to organized labor, its technical background, and its status as a third-party actor. NEMI also helped the industry to portray ventilation to improve overall indoor air quality and smoke-free worksites as an either-or choice; in fact, both can improve worker health.
NASA Astrophysics Data System (ADS)
Trigo, Guilherme F.; Maass, Bolko; Krüger, Hans; Theil, Stephan
2018-01-01
Accurate autonomous navigation capabilities are essential for future lunar robotic landing missions with a pin-point landing requirement, since in the absence of direct line of sight to ground control during critical approach and landing phases, or when facing long signal delays the herein before mentioned capability is needed to establish a guidance solution to reach the landing site reliably. This paper focuses on the processing and evaluation of data collected from flight tests that consisted of scaled descent scenarios where the unmanned helicopter of approximately 85 kg approached a landing site from altitudes of 50 m down to 1 m for a downrange distance of 200 m. Printed crater targets were distributed along the ground track and their detection provided earth-fixed measurements. The Crater Navigation (CNav) algorithm used to detect and match the crater targets is an unmodified method used for real lunar imagery. We analyze the absolute position and attitude solutions of CNav obtained and recorded during these flight tests, and investigate the attainable quality of vehicle pose estimation using both CNav and measurements from a tactical-grade inertial measurement unit. The navigation filter proposed for this end corrects and calibrates the high-rate inertial propagation with the less frequent crater navigation fixes through a closed-loop, loosely coupled hybrid setup. Finally, the attainable accuracy of the fused solution is evaluated by comparison with the on-board ground-truth solution of a dual-antenna high-grade GNSS receiver. It is shown that the CNav is an enabler for building autonomous navigation systems with high quality and suitability for exploration mission scenarios.
Pragmatic Divestment of KC-135 Navigators in the Special Operations Air Refueling Mission
2015-03-26
publicly expressed opinions, and the bandwagon effect of majority opinion. This technique replaces direct debate by a carefully designed program of... effective , comprehensive solution. Ultimately, the panel of experts arrived at conclusions supporting the hypothesis that navigator divestment and SOAR...manpower, personnel, and training effects after navigators are phased out
Galileo: The Added Value for Integrity in Harsh Environments.
Borio, Daniele; Gioia, Ciro
2016-01-16
A global navigation satellite system (GNSS)-based navigation is a challenging task in a signal-degraded environments where GNSS signals are distorted by multipath and attenuated by fading effects: the navigation solution may be inaccurate or unavailable. A possible approach to improve accuracy and availability is the joint use of measurements from different GNSSs and quality check algorithms; this approach is investigated here using live GPS and Galileo signals. A modified receiver autonomous integrity monitoring (RAIM) algorithm, including geometry and separability checks, is proposed to detect and exclude erroneous measurements: the multi-constellation approach provides redundant measurements, and RAIM exploits them to exclude distorted observations. The synergy between combined GPS/Galileo navigation and RAIM is analyzed using live data; the performance is compared to the accuracy and availability of a GPS-only solution. The tests performed demonstrate that the methods developed are effective techniques for GNSS-based navigation in signal-degraded environments. The joint use of the multi-constellation approach and of modified RAIM algorithms improves the performance of the navigation system in terms of both accuracy and availability.
Galileo: The Added Value for Integrity in Harsh Environments
Borio, Daniele; Gioia, Ciro
2016-01-01
A global navigation satellite system (GNSS)-based navigation is a challenging task in a signal-degraded environments where GNSS signals are distorted by multipath and attenuated by fading effects: the navigation solution may be inaccurate or unavailable. A possible approach to improve accuracy and availability is the joint use of measurements from different GNSSs and quality check algorithms; this approach is investigated here using live GPS and Galileo signals. A modified receiver autonomous integrity monitoring (RAIM) algorithm, including geometry and separability checks, is proposed to detect and exclude erroneous measurements: the multi-constellation approach provides redundant measurements, and RAIM exploits them to exclude distorted observations. The synergy between combined GPS/Galileo navigation and RAIM is analyzed using live data; the performance is compared to the accuracy and availability of a GPS-only solution. The tests performed demonstrate that the methods developed are effective techniques for GNSS-based navigation in signal-degraded environments. The joint use of the multi-constellation approach and of modified RAIM algorithms improves the performance of the navigation system in terms of both accuracy and availability. PMID:26784205
NASA Astrophysics Data System (ADS)
Beaudoin, Yanick; Desbiens, André; Gagnon, Eric; Landry, René
2018-01-01
The navigation system of a satellite launcher is of paramount importance. In order to correct the trajectory of the launcher, the position, velocity and attitude must be known with the best possible precision. In this paper, the observability of four navigation solutions is investigated. The first one is the INS/GPS couple. Then, attitude reference sensors, such as magnetometers, are added to the INS/GPS solution. The authors have already demonstrated that the reference trajectory could be used to improve the navigation performance. This approach is added to the two previously mentioned navigation systems. For each navigation solution, the observability is analyzed with different sensor error models. First, sensor biases are neglected. Then, sensor biases are modelled as random walks and as first order Markov processes. The observability is tested with the rank and condition number of the observability matrix, the time evolution of the covariance matrix and sensitivity to measurement outlier tests. The covariance matrix is exploited to evaluate the correlation between states in order to detect structural unobservability problems. Finally, when an unobservable subspace is detected, the result is verified with theoretical analysis of the navigation equations. The results show that evaluating only the observability of a model does not guarantee the ability of the aiding sensors to correct the INS estimates within the mission time. The analysis of the covariance matrix time evolution could be a powerful tool to detect this situation, however in some cases, the problem is only revealed with a sensitivity to measurement outlier test. None of the tested solutions provide GPS position bias observability. For the considered mission, the modelling of the sensor biases as random walks or Markov processes gives equivalent results. Relying on the reference trajectory can improve the precision of the roll estimates. But, in the context of a satellite launcher, the roll estimation error and gyroscope bias are only observable if attitude reference sensors are present.
National Gas Cool Times, September/October 2000.
ERIC Educational Resources Information Center
Natural Gas Cool Times, 2000
2000-01-01
Several articles are presented covering the development and use of gas/electric cooling solutions for public schools and colleges. Articles address financing issues; indoor air quality (IAQ) problems and solutions; and the analysis of heating, ventilation, and air conditioning systems. Three examples of how schools solved their cooling problems…
Lopes, Ana C; Nunes, Urbano
2009-01-01
This paper aims to present a new framework to train people with severe motor disabilities steering an assisted mobile robot (AMR), such as a powered wheelchair. Users with high level of motor disabilities are not able to use standard HMIs, which provide a continuous command signal (e. g. standard joystick). For this reason HMIs providing a small set of simple commands, which are sparse and discrete in time must be used (e. g. scanning interface, or brain computer interface), making very difficult to steer the AMR. In this sense, the assisted navigation training framework (ANTF) is designed to train users driving the AMR, in indoor structured environments, using this type of HMIs. Additionally it provides user characterization on steering the robot, which will later be used to adapt the AMR navigation system to human competence steering the AMR. A rule-based lens (RBL) model is used to characterize users on driving the AMR. Individual judgment performance choosing the best manoeuvres is modeled using a genetic-based policy capturing (GBPC) technique characterized to infer non-compensatory judgment strategies from human decision data. Three user models, at three different learning stages, using the RBL paradigm, are presented.
Development of the navigation system for the visually impaired by using white cane.
Hirahara, Yoshiaki; Sakurai, Yusuke; Shiidu, Yuriko; Yanashima, Kenji; Magatani, Kazushige
2006-01-01
A white cane is a typical support instrument for the visually impaired. They use a white cane for the detection of obstacles while walking. So, the area where they have a mental map, they can walk using white cane without help of others. However, they cannot walk independently in the unknown area, even if they use a white cane. Because, a white cane is a detecting device for obstacles and not a navigation device for there correcting route. Now, we are developing the navigation system for the visually impaired which uses indoor space. In Japan, sometimes colored guide lines to the destination are used for a normal person. These lines are attached on the floor, we can reach the destination, if we walk along one of these line. In our system, a developed new white cane senses one colored guide line, and makes notice to a user by vibration. This system recognizes the color of the line stuck on the floor by the optical sensor attached in the white cane. And in order to guide still more smoothly, infrared beacons (optical beacon), which can perform voice guidance, are also used.
Deep Coupled Integration of CSAC and GNSS for Robust PNT.
Ma, Lin; You, Zheng; Li, Bin; Zhou, Bin; Han, Runqi
2015-09-11
Global navigation satellite systems (GNSS) are the most widely used positioning, navigation, and timing (PNT) technology. However, a GNSS cannot provide effective PNT services in physical blocks, such as in a natural canyon, canyon city, underground, underwater, and indoors. With the development of micro-electromechanical system (MEMS) technology, the chip scale atomic clock (CSAC) gradually matures, and performance is constantly improved. A deep coupled integration of CSAC and GNSS is explored in this thesis to enhance PNT robustness. "Clock coasting" of CSAC provides time synchronized with GNSS and optimizes navigation equations. However, errors of clock coasting increase over time and can be corrected by GNSS time, which is stable but noisy. In this paper, weighted linear optimal estimation algorithm is used for CSAC-aided GNSS, while Kalman filter is used for GNSS-corrected CSAC. Simulations of the model are conducted, and field tests are carried out. Dilution of precision can be improved by integration. Integration is more accurate than traditional GNSS. When only three satellites are visible, the integration still works, whereas the traditional method fails. The deep coupled integration of CSAC and GNSS can improve the accuracy, reliability, and availability of PNT.
Deep Coupled Integration of CSAC and GNSS for Robust PNT
Ma, Lin; You, Zheng; Li, Bin; Zhou, Bin; Han, Runqi
2015-01-01
Global navigation satellite systems (GNSS) are the most widely used positioning, navigation, and timing (PNT) technology. However, a GNSS cannot provide effective PNT services in physical blocks, such as in a natural canyon, canyon city, underground, underwater, and indoors. With the development of micro-electromechanical system (MEMS) technology, the chip scale atomic clock (CSAC) gradually matures, and performance is constantly improved. A deep coupled integration of CSAC and GNSS is explored in this thesis to enhance PNT robustness. “Clock coasting” of CSAC provides time synchronized with GNSS and optimizes navigation equations. However, errors of clock coasting increase over time and can be corrected by GNSS time, which is stable but noisy. In this paper, weighted linear optimal estimation algorithm is used for CSAC-aided GNSS, while Kalman filter is used for GNSS-corrected CSAC. Simulations of the model are conducted, and field tests are carried out. Dilution of precision can be improved by integration. Integration is more accurate than traditional GNSS. When only three satellites are visible, the integration still works, whereas the traditional method fails. The deep coupled integration of CSAC and GNSS can improve the accuracy, reliability, and availability of PNT. PMID:26378542
IPS - a vision aided navigation system
NASA Astrophysics Data System (ADS)
Börner, Anko; Baumbach, Dirk; Buder, Maximilian; Choinowski, Andre; Ernst, Ines; Funk, Eugen; Grießbach, Denis; Schischmanow, Adrian; Wohlfeil, Jürgen; Zuev, Sergey
2017-04-01
Ego localization is an important prerequisite for several scientific, commercial, and statutory tasks. Only by knowing one's own position, can guidance be provided, inspections be executed, and autonomous vehicles be operated. Localization becomes challenging if satellite-based navigation systems are not available, or data quality is not sufficient. To overcome this problem, a team of the German Aerospace Center (DLR) developed a multi-sensor system based on the human head and its navigation sensors - the eyes and the vestibular system. This system is called integrated positioning system (IPS) and contains a stereo camera and an inertial measurement unit for determining an ego pose in six degrees of freedom in a local coordinate system. IPS is able to operate in real time and can be applied for indoor and outdoor scenarios without any external reference or prior knowledge. In this paper, the system and its key hardware and software components are introduced. The main issues during the development of such complex multi-sensor measurement systems are identified and discussed, and the performance of this technology is demonstrated. The developer team started from scratch and transfers this technology into a commercial product right now. The paper finishes with an outlook.
Study on UKF based federal integrated navigation for high dynamic aviation
NASA Astrophysics Data System (ADS)
Zhao, Gang; Shao, Wei; Chen, Kai; Yan, Jie
2011-08-01
High dynamic aircraft is a very attractive new generation vehicles, in which provides near space aviation with large flight envelope both speed and altitude, for example the hypersonic vehicles. The complex flight environments for high dynamic vehicles require high accuracy and stability navigation scheme. Since the conventional Strapdown Inertial Navigation System (SINS) and Global Position System (GPS) federal integrated scheme based on EKF (Extended Kalman Filter) is invalidation in GPS single blackout situation because of high speed flight, a new high precision and stability integrated navigation approach is presented in this paper, in which the SINS, GPS and Celestial Navigation System (CNS) is combined as a federal information fusion configuration based on nonlinear Unscented Kalman Filter (UKF) algorithm. Firstly, the new integrated system state error is modeled. According to this error model, the SINS system is used as the navigation solution mathematic platform. The SINS combine with GPS constitute one error estimation filter subsystem based on UKF to obtain local optimal estimation, and the SINS combine with CNS constitute another error estimation subsystem. A non-reset federated configuration filter based on partial information is proposed to fuse two local optimal estimations to get global optimal error estimation, and the global optimal estimation is used to correct the SINS navigation solution. The χ 2 fault detection method is used to detect the subsystem fault, and the fault subsystem is isolation through fault interval to protect system away from the divergence. The integrated system takes advantages of SINS, GPS and CNS to an immense improvement for high accuracy and reliably high dynamic navigation application. Simulation result shows that federated fusion of using GPS and CNS to revise SINS solution is reasonable and availably with good estimation performance, which are satisfied with the demands of high dynamic flight navigation. The UKF is superior than EKF based integrated scheme, in which has smaller estimation error and quickly convergence rate.
Wei, Wenhui; Gao, Zhaohui; Gao, Shesheng; Jia, Ke
2018-04-09
In order to meet the requirements of autonomy and reliability for the navigation system, combined with the method of measuring speed by using the spectral redshift information of the natural celestial bodies, a new scheme, consisting of Strapdown Inertial Navigation System (SINS)/Spectral Redshift (SRS)/Geomagnetic Navigation System (GNS), is designed for autonomous integrated navigation systems. The principle of this SINS/SRS/GNS autonomous integrated navigation system is explored, and the corresponding mathematical model is established. Furthermore, a robust adaptive central difference particle filtering algorithm is proposed for this autonomous integrated navigation system. The simulation experiments are conducted and the results show that the designed SINS/SRS/GNS autonomous integrated navigation system possesses good autonomy, strong robustness and high reliability, thus providing a new solution for autonomous navigation technology.
Performance analysis of multiple Indoor Positioning Systems in a healthcare environment.
Van Haute, Tom; De Poorter, Eli; Crombez, Pieter; Lemic, Filip; Handziski, Vlado; Wirström, Niklas; Wolisz, Adam; Voigt, Thiemo; Moerman, Ingrid
2016-02-03
The combination of an aging population and nursing staff shortages implies the need for more advanced systems in the healthcare industry. Many key enablers for the optimization of healthcare systems require provisioning of location awareness for patients (e.g. with dementia), nurses, doctors, assets, etc. Therefore, many Indoor Positioning Systems (IPSs) will be indispensable in healthcare systems. However, although many IPSs have been proposed in literature, most of these have been evaluated in non-representative environments such as office buildings rather than in a hospital. To remedy this, the paper evaluates the performance of existing IPSs in an operational modern healthcare environment: the "Sint-Jozefs kliniek Izegem" hospital in Belgium. The evaluation (data-collecting and data-processing) is executed using a standardized methodology and evaluates the point accuracy, room accuracy and latency of multiple IPSs. To evaluate the solutions, the position of a stationary device was requested at 73 evaluation locations. By using the same evaluation locations for all IPSs the performance of all systems could objectively be compared. Several trends can be identified such as the fact that Wi-Fi based fingerprinting solutions have the best accuracy result (point accuracy of 1.21 m and room accuracy of 98%) however it requires calibration before use and needs 5.43 s to estimate the location. On the other hand, proximity based solutions (based on sensor nodes) are significantly cheaper to install, do not require calibration and still obtain acceptable room accuracy results. As a conclusion of this paper, Wi-Fi based solutions have the most potential for an indoor positioning service in case when accuracy is the most important metric. Applying the fingerprinting approach with an anchor installed in every two rooms is the preferred solution for a hospital environment.
Spoofing Detection Using GNSS/INS/Odometer Coupling for Vehicular Navigation
Broumandan, Ali; Lachapelle, Gérard
2018-01-01
Location information is one of the most vital information required to achieve intelligent and context-aware capability for various applications such as driverless cars. However, related security and privacy threats are a major holdback. With increasing focus on using Global Navigation Satellite Systems (GNSS) for autonomous navigation and related applications, it is important to provide robust navigation solutions, yet signal spoofing for illegal or covert transportation and misleading receiver timing is increasing and now frequent. Hence, detection and mitigation of spoofing attacks has become an important topic. Several contributions on spoofing detection have been made, focusing on different layers of a GNSS receiver. This paper focuses on spoofing detection utilizing self-contained sensors, namely inertial measurement units (IMUs) and vehicle odometer outputs. A spoofing detection approach based on a consistency check between GNSS and IMU/odometer mechanization is proposed. To detect a spoofing attack, the method analyses GNSS and IMU/odometer measurements independently during a pre-selected observation window and cross checks the solutions provided by GNSS and inertial navigation solution (INS)/odometer mechanization. The performance of the proposed method is verified in real vehicular environments. Mean spoofing detection time and detection performance in terms of receiver operation characteristics (ROC) in sub-urban and dense urban environments are evaluated. PMID:29695064
Spoofing Detection Using GNSS/INS/Odometer Coupling for Vehicular Navigation.
Broumandan, Ali; Lachapelle, Gérard
2018-04-24
Location information is one of the most vital information required to achieve intelligent and context-aware capability for various applications such as driverless cars. However, related security and privacy threats are a major holdback. With increasing focus on using Global Navigation Satellite Systems (GNSS) for autonomous navigation and related applications, it is important to provide robust navigation solutions, yet signal spoofing for illegal or covert transportation and misleading receiver timing is increasing and now frequent. Hence, detection and mitigation of spoofing attacks has become an important topic. Several contributions on spoofing detection have been made, focusing on different layers of a GNSS receiver. This paper focuses on spoofing detection utilizing self-contained sensors, namely inertial measurement units (IMUs) and vehicle odometer outputs. A spoofing detection approach based on a consistency check between GNSS and IMU/odometer mechanization is proposed. To detect a spoofing attack, the method analyses GNSS and IMU/odometer measurements independently during a pre-selected observation window and cross checks the solutions provided by GNSS and inertial navigation solution (INS)/odometer mechanization. The performance of the proposed method is verified in real vehicular environments. Mean spoofing detection time and detection performance in terms of receiver operation characteristics (ROC) in sub-urban and dense urban environments are evaluated.
Laser-based Relative Navigation Using GPS Measurements for Spacecraft Formation Flying
NASA Astrophysics Data System (ADS)
Lee, Kwangwon; Oh, Hyungjik; Park, Han-Earl; Park, Sang-Young; Park, Chandeok
2015-12-01
This study presents a precise relative navigation algorithm using both laser and Global Positioning System (GPS) measurements in real time. The measurement model of the navigation algorithm between two spacecraft is comprised of relative distances measured by laser instruments and single differences of GPS pseudo-range measurements in spherical coordinates. Based on the measurement model, the Extended Kalman Filter (EKF) is applied to smooth the pseudo-range measurements and to obtain the relative navigation solution. While the navigation algorithm using only laser measurements might become inaccurate because of the limited accuracy of spacecraft attitude estimation when the distance between spacecraft is rather large, the proposed approach is able to provide an accurate solution even in such cases by employing the smoothed GPS pseudo-range measurements. Numerical simulations demonstrate that the errors of the proposed algorithm are reduced by more than about 12% compared to those of an algorithm using only laser measurements, as the accuracy of angular measurements is greater than 0.001° at relative distances greater than 30 km.
Maneuver Recovery Analysis for the Magnetospheric Multiscale Mission
NASA Technical Reports Server (NTRS)
Gramling, Cheryl; Carpenter, Russell; Volle, Michael; Lee, Taesul; Long, Anne
2007-01-01
The use of spacecraft formations creates new and more demanding requirements for orbit determination accuracy. In addition to absolute navigation requirements, there are typically relative navigation requirements that are based on the size or shape of the formation. The difficulty in meeting these requirements is related to the relative dynamics of the spacecraft orbits and the frequency of the formation maintenance maneuvers. This paper examines the effects of bi-weekly formation maintenance maneuvers on the absolute and relative orbit determination accuracy for the four-spacecraft Magnetospheric Multiscale (MMS) formation. Results are presented from high fidelity simulations that include the effects of realistic orbit determination errors in the maneuver planning process. Solutions are determined using a high accuracy extended Kalman filter designed for onboard navigation. Three different solutions are examined, considering the effects of process noise and measurement rate on the solutions.
Efficient coding and detection of ultra-long IDs for visible light positioning systems.
Zhang, Hualong; Yang, Chuanchuan
2018-05-14
Visible light positioning (VLP) is a promising technique to complement Global Navigation Satellite System (GNSS) such as Global positioning system (GPS) and BeiDou Navigation Satellite System (BDS) which features the advantage of low-cost and high accuracy. The situation becomes even more crucial for indoor environments, where satellite signals are weak or even unavailable. For large-scale application of VLP, there would be a considerable number of Light emitting diode (LED) IDs, which bring forward the demand of long LED ID detection. In particular, to provision indoor localization globally, a convenient way is to program a unique ID into each LED during manufacture. This poses a big challenge for image sensors, such as the CMOS camera in everybody's hands since the long ID covers the span of multiple frames. In this paper, we investigate the detection of ultra-long ID using rolling shutter cameras. By analyzing the pattern of data loss in each frame, we proposed a novel coding technique to improve the efficiency of LED ID detection. We studied the performance of Reed-Solomon (RS) code in this system and designed a new coding method which considered the trade-off between performance and decoding complexity. Coding technique decreases the number of frames needed in data processing, significantly reduces the detection time, and improves the accuracy of detection. Numerical and experimental results show that the detected LED ID can be much longer with the coding technique. Besides, our proposed coding method is proved to achieve a performance close to that of RS code while the decoding complexity is much lower.
NASA Astrophysics Data System (ADS)
Hofer, H.; Retscher, G.
2017-09-01
For Wi-Fi positioning location fingerprinting is one of the most commonly employed localization technique. To achieve an acceptable level of positioning accuracy on the few meter level, i.e., to provide at least room resolution in buildings, such an approach is very labour consuming as it requires a high density of reference points. Thus, the novel approach developed aims at a significant reduction of workload for the training phase. The basic idea is to intelligently choose waypoints along possible users' trajectories in the indoor environment. These waypoints are termed intelligent checkpoints (iCPs) and serve as reference points for the fingerprinting localization approach. They are selected along the trajectories in such a way that they define a logical sequence with their ascending order. Thereby, the iCPs are located, for instance, at doors at entrances to buildings, rooms, along corridors, etc., or in low density along the trajectory to provide a suitable absolute user localization. Continuous positioning between these iCPs is obtained with the help of the smartphones' inertial sensors. While walking along a selected trajectory to the destination a dynamic recognition of the iCPs is performed and the drift of the inertial sensors is reduced as the iCP recognition serves as absolute position update. Conducted experiments in a multi-storey office building have shown that positioning accuracy of around 2.0 m are achievable which goes along with a reduction of workload by three quarter using this novel approach. The iCP concept and performance are presented and demonstrated in this paper.
Indoor A* Pathfinding Through an Octree Representation of a Point Cloud
NASA Astrophysics Data System (ADS)
Rodenberg, O. B. P. M.; Verbree, E.; Zlatanova, S.
2016-10-01
There is a growing demand of 3D indoor pathfinding applications. Researched in the field of robotics during the last decades of the 20th century, these methods focussed on 2D navigation. Nowadays we would like to have the ability to help people navigate inside buildings or send a drone inside a building when this is too dangerous for people. What these examples have in common is that an object with a certain geometry needs to find an optimal collision free path between a start and goal point. This paper presents a new workflow for pathfinding through an octree representation of a point cloud. We applied the following steps: 1) the point cloud is processed so it fits best in an octree; 2) during the octree generation the interior empty nodes are filtered and further processed; 3) for each interior empty node the distance to the closest occupied node directly under it is computed; 4) a network graph is computed for all empty nodes; 5) the A* pathfinding algorithm is conducted. This workflow takes into account the connectivity for each node to all possible neighbours (face, edge and vertex and all sizes). Besides, a collision avoidance system is pre-processed in two steps: first, the clearance of each empty node is computed, and then the maximal crossing value between two empty neighbouring nodes is computed. The clearance is used to select interior empty nodes of appropriate size and the maximal crossing value is used to filter the network graph. Finally, both these datasets are used in A* pathfinding.
Trending Technologies for Indoor FM: Looking for "Geo" in Information
NASA Astrophysics Data System (ADS)
Gunduz, M.; Isikdag, U.; Basaraner, M.
2016-10-01
Today technological developments in the Architecture Engineering and Construction (AEC) industry provides opportunities to build huge and complex buildings and facilities. In order to operate these facilities and to meet the requirements of the occupants and also to manage energy, waste and to keep all facility services operational, several Facility Management (FM) solutions were developed. This paper starts by presenting a state of art review of research related to Indoor Facility Management Systems. Later, a textual analysis focused to identify the research trends in this field is presented in the paper. The result of the literature review and textual analysis indicates that current research in Indoor FM Systems is underestimating the role of Geoinformation, Geoinformation models and systems.
Preliminary Operational Results of the TDRSS Onboard Navigation System (TONS) for the Terra Mission
NASA Technical Reports Server (NTRS)
Gramling, Cheryl; Lorah, John; Santoro, Ernest; Work, Kevin; Chambers, Robert; Bauer, Frank H. (Technical Monitor)
2000-01-01
The Earth Observing System Terra spacecraft was launched on December 18, 1999, to provide data for the characterization of the terrestrial and oceanic surfaces, clouds, radiation, aerosols, and radiative balance. The Tracking and Data Relay Satellite System (TDRSS) Onboard Navigation System (ONS) (TONS) flying on Terra provides the spacecraft with an operational real-time navigation solution. TONS is a passive system that makes judicious use of Terra's communication and computer subsystems. An objective of the ONS developed by NASA's Goddard Space Flight Center (GSFC) Guidance, Navigation and Control Center is to provide autonomous navigation with minimal power, weight, and volume impact on the user spacecraft. TONS relies on extracting tracking measurements onboard from a TDRSS forward-link communication signal and processing these measurements in an onboard extended Kalman filter to estimate Terra's current state. Terra is the first NASA low Earth orbiting mission to fly autonomous navigation which produces accurate results. The science orbital accuracy requirements for Terra are 150 meters (m) (3sigma) per axis with a goal of 5m (1 sigma) RSS which TONS is expected to meet. The TONS solutions are telemetered in real-time to the mission scientists along with their science data for immediate processing. Once set in the operational mode, TONS eliminates the need for ground orbit determination and allows for a smooth flow from the spacecraft telemetry to planning products for the mission team. This paper will present the preliminary results of the operational TONS solution available from Terra.
Marques, Rita; Gregório, João; Pinheiro, Fernando; Póvoa, Pedro; da Silva, Miguel Mira; Lapão, Luís Velez
2017-01-31
Hospital-acquired infections are still amongst the major problems health systems are facing. Their occurrence can lead to higher morbidity and mortality rates, increased length of hospital stay, and higher costs for both hospital and patients. Performing hand hygiene is a simple and inexpensive prevention measure, but healthcare workers' compliance with it is often far from ideal. To raise awareness regarding hand hygiene compliance, individual behaviour change and performance optimization, we aimed to develop a gamification solution that collects data and provides real-time feedback accurately in a fun and engaging way. A Design Science Research Methodology (DSRM) was used to conduct this work. DSRM is useful to study the link between research and professional practices by designing, implementing and evaluating artifacts that address a specific need. It follows a development cycle (or iteration) composed by six activities. Two work iterations were performed applying gamification components, each using a different indoor location technology. Preliminary experiments, simulations and field studies were performed in an Intensive Care Unit (ICU) of a Portuguese tertiary hospital. Nurses working on this ICU were in a focus group during the research, participating in several sessions across the implementation process. Nurses enjoyed the concept and considered that it allows for a unique opportunity to receive feedback regarding their performance. Tests performed on the indoor location technology applied in the first iteration regarding distances estimation presented an unacceptable lack of accuracy. Using a proximity-based technique, it was possible to identify the sequence of positions, but beacons presented an unstable behaviour. In the second work iteration, a different indoor location technology was explored but it did not work properly, so there was no chance of testing the solution as a whole (gamification application included). Combining automated monitoring systems with gamification seems to be an innovative and promising approach, based on the already achieved results. Involving nurses in the project since the beginning allowed to align the solution with their needs. Despite strong evolution through recent years, indoor location technologies are still not ready to be applied in the healthcare field with nursing wards.
Joint JSC/GSFC two-TDRS navigation certification results for STS-29, STS-30, and STS-32
NASA Technical Reports Server (NTRS)
Schmidt, Thomas G.; Brown, Edward T.; Murdock, Valerie E.; Cappellari, James O., Jr.; Smith, Evan A.; Schmitt, Mark W.; Omalley, James W.; Lowes, Flora B.; Joyce, James B.
1990-01-01
The procedures used and the results obtained in the joint Johnson Space Center (JSC)/Goddard Space Flight Center (GSFC) navigation certification of the two-Tracking and Data Relay Satellite (TDRS) S-band tracking configuration for support of low- to medium-inclination (28.5 to 62 degrees) Shuttle missions (STS-29 and STS-30) and Shuttle rendezvous missions (STS-32) are described. The objective of this certification effort was to certify the two-TDRS configuration for nominal Space Transportation System (STS) on-orbit navigation support, thereby making it possible to significantly reduce the ground tracking support requirements for routine STS on-orbit navigation. JSC had the primary responsibility for certification of the two-TDRS configuration for STS support, and GSFC supported the effort by performing Ground Network (GN) and Space Network (SN) tracking data evaluation, parallel orbit solutions, and solution comparisons. In the certification process, two types of orbit determination solutions were generated by JSC and by GSFC for each tracking arc evaluated, one type using TDRS-East and TDRS-West tracking data combined with ground tracking data (the reference solutions) and one type using only TDRS-East and TDRS-West tracking data. The two types of solutions were then compared to determine the maximum position differences over the solution arcs and whether these differences satisfied the navigation certification criteria. The certification criteria were a function of the type of Shuttle activity in the tracking arc, i.e., quiet, moderate, or active. Quiet periods included no attitude maneuvers or ventings; moderate periods included one or two maneuvers or ventings; and active periods included more than two maneuvers or ventings. The results of the individual JSC and GSFC certification analyses for the STS-29, STS-30, and STS-32 missions and the joint JSC/GSFC conclusions regarding certification of the two-TDRS S-band configuration for STS support are presented.
The Henry’s law constant (HLC) and the overall mass transfer coefficient are both important parameters for modeling formaldehyde emissions from aqueous solutions. In this work, the apparent HLCs for aqueous formaldehyde solutions were determined in the concentration range from 0....
Wei, Wenhui; Gao, Zhaohui; Gao, Shesheng; Jia, Ke
2018-01-01
In order to meet the requirements of autonomy and reliability for the navigation system, combined with the method of measuring speed by using the spectral redshift information of the natural celestial bodies, a new scheme, consisting of Strapdown Inertial Navigation System (SINS)/Spectral Redshift (SRS)/Geomagnetic Navigation System (GNS), is designed for autonomous integrated navigation systems. The principle of this SINS/SRS/GNS autonomous integrated navigation system is explored, and the corresponding mathematical model is established. Furthermore, a robust adaptive central difference particle filtering algorithm is proposed for this autonomous integrated navigation system. The simulation experiments are conducted and the results show that the designed SINS/SRS/GNS autonomous integrated navigation system possesses good autonomy, strong robustness and high reliability, thus providing a new solution for autonomous navigation technology. PMID:29642549
Code of Federal Regulations, 2012 CFR
2012-07-01
...-(Hydroxyethyl)ethylenediamine triacetic acid, trisodium salt solution Isophorone Lactic acid Latex (ammonia (1... 33 Navigation and Navigable Waters 2 2012-07-01 2012-07-01 false Category D NLSs other than oil-like Category D NLSs that may be carried under this part. 151.47 Section 151.47 Navigation and...
Code of Federal Regulations, 2014 CFR
2014-07-01
...-(Hydroxyethyl)ethylenediamine triacetic acid, trisodium salt solution Isophorone Lactic acid Latex (ammonia (1... 33 Navigation and Navigable Waters 2 2014-07-01 2014-07-01 false Category D NLSs other than oil-like Category D NLSs that may be carried under this part. 151.47 Section 151.47 Navigation and...
Code of Federal Regulations, 2011 CFR
2011-07-01
...-(Hydroxyethyl)ethylenediamine triacetic acid, trisodium salt solution Isophorone Lactic acid Latex (ammonia (1... 33 Navigation and Navigable Waters 2 2011-07-01 2011-07-01 false Category D NLSs other than oil-like Category D NLSs that may be carried under this part. 151.47 Section 151.47 Navigation and...
Code of Federal Regulations, 2013 CFR
2013-07-01
...-(Hydroxyethyl)ethylenediamine triacetic acid, trisodium salt solution Isophorone Lactic acid Latex (ammonia (1... 33 Navigation and Navigable Waters 2 2013-07-01 2013-07-01 false Category D NLSs other than oil-like Category D NLSs that may be carried under this part. 151.47 Section 151.47 Navigation and...
Campbell, Richard; Balbach, Edith
2013-01-01
Following legal action in the 1990s, internal tobacco industry documents became public, allowing unprecedented insight into the industry's relationships with outside organizations. During the 1980s and 1990s, the National Energy Management Institute (NEMI), established by the Sheet Metal Workers International Association and the Sheet Metal and Air Conditioning Contractors' National Association, (SMACNA) received tobacco industry funding to establish an indoor air quality services program. But the arrangement also required NEMI to serve as an advocate for industry efforts to defeat indoor smoking bans by arguing that ventilation was a more appropriate solution to environmental tobacco smoke. Drawing on tobacco industry documents, this paper describes a striking example of the ethical compromises that accompanied NEMI's collaboration with the tobacco industry, highlighting the solicitation of tobacco industry financial support for a SMACNA indoor air quality manual in exchange for sanitizing references to the health impact of environmental tobacco smoke prior to publication.
California's program: Indoor air problems aren't amenable to regulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wesolowski, J.
In 1982, California's legislature established an Indoor Air Quality Program (CIAQP) in the Department of Health Services to carry out research on the nature and extent of the indoor air problem (excluding industrial worksites), to find appropriate mitigation measures, and to promote and coordinate the efforts of other state agencies. Since indoor air problems usually are not amenable to regulatory solutions, regulatory authority was not included in the mandate. The program conducts research into a wide range of contaminants--radon, asbestos, formaldehyde, carbon monoxide, volatile organic compounds, environmental tobacco smoke (ETS), as well as into biological aerosols that cause such diseasesmore » as Legionnaires disease, tuberculosis, allergies, and asthma. Studies are also carried out to better understand the Sick Building Syndrome. The research includes field surveys to determine the exposure of the population to specific contaminants and experiments in the laboratory to develop protocols for reducing exposures. The research emphasizes measurement of exposure--concentration multiplied by the time a person is exposed--as opposed to measurement of concentration only.« less
The Healthcare Needs of Latinos with Serious Mental Illness and the Potential of Peer Navigators.
Corrigan, Patrick W; Torres, Alessandra; Lara, Juana L; Sheehan, Lindsay; Larson, Jonathon E
2017-07-01
Latinos with serious mental illness get sick and die much younger than other adults. In this paper, we review findings of a community based participatory research project meant to identify important healthcare needs, barriers to these needs, solutions to the barriers, and the promise of peer navigators as a solution. Findings from focus groups reflected general concerns of people with mental illness (e.g., insurance, engagement, accessibility) and Latinos with serious mental illness (e.g., immigration, language, and family). Feedback and analyses especially focused on the potential of peer navigators. Implications of these findings for integrated care of Latinos with serious mental illness are discussed.
Multi-Sensor Fusion with Interaction Multiple Model and Chi-Square Test Tolerant Filter.
Yang, Chun; Mohammadi, Arash; Chen, Qing-Wei
2016-11-02
Motivated by the key importance of multi-sensor information fusion algorithms in the state-of-the-art integrated navigation systems due to recent advancements in sensor technologies, telecommunication, and navigation systems, the paper proposes an improved and innovative fault-tolerant fusion framework. An integrated navigation system is considered consisting of four sensory sub-systems, i.e., Strap-down Inertial Navigation System (SINS), Global Navigation System (GPS), the Bei-Dou2 (BD2) and Celestial Navigation System (CNS) navigation sensors. In such multi-sensor applications, on the one hand, the design of an efficient fusion methodology is extremely constrained specially when no information regarding the system's error characteristics is available. On the other hand, the development of an accurate fault detection and integrity monitoring solution is both challenging and critical. The paper addresses the sensitivity issues of conventional fault detection solutions and the unavailability of a precisely known system model by jointly designing fault detection and information fusion algorithms. In particular, by using ideas from Interacting Multiple Model (IMM) filters, the uncertainty of the system will be adjusted adaptively by model probabilities and using the proposed fuzzy-based fusion framework. The paper also addresses the problem of using corrupted measurements for fault detection purposes by designing a two state propagator chi-square test jointly with the fusion algorithm. Two IMM predictors, running in parallel, are used and alternatively reactivated based on the received information form the fusion filter to increase the reliability and accuracy of the proposed detection solution. With the combination of the IMM and the proposed fusion method, we increase the failure sensitivity of the detection system and, thereby, significantly increase the overall reliability and accuracy of the integrated navigation system. Simulation results indicate that the proposed fault tolerant fusion framework provides superior performance over its traditional counterparts.
Multi-Sensor Fusion with Interaction Multiple Model and Chi-Square Test Tolerant Filter
Yang, Chun; Mohammadi, Arash; Chen, Qing-Wei
2016-01-01
Motivated by the key importance of multi-sensor information fusion algorithms in the state-of-the-art integrated navigation systems due to recent advancements in sensor technologies, telecommunication, and navigation systems, the paper proposes an improved and innovative fault-tolerant fusion framework. An integrated navigation system is considered consisting of four sensory sub-systems, i.e., Strap-down Inertial Navigation System (SINS), Global Navigation System (GPS), the Bei-Dou2 (BD2) and Celestial Navigation System (CNS) navigation sensors. In such multi-sensor applications, on the one hand, the design of an efficient fusion methodology is extremely constrained specially when no information regarding the system’s error characteristics is available. On the other hand, the development of an accurate fault detection and integrity monitoring solution is both challenging and critical. The paper addresses the sensitivity issues of conventional fault detection solutions and the unavailability of a precisely known system model by jointly designing fault detection and information fusion algorithms. In particular, by using ideas from Interacting Multiple Model (IMM) filters, the uncertainty of the system will be adjusted adaptively by model probabilities and using the proposed fuzzy-based fusion framework. The paper also addresses the problem of using corrupted measurements for fault detection purposes by designing a two state propagator chi-square test jointly with the fusion algorithm. Two IMM predictors, running in parallel, are used and alternatively reactivated based on the received information form the fusion filter to increase the reliability and accuracy of the proposed detection solution. With the combination of the IMM and the proposed fusion method, we increase the failure sensitivity of the detection system and, thereby, significantly increase the overall reliability and accuracy of the integrated navigation system. Simulation results indicate that the proposed fault tolerant fusion framework provides superior performance over its traditional counterparts. PMID:27827832
Maritime User Requirements at High Latitudes - the MARENOR Project
NASA Astrophysics Data System (ADS)
Behlke, R.
2014-12-01
The ionosphere at high latitudes is characterised by a great variety of spatial and temporal variations that influence radio signals. In addition to navigation solutions that are based on Global Navigation Satellite Systems (GNSS), satellite communication systems also suffer from ionospheric degradation. This is worsened by harsh weather conditions, insufficient coverage by geostationary satellites and the absence of land-based augmentation infrastructure. Climate change will lead to a decrease in sea ice extent and thus to an increased use of trans-polar shipping routes, presence of gas and oil industries in the High Arctic and higher focus on Search-and-Rescue (SAR) as well as sovereignty issues. These moments usually require navigation and communication solutions that are accurate and reliable. We describe requirements presented by industrial operators on and around Svalbard. In addition, we present the MARENOR project that aims on evaluating navigation and communication systems at high latitudes including first results
3D Reconfigurable MPSoC for Unmanned Spacecraft Navigation
NASA Astrophysics Data System (ADS)
Dekoulis, George
2016-07-01
This paper describes the design of a new lightweight spacecraft navigation system for unmanned space missions. The system addresses the demands for more efficient autonomous navigation in the near-Earth environment or deep space. The proposed instrumentation is directly suitable for unmanned systems operation and testing of new airborne prototypes for remote sensing applications. The system features a new sensor technology and significant improvements over existing solutions. Fluxgate type sensors have been traditionally used in unmanned defense systems such as target drones, guided missiles, rockets and satellites, however, the guidance sensors' configurations exhibit lower specifications than the presented solution. The current implementation is based on a recently developed material in a reengineered optimum sensor configuration for unprecedented low-power consumption. The new sensor's performance characteristics qualify it for spacecraft navigation applications. A major advantage of the system is the efficiency in redundancy reduction achieved in terms of both hardware and software requirements.
Quantifying Uncertainties in Navigation and Orbit Propagation Analyses
NASA Technical Reports Server (NTRS)
Krieger, Andrew W.; Welch, Bryan W.
2017-01-01
A tool used to calculate dilution of precision (DOP) was created in order to assist the Space Communications and Navigation (SCaN) program to analyze current and future user missions. The SCaN Center for Engineering, Networks, Integration, and Communication (SCENIC) is developing a new user interface (UI) to augment and replace the capabilities of currently used commercial software, such as Systems Tool Kit (STK). The DOP tool will be integrated in the SCENIC UI and will be used to analyze the accuracy of navigation solutions. This tool was developed using MATLAB and free and open-source tools to save cost and to use already existing orbital software libraries. GPS DOP data was collected and used for validation purposes. The similarities between the DOP tool results and GPS data show that the DOP tool is performing correctly. Additional improvements can be made in the DOP tool to improve its accuracy and performance in analyzing navigation solutions.
Can ornamental potted plants remove volatile organic compounds from indoor air? A review.
Dela Cruz, Majbrit; Christensen, Jan H; Thomsen, Jane Dyrhauge; Müller, Renate
2014-12-01
Volatile organic compounds (VOCs) are found in indoor air, and many of these can affect human health (e.g. formaldehyde and benzene are carcinogenic). Plants affect the levels of VOCs in indoor environments, thus they represent a potential green solution for improving indoor air quality that at the same time can improve human health. This article reviews scientific studies of plants' ability to remove VOCs from indoor air. The focus of the review is on pathways of VOC removal by the plants and factors affecting the efficiency and rate of VOC removal by plants. Laboratory based studies indicate that plant induced removal of VOCs is a combination of direct (e.g. absorption) and indirect (e.g. biotransformation by microorganisms) mechanisms. They also demonstrate that plants' rate of reducing the level of VOCs is influenced by a number of factors such as plant species, light intensity and VOC concentration. For instance, an increase in light intensity has in some studies been shown to lead to an increase in removal of a pollutant. Studies conducted in real-life settings such as offices and homes are few and show mixed results.
Levasseur, Marie-Eve; Poulin, Patrick; Campagna, Céline; Leclerc, Jean-Marc
2017-11-25
A paradigm change in the management of environmental health issues has been observed in recent years: instead of managing specific risks individually, a holistic vision of environmental problems would assure sustainable solutions. However, concrete actions that could help translate these recommendations into interventions are lacking. This review presents the relevance of using an integrated indoor air quality management approach to ensure occupant health and comfort. At the nexus of three basic concepts (reducing contaminants at the source, improving ventilation, and, when relevant, purifying the indoor air), this approach can help maintain and improve indoor air quality and limit exposure to several contaminants. Its application is particularly relevant in a climate change context since the evolving outdoor conditions have to be taken into account during building construction and renovation. The measures presented through this approach target public health players, building managers, owners, occupants, and professionals involved in building design, construction, renovation, and maintenance. The findings of this review will help the various stakeholders initiate a strategic reflection on the importance of indoor air quality and climate change issues for existing and future buildings. Several new avenues and recommendations are presented to set the path for future research activities.
Levasseur, Marie-Eve; Poulin, Patrick; Campagna, Céline; Leclerc, Jean-Marc
2017-01-01
A paradigm change in the management of environmental health issues has been observed in recent years: instead of managing specific risks individually, a holistic vision of environmental problems would assure sustainable solutions. However, concrete actions that could help translate these recommendations into interventions are lacking. This review presents the relevance of using an integrated indoor air quality management approach to ensure occupant health and comfort. At the nexus of three basic concepts (reducing contaminants at the source, improving ventilation, and, when relevant, purifying the indoor air), this approach can help maintain and improve indoor air quality and limit exposure to several contaminants. Its application is particularly relevant in a climate change context since the evolving outdoor conditions have to be taken into account during building construction and renovation. The measures presented through this approach target public health players, building managers, owners, occupants, and professionals involved in building design, construction, renovation, and maintenance. The findings of this review will help the various stakeholders initiate a strategic reflection on the importance of indoor air quality and climate change issues for existing and future buildings. Several new avenues and recommendations are presented to set the path for future research activities. PMID:29186831
A low cost indoor localization system for mobile robot experimental setup
NASA Astrophysics Data System (ADS)
Adinandra, S.; Syarif, A.
2018-04-01
Indoor localization becomes one of the most important part in mobile robot system One fundamental requirement is to provide an easy-to-use and practical localization system for real-time experiments. In this paper we propose a combination of a recent open source virtual reality (VR) tools, a simple MATLAB code and a low cost USB webcam as an indoor mobile robot localization system Using the VR tools as a server and MATLAB as a client, the proposed solution can cover up to 1.6 [m] × 3.2 [m] with the measurement position accuracy up to 1.2 [cm]. The system is insensitive to light, easy to move and can be quickly set up. A series of successful real-time experiments with three different mobile robot types has been conducted.
Integration of GIS and Bim for Indoor Geovisual Analytics
NASA Astrophysics Data System (ADS)
Wu, B.; Zhang, S.
2016-06-01
This paper presents an endeavour of integration of GIS (Geographical Information System) and BIM (Building Information Modelling) for indoor geovisual analytics. The merits of two types of technologies, GIS and BIM are firstly analysed in the context of indoor environment. GIS has well-developed capabilities of spatial analysis such as network analysis, while BIM has the advantages for indoor 3D modelling and dynamic simulation. This paper firstly investigates the important aspects for integrating GIS and BIM. Different data standards and formats such as the IFC (Industry Foundation Classes) and GML (Geography Markup Language) are discussed. Their merits and limitations in data transformation between GIS and BIM are analysed in terms of semantic and geometric information. An optimized approach for data exchange between GIS and BIM datasets is then proposed. After that, a strategy of using BIM for 3D indoor modelling, GIS for spatial analysis, and BIM again for visualization and dynamic simulation of the analysis results is presented. Based on the developments, this paper selects a typical problem, optimized indoor emergency evacuation, to demonstrate the integration of GIS and BIM for indoor geovisual analytics. The block Z of the Hong Kong Polytechnic University is selected as a test site. Detailed indoor and outdoor 3D models of the block Z are created using a BIM software Revit. The 3D models are transferred to a GIS software ArcGIS to carry out spatial analysis. Optimized evacuation plans considering dynamic constraints are generated based on network analysis in ArcGIS assuming there is a fire accident inside the building. The analysis results are then transferred back to BIM software for visualization and dynamic simulation. The developed methods and results are of significance to facilitate future development of GIS and BIM integrated solutions in various applications.
Hua, Xia; Teng, Fei; Zhao, Yunxuan; Xu, Juan; Xu, Chuangye; Yang, Yang; Zhang, Qiqi; Paul, Shashi; Zhang, Yi; Chen, Mindong; Zhao, Xudong
2015-09-15
As a high-quantum-efficiency photocatalyst, the serious photo-corrosion of silver phosphate (Ag3PO4), limits the practical applications in water purification and challenges us. Herein, Ag3PO4 is found to have a high stability under natural indoor weak light irradiation, suggesting that we can employ it by adopting a new application strategy. In our studies, rhodamine B (RhB, cationic dye), methyl orange (MO, anionic dye) and RhB-MO mixture aqueous solutions are used as the probing reaction for the degradation of organic wastewater. It is found that RhB, MO and RhB-MO can be completely degraded after 28 h under natural indoor weak light irradiation, indicating that multi-component organic contaminants can be efficiently degraded by Ag3PO4 under natural indoor weak light irradiation. The density of natural indoor weak light is measured to be 72cd, which is merely one-thousandth of 300 W xenon lamp (68.2 × 10(3)cd). Most importantly, Ag3PO4 shows a high stability under natural indoor weak light irradiation, demonstrated by the formation of fairly rare Ag. Furthermore, we also investigate the influence of inorganic ions on organic dyes degradation. It shows that the Cl(-) and Cr(6+) ions with high concentrations in wastewater have significantly decreased the degradation rate. From the viewpoint of energy saving and stability, this study shows us that we can utilize the Ag-containing photocatalysts under natural indoor weak light, which could be extended to indoor air cleaning process. Copyright © 2015 Elsevier Ltd. All rights reserved.
A New Method for Single-Epoch Ambiguity Resolution with Indoor Pseudolite Positioning.
Li, Xin; Zhang, Peng; Guo, Jiming; Wang, Jinling; Qiu, Weining
2017-04-21
Ambiguity resolution (AR) is crucial for high-precision indoor pseudolite positioning. Due to the existing characteristics of the pseudolite positioning system, such as the geometry structure of the stationary pseudolite which is consistently invariant, the indoor signal is easy to interrupt and the first order linear truncation error cannot be ignored, and a new AR method based on the idea of the ambiguity function method (AFM) is proposed in this paper. The proposed method is a single-epoch and nonlinear method that is especially well-suited for indoor pseudolite positioning. Considering the very low computational efficiency of conventional AFM, we adopt an improved particle swarm optimization (IPSO) algorithm to search for the best solution in the coordinate domain, and variances of a least squares adjustment is conducted to ensure the reliability of the solving ambiguity. Several experiments, including static and kinematic tests, are conducted to verify the validity of the proposed AR method. Numerical results show that the IPSO significantly improved the computational efficiency of AFM and has a more elaborate search ability compared to the conventional grid searching method. For the indoor pseudolite system, which had an initial approximate coordinate precision better than 0.2 m, the AFM exhibited good performances in both static and kinematic tests. With the corrected ambiguity gained from our proposed method, indoor pseudolite positioning can achieve centimeter-level precision using a low-cost single-frequency software receiver.
Accuracy Analysis of a Low-Cost Platform for Positioning and Navigation
NASA Astrophysics Data System (ADS)
Hofmann, S.; Kuntzsch, C.; Schulze, M. J.; Eggert, D.; Sester, M.
2012-07-01
This paper presents an accuracy analysis of a platform based on low-cost components for landmark-based navigation intended for research and teaching purposes. The proposed platform includes a LEGO MINDSTORMS NXT 2.0 kit, an Android-based Smartphone as well as a compact laser scanner Hokuyo URG-04LX. The robot is used in a small indoor environment, where GNSS is not available. Therefore, a landmark map was produced in advance, with the landmark positions provided to the robot. All steps of procedure to set up the platform are shown. The main focus of this paper is the reachable positioning accuracy, which was analyzed in this type of scenario depending on the accuracy of the reference landmarks and the directional and distance measuring accuracy of the laser scanner. Several experiments were carried out, demonstrating the practically achievable positioning accuracy. To evaluate the accuracy, ground truth was acquired using a total station. These results are compared to the theoretically achievable accuracies and the laser scanner's characteristics.
Jiao, Sunny; Bungay, Vicky
2018-05-01
Men engaged in sex work experience significant stigma that can have devastating effects for their mental health. Little is known about how male sex workers experience stigma and its effects on mental health or their strategies to prevent its effects in the Canadian context. This study examined the interrelationships between stigma and mental health among 33 Canadian indoor, male sex workers with a specific goal of understanding how stigma affected men's mental health and their protective strategies to mitigate against its effects. Men experienced significant enacted stigma that negatively affected their social supports and ability to develop and maintain noncommercial, romantic relationships. Men navigated stigma by avoidance and resisting internalization. Strategy effectiveness to promote mental health varied based on men's perspectives of sex work as a career versus a forced source of income. Programming to promote men's mental health must take into consideration men's diverse strategies and serve to build social supports.
Thermal Image Sensing Model for Robotic Planning and Search.
Castro Jiménez, Lídice E; Martínez-García, Edgar A
2016-08-08
This work presents a search planning system for a rolling robot to find a source of infra-red (IR) radiation at an unknown location. Heat emissions are observed by a low-cost home-made IR passive visual sensor. The sensor capability for detection of radiation spectra was experimentally characterized. The sensor data were modeled by an exponential model to estimate the distance as a function of the IR image's intensity, and, a polynomial model to estimate temperature as a function of IR intensities. Both theoretical models are combined to deduce a subtle nonlinear exact solution via distance-temperature. A planning system obtains feed back from the IR camera (position, intensity, and temperature) to lead the robot to find the heat source. The planner is a system of nonlinear equations recursively solved by a Newton-based approach to estimate the IR-source in global coordinates. The planning system assists an autonomous navigation control in order to reach the goal and avoid collisions. Trigonometric partial differential equations were established to control the robot's course towards the heat emission. A sine function produces attractive accelerations toward the IR source. A cosine function produces repulsive accelerations against the obstacles observed by an RGB-D sensor. Simulations and real experiments of complex indoor are presented to illustrate the convenience and efficacy of the proposed approach.
Dhital, Anup; Bancroft, Jared B; Lachapelle, Gérard
2013-11-07
In natural and urban canyon environments, Global Navigation Satellite System (GNSS) signals suffer from various challenges such as signal multipath, limited or lack of signal availability and poor geometry. Inertial sensors are often employed to improve the solution continuity under poor GNSS signal quality and availability conditions. Various fault detection schemes have been proposed in the literature to detect and remove biased GNSS measurements to obtain a more reliable navigation solution. However, many of these methods are found to be sub-optimal and often lead to unavailability of reliability measures, mostly because of the improper characterization of the measurement errors. A robust filtering architecture is thus proposed which assumes a heavy-tailed distribution for the measurement errors. Moreover, the proposed filter is capable of adapting to the changing GNSS signal conditions such as when moving from open sky conditions to deep canyons. Results obtained by processing data collected in various GNSS challenged environments show that the proposed scheme provides a robust navigation solution without having to excessively reject usable measurements. The tests reported herein show improvements of nearly 15% and 80% for position accuracy and reliability, respectively, when applying the above approach.
Dhital, Anup; Bancroft, Jared B.; Lachapelle, Gérard
2013-01-01
In natural and urban canyon environments, Global Navigation Satellite System (GNSS) signals suffer from various challenges such as signal multipath, limited or lack of signal availability and poor geometry. Inertial sensors are often employed to improve the solution continuity under poor GNSS signal quality and availability conditions. Various fault detection schemes have been proposed in the literature to detect and remove biased GNSS measurements to obtain a more reliable navigation solution. However, many of these methods are found to be sub-optimal and often lead to unavailability of reliability measures, mostly because of the improper characterization of the measurement errors. A robust filtering architecture is thus proposed which assumes a heavy-tailed distribution for the measurement errors. Moreover, the proposed filter is capable of adapting to the changing GNSS signal conditions such as when moving from open sky conditions to deep canyons. Results obtained by processing data collected in various GNSS challenged environments show that the proposed scheme provides a robust navigation solution without having to excessively reject usable measurements. The tests reported herein show improvements of nearly 15% and 80% for position accuracy and reliability, respectively, when applying the above approach. PMID:24212120
ERIC Educational Resources Information Center
Quraishi, Arif; Kapfer, Tom
1999-01-01
Presents practical solutions to school indoor-air-quality problems. Areas where school administrators should set IAQ goals and provide resources are listed, and tips for HVAC maintenance and cleaning to reduce air pollutants are provided. (GR)
Drope, J; Bialous, S; Glantz, S
2004-01-01
Objective: To describe how the tobacco industry developed a network of consultants to promote ventilation as a "solution" to secondhand smoke (SHS) in the USA. Methods: Analysis of previously secret tobacco industry documents. Results: As with its other strategies to undermine the passage of clean indoor legislation and regulations, the tobacco industry used consultants who represented themselves as independent but who were promoting the industry's ventilation "solution" strategies under close, but generally undisclosed, industry supervision. The nature of the industry's use of ventilation consultants evolved over time. In the 1980s, the industry used them in an effort to steer the concerns about indoor air quality away from secondhand smoke, saying SHS was an insignificant component of a much larger problem of indoor air quality and inadequate ventilation. By the 1990s, the industry and its consultants were maintaining that adequate ventilation could easily accommodate "moderate smoking". The consultants carried the ventilation message to businesses, particularly the hospitality business, and to local and national and international regulatory and legislative bodies. Conclusion: While the tobacco industry and its consultants have gone to considerable lengths to promote the tobacco industry's ventilation "solution", this strategy has had limited success in the USA, probably because, in the end, it is simpler, cheaper, and healthier to end smoking. Tobacco control advocates need to continue to educate policymakers about this fact, particularly in regions where this strategy has been more effective. PMID:14985616
An Experiment with Air Purifiers in Delhi during Winter 2015-2016
Vyas, Sangita
2016-01-01
Particulate pollution has important consequences for human health, and is an issue of global concern. Outdoor air pollution has become a cause for alarm in India in particular because recent data suggest that ambient pollution levels in Indian cities are some of the highest in the world. We study the number of particles between 0.5μm and 2.5μm indoors while using affordable air purifiers in the highly polluted city of Delhi. Though substantial reductions in indoor number concentrations are observed during air purifier use, indoor air quality while using an air purifier is frequently worse than in cities with moderate pollution, and often worse than levels observed even in polluted cities. When outdoor pollution levels are higher, on average, indoor pollution levels while using an air purifier are also higher. Moreover, the ratio of indoor air quality during air purifier use to two comparison measures of air quality without an air purifier are also positively correlated with outdoor pollution levels, suggesting that as ambient air quality worsens there are diminishing returns to improvements in indoor air quality during air purifier use. The findings of this study indicate that although the most affordable air purifiers currently available are associated with significant improvements in the indoor environment, they are not a replacement for public action in regions like Delhi. Although private solutions may serve as a stopgap, reducing ambient air pollution must be a public health and policy priority in any region where air pollution is as high as Delhi’s during the winter. PMID:27978542
Evaluating gaze-driven power wheelchair with navigation support for persons with disabilities.
Wästlund, Erik; Sponseller, Kay; Pettersson, Ola; Bared, Anders
2015-01-01
This article describes a novel add-on for powered wheelchairs that is composed of a gaze-driven control system and a navigation support system. The add-on was tested by three users. All of the users were individuals with severe disabilities and no possibility of moving independently. The system is an add-on to a standard power wheelchair and can be customized for different levels of support according to the cognitive level, motor control, perceptual skills, and specific needs of the user. The primary aim of this study was to test the functionality and safety of the system in the user's home environment. The secondary aim was to evaluate whether access to a gaze-driven powered wheelchair with navigation support is perceived as meaningful in terms of independence and participation. The results show that the system has the potential to provide safe, independent indoor mobility and that the users perceive doing so as fun, meaningful, and a way to reduce dependency on others. Independent mobility has numerous benefits in addition to psychological and emotional well-being. By observing users' actions, caregivers and healthcare professionals can assess the individual's capabilities, which was not previously possible. Rehabilitation can be better adapted to the individual's specific needs, and driving a wheelchair independently can be a valuable, motivating training tool.
A signal strength priority based position estimation for mobile platforms
NASA Astrophysics Data System (ADS)
Kalgikar, Bhargav; Akopian, David; Chen, Philip
2010-01-01
Global Positioning System (GPS) products help to navigate while driving, hiking, boating, and flying. GPS uses a combination of orbiting satellites to determine position coordinates. This works great in most outdoor areas, but the satellite signals are not strong enough to penetrate inside most indoor environments. As a result, a new strain of indoor positioning technologies that make use of 802.11 wireless LANs (WLAN) is beginning to appear on the market. In WLAN positioning the system either monitors propagation delays between wireless access points and wireless device users to apply trilateration techniques or it maintains the database of location-specific signal fingerprints which is used to identify the most likely match of incoming signal data with those preliminary surveyed and saved in the database. In this paper we investigate the issue of deploying WLAN positioning software on mobile platforms with typically limited computational resources. We suggest a novel received signal strength rank order based location estimation system to reduce computational loads with a robust performance. The proposed system performance is compared to conventional approaches.
Defining indoor heat thresholds for health in the UK.
Anderson, Mindy; Carmichael, Catriona; Murray, Virginia; Dengel, Andy; Swainson, Michael
2013-05-01
It has been recognised that as outdoor ambient temperatures increase past a particular threshold, so do mortality/morbidity rates. However, similar thresholds for indoor temperatures have not yet been identified. Due to a warming climate, the non-sustainability of air conditioning as a solution, and the desire for more energy-efficient airtight homes, thresholds for indoor temperature should be defined as a public health issue. The aim of this paper is to outline the need for indoor heat thresholds and to establish if they can be identified. Our objectives include: describing how indoor temperature is measured; highlighting threshold measurements and indices; describing adaptation to heat; summary of the risk of susceptible groups to heat; reviewing the current evidence on the link between sleep, heat and health; exploring current heat and health warning systems and thresholds; exploring the built environment and the risk of overheating; and identifying the gaps in current knowledge and research. A global literature search of key databases was conducted using a pre-defined set of keywords to retrieve peer-reviewed and grey literature. The paper will apply the findings to the context of the UK. A summary of 96 articles, reports, government documents and textbooks were analysed and a gap analysis was conducted. Evidence on the effects of indoor heat on health implies that buildings are modifiers of the effect of climate on health outcomes. Personal exposure and place-based heat studies showed the most significant correlations between indoor heat and health outcomes. However, the data are sparse and inconclusive in terms of identifying evidence-based definitions for thresholds. Further research needs to be conducted in order to provide an evidence base for threshold determination. Indoor and outdoor heat are related but are different in terms of language and measurement. Future collaboration between the health and building sectors is needed to develop a common language and an index for indoor heat and health thresholds in a changing climate.
An Effective Terrain Aided Navigation for Low-Cost Autonomous Underwater Vehicles.
Zhou, Ling; Cheng, Xianghong; Zhu, Yixian; Dai, Chenxi; Fu, Jinbo
2017-03-25
Terrain-aided navigation is a potentially powerful solution for obtaining submerged position fixes for autonomous underwater vehicles. The application of terrain-aided navigation with high-accuracy inertial navigation systems has demonstrated meter-level navigation accuracy in sea trials. However, available sensors may be limited depending on the type of the mission. Such limitations, especially for low-grade navigation sensors, not only degrade the accuracy of traditional navigation systems, but further impact the ability to successfully employ terrain-aided navigation. To address this problem, a tightly-coupled navigation is presented to successfully estimate the critical sensor errors by incorporating raw sensor data directly into an augmented navigation system. Furthermore, three-dimensional distance errors are calculated, providing measurement updates through the particle filter for absolute and bounded position error. The development of the terrain aided navigation system is elaborated for a vehicle equipped with a non-inertial-grade strapdown inertial navigation system, a 4-beam Doppler Velocity Log range sensor and a sonar altimeter. Using experimental data for navigation performance evaluation in areas with different terrain characteristics, the experiment results further show that the proposed method can be successfully applied to the low-cost AUVs and significantly improves navigation performance.
An Effective Terrain Aided Navigation for Low-Cost Autonomous Underwater Vehicles
Zhou, Ling; Cheng, Xianghong; Zhu, Yixian; Dai, Chenxi; Fu, Jinbo
2017-01-01
Terrain-aided navigation is a potentially powerful solution for obtaining submerged position fixes for autonomous underwater vehicles. The application of terrain-aided navigation with high-accuracy inertial navigation systems has demonstrated meter-level navigation accuracy in sea trials. However, available sensors may be limited depending on the type of the mission. Such limitations, especially for low-grade navigation sensors, not only degrade the accuracy of traditional navigation systems, but further impact the ability to successfully employ terrain-aided navigation. To address this problem, a tightly-coupled navigation is presented to successfully estimate the critical sensor errors by incorporating raw sensor data directly into an augmented navigation system. Furthermore, three-dimensional distance errors are calculated, providing measurement updates through the particle filter for absolute and bounded position error. The development of the terrain aided navigation system is elaborated for a vehicle equipped with a non-inertial-grade strapdown inertial navigation system, a 4-beam Doppler Velocity Log range sensor and a sonar altimeter. Using experimental data for navigation performance evaluation in areas with different terrain characteristics, the experiment results further show that the proposed method can be successfully applied to the low-cost AUVs and significantly improves navigation performance. PMID:28346346
GPS aviation outage prediction and reporting systems
DOT National Transportation Integrated Search
1997-11-01
Use of GPS for instrument flight rule (IFR) air navigation requires that the system have integrity. Integrity is the ability to detect when a satellite is out of tolerance and should not be used in the navigation solution and then warns the pilot in ...
Context-Aided Sensor Fusion for Enhanced Urban Navigation
Martí, Enrique David; Martín, David; García, Jesús; de la Escalera, Arturo; Molina, José Manuel; Armingol, José María
2012-01-01
The deployment of Intelligent Vehicles in urban environments requires reliable estimation of positioning for urban navigation. The inherent complexity of this kind of environments fosters the development of novel systems which should provide reliable and precise solutions to the vehicle. This article details an advanced GNSS/IMU fusion system based on a context-aided Unscented Kalman filter for navigation in urban conditions. The constrained non-linear filter is here conditioned by a contextual knowledge module which reasons about sensor quality and driving context in order to adapt it to the situation, while at the same time it carries out a continuous estimation and correction of INS drift errors. An exhaustive analysis has been carried out with available data in order to characterize the behavior of available sensors and take it into account in the developed solution. The performance is then analyzed with an extensive dataset containing representative situations. The proposed solution suits the use of fusion algorithms for deploying Intelligent Transport Systems in urban environments. PMID:23223080
Context-aided sensor fusion for enhanced urban navigation.
Martí, Enrique David; Martín, David; García, Jesús; de la Escalera, Arturo; Molina, José Manuel; Armingol, José María
2012-12-06
The deployment of Intelligent Vehicles in urban environments requires reliable estimation of positioning for urban navigation. The inherent complexity of this kind of environments fosters the development of novel systems which should provide reliable and precise solutions to the vehicle. This article details an advanced GNSS/IMU fusion system based on a context-aided Unscented Kalman filter for navigation in urban conditions. The constrained non-linear filter is here conditioned by a contextual knowledge module which reasons about sensor quality and driving context in order to adapt it to the situation, while at the same time it carries out a continuous estimation and correction of INS drift errors. An exhaustive analysis has been carried out with available data in order to characterize the behavior of available sensors and take it into account in the developed solution. The performance is then analyzed with an extensive dataset containing representative situations. The proposed solution suits the use of fusion algorithms for deploying Intelligent Transport Systems in urban environments.
Yang, Dan; Xu, Bin; Rao, Kaiyou; Sheng, Weihua
2018-01-24
Indoor occupants' positions are significant for smart home service systems, which usually consist of robot service(s), appliance control and other intelligent applications. In this paper, an innovative localization method is proposed for tracking humans' position in indoor environments based on passive infrared (PIR) sensors using an accessibility map and an A-star algorithm, aiming at providing intelligent services. First the accessibility map reflecting the visiting habits of the occupants is established through the integral training with indoor environments and other prior knowledge. Then the PIR sensors, which placement depends on the training results in the accessibility map, get the rough location information. For more precise positioning, the A-start algorithm is used to refine the localization, fused with the accessibility map and the PIR sensor data. Experiments were conducted in a mock apartment testbed. The ground truth data was obtained from an Opti-track system. The results demonstrate that the proposed method is able to track persons in a smart home environment and provide a solution for home robot localization.
Yang, Dan; Xu, Bin; Rao, Kaiyou; Sheng, Weihua
2018-01-01
Indoor occupants’ positions are significant for smart home service systems, which usually consist of robot service(s), appliance control and other intelligent applications. In this paper, an innovative localization method is proposed for tracking humans’ position in indoor environments based on passive infrared (PIR) sensors using an accessibility map and an A-star algorithm, aiming at providing intelligent services. First the accessibility map reflecting the visiting habits of the occupants is established through the integral training with indoor environments and other prior knowledge. Then the PIR sensors, which placement depends on the training results in the accessibility map, get the rough location information. For more precise positioning, the A-start algorithm is used to refine the localization, fused with the accessibility map and the PIR sensor data. Experiments were conducted in a mock apartment testbed. The ground truth data was obtained from an Opti-track system. The results demonstrate that the proposed method is able to track persons in a smart home environment and provide a solution for home robot localization. PMID:29364188
NASA Astrophysics Data System (ADS)
Rabi, R.; Oufni, L.
2017-10-01
Inhalation of radon (222Rn) and its decay products are a major source of natural radiation exposure. It is known from recent surveys in many countries that radon and its progeny contribute significantly to total inhalation dose and it is fairly established that radon when inhaled in large quantity causes lung disorder. Indoor air conditions and ventilation systems strongly influence the indoor radon concentration. This study focuses on investigating both numerically and experimentally the influence of environmental conditions on the indoor radon concentration and spatial distribution. The numerical results showed that ventilation rate, temperature and humidity have significant impacts on both radon content and distribution. The variations of radon concentration with the ventilation, temperature and relative humidity are discussed. The measurement results show the diurnal variations of the indoor radon concentration are found to exhibit a positive correlation with relative humidity and negatively correlate with the air temperature. The analytic solution is used to validate the numeric results. The comparison amongst analytical, numerical and measurement results shows close agreement.
NASA Astrophysics Data System (ADS)
Menzione, Francesco; Renga, Alfredo; Grassi, Michele
2017-09-01
In the framework of the novel navigation scenario offered by the next generation satellite low thrust autonomous LEO-to-MEO orbit transfer, this study proposes and tests a GNSS based navigation system aimed at providing on-board precise and robust orbit determination strategy to override rising criticalities. The analysis introduces the challenging design issues to simultaneously deal with the variable orbit regime, the electric thrust control and the high orbit GNSS visibility conditions. The Consider Kalman Filtering approach is here proposed as the filtering scheme to process the GNSS raw data provided by a multi-antenna/multi-constellation receiver in presence of uncertain parameters affecting measurements, actuation and spacecraft physical properties. Filter robustness and achievable navigation accuracy are verified using a high fidelity simulation of the low-thrust rising scenario and performance are compared with the one of a standard Extended Kalman Filtering approach to highlight the advantages of the proposed solution. Performance assessment of the developed navigation solution is accomplished for different transfer phases.
NASA Astrophysics Data System (ADS)
Hesar, Siamak G.; Parker, Jeffrey S.; Leonard, Jason M.; McGranaghan, Ryan M.; Born, George H.
2015-12-01
We study the application of Linked Autonomous Interplanetary Satellite Orbit Navigation (LiAISON) to track vehicles on the far side of the lunar surface. The LiAISON architecture is demonstrated to achieve accurate orbit determination solutions for various mission scenarios in the Earth-Moon system. Given the proper description of the force field, LiAISON is capable of producing absolute orbit determination solutions using relative satellite-to-satellite tracking observations alone. The lack of direct communication between Earth-based tracking stations and the far side of the Moon provides an ideal opportunity for implementing LiAISON. This paper presents a novel approach to use the LiAISON architecture to perform autonomous navigation of assets on the lunar far side surface. Relative measurements between a spacecraft placed in an EML-2 halo orbit and lunar surface asset(s) are simulated and processed. Comprehensive simulation results show that absolute states of the surface assets are observable with an achieved accuracy of the position estimate on the order of tens of meters.
NASA Astrophysics Data System (ADS)
Nair, Binu M.; Diskin, Yakov; Asari, Vijayan K.
2012-10-01
We present an autonomous system capable of performing security check routines. The surveillance machine, the Clearpath Husky robotic platform, is equipped with three IP cameras with different orientations for the surveillance tasks of face recognition, human activity recognition, autonomous navigation and 3D reconstruction of its environment. Combining the computer vision algorithms onto a robotic machine has given birth to the Robust Artificial Intelligencebased Defense Electro-Robot (RAIDER). The end purpose of the RAIDER is to conduct a patrolling routine on a single floor of a building several times a day. As the RAIDER travels down the corridors off-line algorithms use two of the RAIDER's side mounted cameras to perform a 3D reconstruction from monocular vision technique that updates a 3D model to the most current state of the indoor environment. Using frames from the front mounted camera, positioned at the human eye level, the system performs face recognition with real time training of unknown subjects. Human activity recognition algorithm will also be implemented in which each detected person is assigned to a set of action classes picked to classify ordinary and harmful student activities in a hallway setting.The system is designed to detect changes and irregularities within an environment as well as familiarize with regular faces and actions to distinguish potentially dangerous behavior. In this paper, we present the various algorithms and their modifications which when implemented on the RAIDER serves the purpose of indoor surveillance.
Visible light communication and indoor positioning using a-SiCH device as receiver
NASA Astrophysics Data System (ADS)
Vieira, M. A.; Vieira, M.; Louro, P.; Vieira, P.; Fantoni, A.
2017-08-01
An indoor positioning system were trichromatic white LEDs are used both for illumination proposes and as transmitters and an optical processor, based on a-SiC:H technology, as mobile receiver is presented. OOK modulation scheme is used, and it provides a good trade-off between system performance and implementation complexity. The relationship between the transmitted data and the received digital output levels is decoded. The system topology for positioning is a self-positioning system in which the measuring unit is mobile. This unit receives the signals of several transmitters in known locations, and has the capability to compute its location based on the measured signals. LED bulbs work as transmitters, sending information together with different IDs related to their physical locations. A triangular topology for the unit cell is analysed. A 2D localization design, demonstrated by a prototype implementation is presented. Fine-grained indoor localization is tested. The received signal is used in coded multiplexing techniques for supporting communications and navigation concomitantly on the same channel. The position is estimated through the visible multilateration metodh using several non-collinear transmitters. The location and motion information is found by mapping position and estimates the location areas. Data analysis showed that by using a pinpin double photodiode based on a a-SiC:H heterostucture as receiver, and RBGLEDs as transmitters it is possible not only to determine the mobile target's position but also to infer the motion direction over time, along with the received information in each position.
Automatically Determining Scale Within Unstructured Point Clouds
NASA Astrophysics Data System (ADS)
Kadamen, Jayren; Sithole, George
2016-06-01
Three dimensional models obtained from imagery have an arbitrary scale and therefore have to be scaled. Automatically scaling these models requires the detection of objects in these models which can be computationally intensive. Real-time object detection may pose problems for applications such as indoor navigation. This investigation poses the idea that relational cues, specifically height ratios, within indoor environments may offer an easier means to obtain scales for models created using imagery. The investigation aimed to show two things, (a) that the size of objects, especially the height off ground is consistent within an environment, and (b) that based on this consistency, objects can be identified and their general size used to scale a model. To test the idea a hypothesis is first tested on a terrestrial lidar scan of an indoor environment. Later as a proof of concept the same test is applied to a model created using imagery. The most notable finding was that the detection of objects can be more readily done by studying the ratio between the dimensions of objects that have their dimensions defined by human physiology. For example the dimensions of desks and chairs are related to the height of an average person. In the test, the difference between generalised and actual dimensions of objects were assessed. A maximum difference of 3.96% (2.93cm) was observed from automated scaling. By analysing the ratio between the heights (distance from the floor) of the tops of objects in a room, identification was also achieved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rudd, A.
This document covers a description of the need and applied solutions for supplemental dehumidification in warm-humid climates, especially for energy efficient homes where the sensible cooling load has been dramatically reduced. In older homes in warm-humid climates, cooling loads are typically high and cooling equipment runs a lot to cool the air. The cooling process also removes indoor moisture, reducing indoor relative humidity. However, at current residential code levels, and especially for above-code programs, sensible cooling loads have been so dramatically reduced that the cooling system does not run a lot to cool the air, resulting in much less moisturemore » being removed. In these new homes, cooling equipment is off for much longer periods of time especially during spring/fall seasons, summer shoulder months, rainy periods, some summer nights, and some winter days. In warm-humid climates, those long off periods allow indoor humidity to become elevated due to internally generated moisture and ventilation air change. Elevated indoor relative humidity impacts comfort, indoor air quality, and building material durability. Industry is responding with supplemental dehumidification options, but that effort is really in its infancy regarding year-round humidity control in low-energy homes. Available supplemental humidity control options are discussed. Some options are less expensive but may not control indoor humidity as well as more expensive and comprehensive options. The best performing option is one that avoids overcooling and avoids adding unnecessary heat to the space by using waste heat from the cooling system to reheat the cooled and dehumidified air to room-neutral temperature.« less
Light use efficiency for vegetables production in protected and indoor environments
NASA Astrophysics Data System (ADS)
Cocetta, Giacomo; Casciani, Daria; Bulgari, Roberta; Musante, Fulvio; Kołton, Anna; Rossi, Maurizio; Ferrante, Antonio
2017-01-01
In recent years, there is a growing interest for vegetables production in indoor or disadvantaged climatic zones by using greenhouses. The main problem of crop growing indoor or in environment with limited light availability is the correct choice of light source and the quality of lighting spectrum. In greenhouse and indoor cultivations, plant density is higher than in the open field and plants have to compete for light and nutrients. Nowadays, advanced systems for indoor horticulture use light emitting diodes (LED) for improving crop growth, enhancing the plant productivity and favouring the best nutritional quality formation. In closed environments, as indoor growing modules, the lighting system represents the only source of light and its features are fundamental for obtaining the best lighting performances for plant and the most efficient solution. LED lighting engines are more efficient compared to the lighting sources used traditionally in horticulture and allow light spectrum and intensity modulations to enhance the light use efficiency for plants. The lighting distribution and the digital controls are fundamental for tailoring the spectral distribution on each plant in specific moments of its growth and play an important role for optimizing growth and produce high-quality vegetables. LED lights can increase plant growth and yield, but also nutraceutical quality, since some light intensities increase pigments biosynthesis and enhance the antioxidants content of leaves or fruits: in this regards the selection of LED primary light sources in relation to the peaks of the absorbance curve of the plants is important.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rudd, Armin
This document covers a description of the need and applied solutions for supplemental dehumidification in warm-humid climates, especially for energy efficient homes where the sensible cooling load has been dramatically reduced. Cooling loads are typically high and cooling equipment runs a lot to cool the air in older homes in warm-humid climates. The cooling process also removes indoor moisture, reducing indoor relative humidity. However, at current residential code levels, and especially for above-code programs, sensible cooling loads have been so dramatically reduced that the cooling system does not run a lot to cool the air, resulting in much less moisturemore » being removed. In these new homes, cooling equipment is off for much longer periods of time especially during spring/fall seasons, summer shoulder months, rainy periods, some summer nights, and winter days. In warm-humid climates, those long-off periods allow indoor humidity to become elevated due to internally generated moisture and ventilation air change. Elevated indoor relative humidity impacts comfort, indoor air quality, and building material durability. Industry is responding with supplemental dehumidification options, but that effort is really in its infancy regarding year-round humidity control in low-energy homes. Available supplemental humidity control options are discussed. Some options are less expensive but may not control indoor humidity as well as more expensive and comprehensive options. The best performing option is one that avoids overcooling and adding unnecessary heat to the space by using waste heat from the cooling system to reheat the cooled and dehumidified air to room-neutral temperature.« less
Precise point positioning with the BeiDou navigation satellite system.
Li, Min; Qu, Lizhong; Zhao, Qile; Guo, Jing; Su, Xing; Li, Xiaotao
2014-01-08
By the end of 2012, China had launched 16 BeiDou-2 navigation satellites that include six GEOs, five IGSOs and five MEOs. This has provided initial navigation and precise pointing services ability in the Asia-Pacific regions. In order to assess the navigation and positioning performance of the BeiDou-2 system, Wuhan University has built up a network of BeiDou Experimental Tracking Stations (BETS) around the World. The Position and Navigation Data Analyst (PANDA) software was modified to determine the orbits of BeiDou satellites and provide precise orbit and satellite clock bias products from the BeiDou satellite system for user applications. This article uses the BeiDou/GPS observations of the BeiDou Experimental Tracking Stations to realize the BeiDou and BeiDou/GPS static and kinematic precise point positioning (PPP). The result indicates that the precision of BeiDou static and kinematic PPP reaches centimeter level. The precision of BeiDou/GPS kinematic PPP solutions is improved significantly compared to that of BeiDou-only or GPS-only kinematic PPP solutions. The PPP convergence time also decreases with the use of combined BeiDou/GPS systems.
Precise Point Positioning with the BeiDou Navigation Satellite System
Li, Min; Qu, Lizhong; Zhao, Qile; Guo, Jing; Su, Xing; Li, Xiaotao
2014-01-01
By the end of 2012, China had launched 16 BeiDou-2 navigation satellites that include six GEOs, five IGSOs and five MEOs. This has provided initial navigation and precise pointing services ability in the Asia-Pacific regions. In order to assess the navigation and positioning performance of the BeiDou-2 system, Wuhan University has built up a network of BeiDou Experimental Tracking Stations (BETS) around the World. The Position and Navigation Data Analyst (PANDA) software was modified to determine the orbits of BeiDou satellites and provide precise orbit and satellite clock bias products from the BeiDou satellite system for user applications. This article uses the BeiDou/GPS observations of the BeiDou Experimental Tracking Stations to realize the BeiDou and BeiDou/GPS static and kinematic precise point positioning (PPP). The result indicates that the precision of BeiDou static and kinematic PPP reaches centimeter level. The precision of BeiDou/GPS kinematic PPP solutions is improved significantly compared to that of BeiDou-only or GPS-only kinematic PPP solutions. The PPP convergence time also decreases with the use of combined BeiDou/GPS systems. PMID:24406856
Chu, Tianxing; Guo, Ningyan; Backén, Staffan; Akos, Dennis
2012-01-01
Low-cost MEMS-based IMUs, video cameras and portable GNSS devices are commercially available for automotive applications and some manufacturers have already integrated such facilities into their vehicle systems. GNSS provides positioning, navigation and timing solutions to users worldwide. However, signal attenuation, reflections or blockages may give rise to positioning difficulties. As opposed to GNSS, a generic IMU, which is independent of electromagnetic wave reception, can calculate a high-bandwidth navigation solution, however the output from a self-contained IMU accumulates errors over time. In addition, video cameras also possess great potential as alternate sensors in the navigation community, particularly in challenging GNSS environments and are becoming more common as options in vehicles. Aiming at taking advantage of these existing onboard technologies for ground vehicle navigation in challenging environments, this paper develops an integrated camera/IMU/GNSS system based on the extended Kalman filter (EKF). Our proposed integration architecture is examined using a live dataset collected in an operational traffic environment. The experimental results demonstrate that the proposed integrated system provides accurate estimations and potentially outperforms the tightly coupled GNSS/IMU integration in challenging environments with sparse GNSS observations.
Monocular Camera/IMU/GNSS Integration for Ground Vehicle Navigation in Challenging GNSS Environments
Chu, Tianxing; Guo, Ningyan; Backén, Staffan; Akos, Dennis
2012-01-01
Low-cost MEMS-based IMUs, video cameras and portable GNSS devices are commercially available for automotive applications and some manufacturers have already integrated such facilities into their vehicle systems. GNSS provides positioning, navigation and timing solutions to users worldwide. However, signal attenuation, reflections or blockages may give rise to positioning difficulties. As opposed to GNSS, a generic IMU, which is independent of electromagnetic wave reception, can calculate a high-bandwidth navigation solution, however the output from a self-contained IMU accumulates errors over time. In addition, video cameras also possess great potential as alternate sensors in the navigation community, particularly in challenging GNSS environments and are becoming more common as options in vehicles. Aiming at taking advantage of these existing onboard technologies for ground vehicle navigation in challenging environments, this paper develops an integrated camera/IMU/GNSS system based on the extended Kalman filter (EKF). Our proposed integration architecture is examined using a live dataset collected in an operational traffic environment. The experimental results demonstrate that the proposed integrated system provides accurate estimations and potentially outperforms the tightly coupled GNSS/IMU integration in challenging environments with sparse GNSS observations. PMID:22736999
Indoor Air Quality Problem Solving Tool
Use the IAQ Problem Solving Tool to learn about the connection between health complaints and common solutions in schools. This resource provides an easy, step-by-step process to start identifying and resolving IAQ problems found at your school.
A statistical characterization of the Galileo-to-GPS inter-system bias
NASA Astrophysics Data System (ADS)
Gioia, Ciro; Borio, Daniele
2016-11-01
Global navigation satellite system operates using independent time scales and thus inter-system time offsets have to be determined to enable multi-constellation navigation solutions. GPS/Galileo inter-system bias and drift are evaluated here using different types of receivers: two mass market and two professional receivers. Moreover, three different approaches are considered for the inter-system bias determination: in the first one, the broadcast Galileo to GPS time offset is used to align GPS and Galileo time scales. In the second, the inter-system bias is included in the multi-constellation navigation solution and is estimated using the measurements available. Finally, an enhanced algorithm using constraints on the inter-system bias time evolution is proposed. The inter-system bias estimates obtained with the different approaches are analysed and their stability is experimentally evaluated using the Allan deviation. The impact of the inter-system bias on the position velocity time solution is also considered and the performance of the approaches analysed is evaluated in terms of standard deviation and mean errors for both horizontal and vertical components. From the experiments, it emerges that the inter-system bias is very stable and that the use of constraints, modelling the GPS/Galileo inter-system bias behaviour, significantly improves the performance of multi-constellation navigation.
Action tagging in a multi-user indoor environment for behavioural analysis purposes.
Guerra, Claudio; Bianchi, Valentina; De Munari, Ilaria; Ciampolini, Paolo
2015-01-01
EU population is getting older, so that ICT-based solutions are expected to provide support in the challenges implied by the demographic change. At the University of Parma an AAL (Ambient Assisted Living) system, named CARDEA, has been developed. In this paper a new feature of the system is introduced, in which environmental and personal (i.e., wearable) sensors coexist, providing an accurate picture of the user's activity and needs. Environmental devices may greatly help in performing activity recognition and behavioral analysis tasks. However, in a multi-user environment, this implies the need of attributing environmental sensors outcome to a specific user, i.e., identifying the user when he performs a task detected by an environmental device. We implemented such an "action tagging" feature, based on information fusion, within the CARDEA environment, as an inexpensive, alternative solution to the problematic issue of indoor locationing.
NA-241_Quarterly Report_SBLibby - 12.31.2017_v2
DOE Office of Scientific and Technical Information (OSTI.GOV)
Libby, Stephen B.
This is an evaluation of candidate navigation solutions for GPS free inspection tools that can be used in tours of large building interiors. In principle, COTS portable inertial motion unit (IMU) sensors with satisfactory accuracy, SWAP (size, weight, power), low error, and bias drift can provide sufficiently accurate dead reckoning navigation in a large building in the absence of GPS. To explore this assumption, the capabilities of representative IMU navigation sensors to meet these requirements will be evaluated, starting with a market survey, and then carrying out a basic analysis of these sensors using LLNL’s navigation codes.
Sun, Xinlu; Chong, Heap-Yih; Liao, Pin-Chao
2018-06-25
Navigated inspection seeks to improve hazard identification (HI) accuracy. With tight inspection schedule, HI also requires efficiency. However, lacking quantification of HI efficiency, navigated inspection strategies cannot be comprehensively assessed. This work aims to determine inspection efficiency in navigated safety inspection, controlling for the HI accuracy. Based on a cognitive method of the random search model (RSM), an experiment was conducted to observe the HI efficiency in navigation, for a variety of visual clutter (VC) scenarios, while using eye-tracking devices to record the search process and analyze the search performance. The results show that the RSM is an appropriate instrument, and VC serves as a hazard classifier for navigation inspection in improving inspection efficiency. This suggests a new and effective solution for addressing the low accuracy and efficiency of manual inspection through navigated inspection involving VC and the RSM. It also provides insights into the inspectors' safety inspection ability.
Oliver, L C; Shackleton, B W
1998-01-01
Increasingly recognized as a potential public health problem since the outbreak of Legionnaire's disease in Philadelphia in 1976, polluted indoor air has been associated with health problems that include asthma, sick building syndrome, multiple chemical sensitivity, and hypersensitivity pneumonitis. Symptoms are often nonspecific and include headache, eye and throat irritation, chest tightness and shortness of breath, and fatigue. Air-borne contaminants include commonly used chemicals, vehicular exhaust, microbial organisms, fibrous glass particles, and dust. Identified causes include defective building design and construction, aging of buildings and their ventilation systems, poor climate control, inattention to building maintenance. A major contributory factor is the explosion in the use of chemicals in building construction and furnishing materials over the past four decades. Organizational issues and psychological variables often contribute to the problem and hinder its resolution. This article describes the health problems related to poor indoor air quality and offers solutions. Images p398-a p399-a PMID:9769764
Hygrothermal Analysis of Indoor Environment of Residential Prefabricated Buildings
NASA Astrophysics Data System (ADS)
Kraus, Michal
2017-10-01
Recent studies show that the relative humidity and the indoor air temperature constitute an important determinant of the quality of indoor air. Hygrothermal microclimate has a significant impact on occupant’s health and their comfort. The study presents the results of experimental measurement of indoor air temperature and relative humidity in selected apartment in prefabricated panel house situated in Ostrava, Czechia. The contribution describes and analysis the relation between indoor air temperature [°C] and relative humidity [%] in this apartment. The experimental object is selected with respect to the housing stock in the Czech Republic. A third of the housing stock in the Czech Republic is composed of prefabricated panel houses. Regeneration and revitalization of these buildings were in the focus of interest during recent years. Building modifications, such as thermal insulation of building envelope or window replacement, lead to a significantly higher level of airtightness of these objects. Humidity and indoor air temperature are measured in 10-minute cycles for two periods. The values of temperature and humidity are measured for the non-heating and the heating season. The length of each experimental period is 30 days. The mean value of indoor air temperature is 22.21 °C and average relative humidity is 45.87% in the non-heating period. The values of 22.62 °C and 35.20% represent average values for the heating period. A slight increase of the average temperature of the indoor environment (+1.85%) is observed. The decrease of the relative humidity is evident at first glance. The relative humidity of the internal environment is approximately 10% lower in the heating period. Long-term decline of relative humidity below 30% brings many problems. It is necessary to take measures to increase of relative humidity in residential prefabricated building. The aquarium appears to be ineffective. The solution may be forced artificial ventilation or humidifiers.
Ego-motion based on EM for bionic navigation
NASA Astrophysics Data System (ADS)
Yue, Xiaofeng; Wang, L. J.; Liu, J. G.
2015-12-01
Researches have proved that flying insects such as bees can achieve efficient and robust flight control, and biologists have explored some biomimetic principles regarding how they control flight. Based on those basic studies and principles acquired from the flying insects, this paper proposes a different solution of recovering ego-motion for low level navigation. Firstly, a new type of entropy flow is provided to calculate the motion parameters. Secondly, EKF, which has been used for navigation for some years to correct accumulated error, and estimation-Maximization, which is always used to estimate parameters, are put together to determine the ego-motion estimation of aerial vehicles. Numerical simulation on MATLAB has proved that this navigation system provides more accurate position and smaller mean absolute error than pure optical flow navigation. This paper has done pioneering work in bionic mechanism to space navigation.
NASA Technical Reports Server (NTRS)
Balabanovic, Marko; Becker, Craig; Morse, Sarah K.; Nourbakhsh, Illah R.
1994-01-01
The success of every mobile robot application hinges on the ability to navigate robustly in the real world. The problem of robust navigation is separable from the challenges faced by any particular robot application. We offer the Real-World Navigator as a solution architecture that includes a path planner, a map-based localizer, and a motion control loop that combines reactive avoidance modules with deliberate goal-based motion. Our architecture achieves a high degree of reliability by maintaining and reasoning about an explicit description of positional uncertainty. We provide two implementations of real-world robot systems that incorporate the Real-World Navigator. The Vagabond Project culminated in a robot that successfully navigated a portion of the Stanford University campus. The Scimmer project developed successful entries for the AIAA 1993 Robotics Competition, placing first in one of the two contests entered.
Orion Optical Navigation for Loss of Communication Lunar Return Contingencies
NASA Technical Reports Server (NTRS)
Getchius, Joel; Hanak, Chad; Kubitschek, Daniel G.
2010-01-01
The Orion Crew Exploration Vehicle (CEV) will replace the Space Shuttle and serve as the next-generation spaceship to carry humans back to the Moon for the first time since the Apollo program. For nominal lunar mission operations, the Mission Control Navigation team will utilize radiometric measurements to determine the position and velocity of Orion and uplink state information to support Lunar return. However, in the loss of communications contingency return scenario, Orion must safely return the crew to the Earth's surface. The navigation design solution for this loss of communications scenario is optical navigation consisting of lunar landmark tracking in low lunar orbit and star- horizon angular measurements coupled with apparent planetary diameter for Earth return trajectories. This paper describes the optical measurement errors and the navigation filter that will process those measurements to support navigation for safe crew return.
Indoor source apportionment in urban communities near industrial sites
NASA Astrophysics Data System (ADS)
Tunno, Brett J.; Dalton, Rebecca; Cambal, Leah; Holguin, Fernando; Lioy, Paul; Clougherty, Jane E.
2016-08-01
Because fine particulate matter (PM2.5) differs in chemical composition, source apportionment is frequently used for identification of relative contributions of multiple sources to outdoor concentrations. Indoor air pollution and source apportionment is often overlooked, though people in northern climates may spend up to 90% of their time inside. We selected 21 homes for a 1-week indoor sampling session during summer (July to September 2011), repeated in winter (January to March 2012). Elemental analysis was performed using inductively-coupled plasma mass spectrometry (ICP-MS), and factor analysis was used to determine constituent grouping. Multivariate modeling was run on factor scores to corroborate interpretations of source factors based on a literature review. For each season, a 5-factor solution explained 86-88% of variability in constituent concentrations. Indoor sources (i.e. cooking, smoking) explained greater variability than did outdoor sources in these industrial communities. A smoking factor was identified in each season, predicted by number of cigarettes smoked. Cooking factors were also identified in each season, explained by frequency of stove cooking and stovetop frying. Significant contributions from outdoor sources including coal and motor vehicles were also identified. Higher coal and secondary-related elemental concentrations were detected during summer than winter. Our findings suggest that source contributions to indoor concentrations can be identified and should be examined in relation to health effects.
A Visual-Based Approach for Indoor Radio Map Construction Using Smartphones.
Liu, Tao; Zhang, Xing; Li, Qingquan; Fang, Zhixiang
2017-08-04
Localization of users in indoor spaces is a common issue in many applications. Among various technologies, a Wi-Fi fingerprinting based localization solution has attracted much attention, since it can be easily deployed using the existing off-the-shelf mobile devices and wireless networks. However, the collection of the Wi-Fi radio map is quite labor-intensive, which limits its potential for large-scale application. In this paper, a visual-based approach is proposed for the construction of a radio map in anonymous indoor environments. This approach collects multi-sensor data, e.g., Wi-Fi signals, video frames, inertial readings, when people are walking in indoor environments with smartphones in their hands. Then, it spatially recovers the trajectories of people by using both visual and inertial information. Finally, it estimates the location of fingerprints from the trajectories and constructs a Wi-Fi radio map. Experiment results show that the average location error of the fingerprints is about 0.53 m. A weighted k-nearest neighbor method is also used to evaluate the constructed radio map. The average localization error is about 3.2 m, indicating that the quality of the constructed radio map is at the same level as those constructed by site surveying. However, this approach can greatly reduce the human labor cost, which increases the potential for applying it to large indoor environments.
NASA Astrophysics Data System (ADS)
Tashakkori, H.; Rajabifard, A.; Kalantari, M.
2016-10-01
Search and rescue procedures for indoor environments are quite complicated due to the fact that much of the indoor information is unavailable to rescuers before physical entrance to the incident scene. Thus, decision making regarding the number of crew required and the way they should be dispatched in the building considering the various access points and complexities in the buildings in order to cover the search area in minimum time is dependent on prior knowledge and experience of the emergency commanders. Hence, this paper introduces the Search and Rescue Problem (SRP) which aims at finding best search and rescue routes that minimize the overall search time in the buildings. 3D BIM-oriented indoor GIS is integrated in the indoor route graph to find accurate routes based on the building geometric and semantic information. An Ant Colony Based Algorithm is presented that finds the number of first responders required and their individual routes to search all rooms and points of interest inside the building to minimize the overall time spent by all rescuers inside the disaster area. The evaluation of the proposed model for a case study building shows a significant improve in search and rescue time which will lead to a higher chance of saving lives and less exposure of emergency crew to danger.
NASA Astrophysics Data System (ADS)
Celik, Koray
This thesis presents a novel robotic navigation strategy by using a conventional tactical monocular camera, proving the feasibility of using a monocular camera as the sole proximity sensing, object avoidance, mapping, and path-planning mechanism to fly and navigate small to medium scale unmanned rotary-wing aircraft in an autonomous manner. The range measurement strategy is scalable, self-calibrating, indoor-outdoor capable, and has been biologically inspired by the key adaptive mechanisms for depth perception and pattern recognition found in humans and intelligent animals (particularly bats), designed to assume operations in previously unknown, GPS-denied environments. It proposes novel electronics, aircraft, aircraft systems, systems, and procedures and algorithms that come together to form airborne systems which measure absolute ranges from a monocular camera via passive photometry, mimicking that of a human-pilot like judgement. The research is intended to bridge the gap between practical GPS coverage and precision localization and mapping problem in a small aircraft. In the context of this study, several robotic platforms, airborne and ground alike, have been developed, some of which have been integrated in real-life field trials, for experimental validation. Albeit the emphasis on miniature robotic aircraft this research has been tested and found compatible with tactical vests and helmets, and it can be used to augment the reliability of many other types of proximity sensors.
Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor.
Huang, Lvwen; Chen, Siyuan; Zhang, Jianfeng; Cheng, Bang; Liu, Mingqing
2017-08-23
Object tracking is a crucial research subfield in computer vision and it has wide applications in navigation, robotics and military applications and so on. In this paper, the real-time visualization of 3D point clouds data based on the VLP-16 3D Light Detection and Ranging (LiDAR) sensor is achieved, and on the basis of preprocessing, fast ground segmentation, Euclidean clustering segmentation for outliers, View Feature Histogram (VFH) feature extraction, establishing object models and searching matching a moving spherical target, the Kalman filter and adaptive particle filter are used to estimate in real-time the position of a moving spherical target. The experimental results show that the Kalman filter has the advantages of high efficiency while adaptive particle filter has the advantages of high robustness and high precision when tested and validated on three kinds of scenes under the condition of target partial occlusion and interference, different moving speed and different trajectories. The research can be applied in the natural environment of fruit identification and tracking, robot navigation and control and other fields.
Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor
Chen, Siyuan; Zhang, Jianfeng; Cheng, Bang; Liu, Mingqing
2017-01-01
Object tracking is a crucial research subfield in computer vision and it has wide applications in navigation, robotics and military applications and so on. In this paper, the real-time visualization of 3D point clouds data based on the VLP-16 3D Light Detection and Ranging (LiDAR) sensor is achieved, and on the basis of preprocessing, fast ground segmentation, Euclidean clustering segmentation for outliers, View Feature Histogram (VFH) feature extraction, establishing object models and searching matching a moving spherical target, the Kalman filter and adaptive particle filter are used to estimate in real-time the position of a moving spherical target. The experimental results show that the Kalman filter has the advantages of high efficiency while adaptive particle filter has the advantages of high robustness and high precision when tested and validated on three kinds of scenes under the condition of target partial occlusion and interference, different moving speed and different trajectories. The research can be applied in the natural environment of fruit identification and tracking, robot navigation and control and other fields. PMID:28832520
Comparison of Factorization-Based Filtering for Landing Navigation
NASA Technical Reports Server (NTRS)
McCabe, James S.; Brown, Aaron J.; DeMars, Kyle J.; Carson, John M., III
2017-01-01
This paper develops and analyzes methods for fusing inertial navigation data with external data, such as data obtained from an altimeter and a star camera. The particular filtering techniques are based upon factorized forms of the Kalman filter, specifically the UDU and Cholesky factorizations. The factorized Kalman filters are utilized to ensure numerical stability of the navigation solution. Simulations are carried out to compare the performance of the different approaches along a lunar descent trajectory using inertial and external data sources. It is found that the factorized forms improve upon conventional filtering techniques in terms of ensuring numerical stability for the investigated landing navigation scenario.
A simplified satellite navigation system for an autonomous Mars roving vehicle.
NASA Technical Reports Server (NTRS)
Janosko, R. E.; Shen, C. N.
1972-01-01
The use of a retroflecting satellite and a laser rangefinder to navigate a Martian roving vehicle is considered in this paper. It is shown that a simple system can be employed to perform this task. An error analysis is performed on the navigation equations and it is shown that the error inherent in the scheme proposed can be minimized by the proper choice of measurement geometry. A nonlinear programming approach is used to minimize the navigation error subject to constraints that are due to geometric and laser requirements. The problem is solved for a particular set of laser parameters and the optimal solution is presented.
Taux: A System for Evaluating Sound Feedback in Navigational Tasks
ERIC Educational Resources Information Center
Lutz, Robert J.
2008-01-01
This thesis presents the design and development of an evaluation system for generating audio displays that provide feedback to persons performing navigation tasks. It first develops the need for such a system by describing existing wayfinding solutions, investigating new electronic location-based methods that have the potential of changing these…
Gyroscope-reduced inertial navigation system for flight vehicle motion estimation
NASA Astrophysics Data System (ADS)
Wang, Xin; Xiao, Lu
2017-01-01
In this paper, a novel configuration of strategically distributed accelerometer sensors with the aid of one gyro to infer a flight vehicle's angular motion is presented. The MEMS accelerometer and gyro sensors are integrated to form a gyroscope-reduced inertial measurement unit (GR-IMU). The motivation for gyro aided accelerometers array is to have direct measurements of angular rates, which is an improvement to the traditional gyroscope-free inertial system that employs only direct measurements of specific force. Some technical issues regarding error calibration in accelerometers and gyro in GR-IMU are put forward. The GR-IMU based inertial navigation system can be used to find a complete attitude solution for flight vehicle motion estimation. Results of numerical simulation are given to illustrate the effectiveness of the proposed configuration. The gyroscope-reduced inertial navigation system based on distributed accelerometer sensors can be developed into a cost effective solution for a fast reaction, MEMS based motion capture system. Future work will include the aid from external navigation references (e.g. GPS) to improve long time mission performance.
NASA Astrophysics Data System (ADS)
Müller, M. S.; Urban, S.; Jutzi, B.
2017-08-01
The number of unmanned aerial vehicles (UAVs) is increasing since low-cost airborne systems are available for a wide range of users. The outdoor navigation of such vehicles is mostly based on global navigation satellite system (GNSS) methods to gain the vehicles trajectory. The drawback of satellite-based navigation are failures caused by occlusions and multi-path interferences. Beside this, local image-based solutions like Simultaneous Localization and Mapping (SLAM) and Visual Odometry (VO) can e.g. be used to support the GNSS solution by closing trajectory gaps but are computationally expensive. However, if the trajectory estimation is interrupted or not available a re-localization is mandatory. In this paper we will provide a novel method for a GNSS-free and fast image-based pose regression in a known area by utilizing a small convolutional neural network (CNN). With on-board processing in mind, we employ a lightweight CNN called SqueezeNet and use transfer learning to adapt the network to pose regression. Our experiments show promising results for GNSS-free and fast localization.
Using multiple IMUs in a stacked filter configuration for calibration and fine alignment
NASA Astrophysics Data System (ADS)
El-Osery, Aly; Bruder, Stephen; Wedeward, Kevin
2018-05-01
Determination of a vehicle or person's position and/or orientation is a critical task for a multitude of applications ranging from automated cars and first responders to missiles and fighter jets. Most of these applications rely primarily on global navigation satellite systems, e.g., GPS, which are highly vulnerable to degradation whether by environmental factors or malicious actions. The use of inertial navigation techniques has been shown to provide increased reliability of navigation systems in these situations. Due to advances in MEMS technology and processing capabilities, the use of small and low-cost inertial measurement units (IMUs) are becoming increasingly feasible, which results in small size, weight and power (SWaP) solutions. A known limitation of MEMS IMUs are errors that causes the navigation solution to drift; furthermore, calibration and initialization are challenging tasks. In this paper, we investigate the use of multiple IMUs to aid in calibrating the navigation system and obtaining accurate initialization by performing fine alignment. By using a centralized filter, physical constraints between the multiple IMUs on a rigid body are leveraged to provide relative updates, which in turn aids in the estimation of the individual biases and scale-factors. Developed algorithms will be validated through simulation and actual measurements using low-cost IMUs.
Thermal Image Sensing Model for Robotic Planning and Search
Castro Jiménez, Lídice E.; Martínez-García, Edgar A.
2016-01-01
This work presents a search planning system for a rolling robot to find a source of infra-red (IR) radiation at an unknown location. Heat emissions are observed by a low-cost home-made IR passive visual sensor. The sensor capability for detection of radiation spectra was experimentally characterized. The sensor data were modeled by an exponential model to estimate the distance as a function of the IR image’s intensity, and, a polynomial model to estimate temperature as a function of IR intensities. Both theoretical models are combined to deduce a subtle nonlinear exact solution via distance-temperature. A planning system obtains feed back from the IR camera (position, intensity, and temperature) to lead the robot to find the heat source. The planner is a system of nonlinear equations recursively solved by a Newton-based approach to estimate the IR-source in global coordinates. The planning system assists an autonomous navigation control in order to reach the goal and avoid collisions. Trigonometric partial differential equations were established to control the robot’s course towards the heat emission. A sine function produces attractive accelerations toward the IR source. A cosine function produces repulsive accelerations against the obstacles observed by an RGB-D sensor. Simulations and real experiments of complex indoor are presented to illustrate the convenience and efficacy of the proposed approach. PMID:27509510
MusA: Using Indoor Positioning and Navigation to Enhance Cultural Experiences in a Museum
Rubino, Irene; Xhembulla, Jetmir; Martina, Andrea; Bottino, Andrea; Malnati, Giovanni
2013-01-01
In recent years there has been a growing interest in the use of multimedia mobile guides in museum environments. Mobile devices have the capabilities to detect the user context and to provide pieces of information suitable to help visitors discover and follow the logical and emotional connections that develop during the visit. In this scenario, location based services (LBS) currently represent an asset, and the choice of the technology to determine users' position, combined with the definition of methods that can effectively convey information, become key issues in the design process. In this work, we present Museum Assistant (MusA), a general framework for the development of multimedia interactive guides for mobile devices. Its main feature is a vision-based indoor positioning system that allows the provision of several LBS, from way-finding to the contextualized communication of cultural contents, aimed at providing a meaningful exploration of exhibits according to visitors' personal interest and curiosity. Starting from the thorough description of the system architecture, the article presents the implementation of two mobile guides, developed to respectively address adults and children, and discusses the evaluation of the user experience and the visitors' appreciation of these applications. PMID:24351645
MusA: using indoor positioning and navigation to enhance cultural experiences in a museum.
Rubino, Irene; Xhembulla, Jetmir; Martina, Andrea; Bottino, Andrea; Malnati, Giovanni
2013-12-17
In recent years there has been a growing interest in the use of multimedia mobile guides in museum environments. Mobile devices have the capabilities to detect the user context and to provide pieces of information suitable to help visitors discover and follow the logical and emotional connections that develop during the visit. In this scenario, location based services (LBS) currently represent an asset, and the choice of the technology to determine users' position, combined with the definition of methods that can effectively convey information, become key issues in the design process. In this work, we present Museum Assistant (MusA), a general framework for the development of multimedia interactive guides for mobile devices. Its main feature is a vision-based indoor positioning system that allows the provision of several LBS, from way-finding to the contextualized communication of cultural contents, aimed at providing a meaningful exploration of exhibits according to visitors' personal interest and curiosity. Starting from the thorough description of the system architecture, the article presents the implementation of two mobile guides, developed to respectively address adults and children, and discusses the evaluation of the user experience and the visitors' appreciation of these applications.
Revisiting Gaussian Process Regression Modeling for Localization in Wireless Sensor Networks
Richter, Philipp; Toledano-Ayala, Manuel
2015-01-01
Signal strength-based positioning in wireless sensor networks is a key technology for seamless, ubiquitous localization, especially in areas where Global Navigation Satellite System (GNSS) signals propagate poorly. To enable wireless local area network (WLAN) location fingerprinting in larger areas while maintaining accuracy, methods to reduce the effort of radio map creation must be consolidated and automatized. Gaussian process regression has been applied to overcome this issue, also with auspicious results, but the fit of the model was never thoroughly assessed. Instead, most studies trained a readily available model, relying on the zero mean and squared exponential covariance function, without further scrutinization. This paper studies the Gaussian process regression model selection for WLAN fingerprinting in indoor and outdoor environments. We train several models for indoor/outdoor- and combined areas; we evaluate them quantitatively and compare them by means of adequate model measures, hence assessing the fit of these models directly. To illuminate the quality of the model fit, the residuals of the proposed model are investigated, as well. Comparative experiments on the positioning performance verify and conclude the model selection. In this way, we show that the standard model is not the most appropriate, discuss alternatives and present our best candidate. PMID:26370996
Navigation of the GRAIL Spacecraft Pair Through the Extended Mission at the Moon
NASA Technical Reports Server (NTRS)
Goodson, Troy D.; Antreasian, Peter G.; Bhat, Ram S.; Chung, Min-Kun; Criddle, Kevin E.; Hatch, Sara J.; Jefferson, David C.; Lau, Eunice L.; Roncoli, Ralph B.; Ryne, Mark S.;
2013-01-01
The GRAIL extended mission (XM) dramatically expands the scope of GRAIL's gravity science investigation by flying the pair of spacecraft at the lowest orbit the flight team can safely support. From the perspective of the Navigation team, the low orbit altitude introduces new challenges. At this lower altitude, navigation is more sensitive to higher-order terms of the gravity field so that orbit determination solutions are more difficult and there is less certainty of achieving maneuver targets. This paper reports on the strategy and performance of the Navigation system for GRAIL's XM. On a weekly basis, the Navigation team provided reference trajectory updates, designed three maneuvers, and reconstructed the execution of those maneuvers. In all, the XM involved 55 planned maneuvers; five were canceled. The results of the Navigation team's efforts, in terms of maintaining the reference-trajectory targets, satisfying requirements, and achieving desired separation distances, are assessed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mendell, Mark J.; Apte, Mike G.
This report considers the question of whether the California Energy Commission should incorporate the ASHRAE 62.1 ventilation standard into the Title 24 ventilation rate (VR) standards, thus allowing buildings to follow the Indoor Air Quality Procedure. This, in contrast to the current prescriptive standard, allows the option of using ventilation rate as one of several strategies, which might include source reduction and air cleaning, to meet specified targets of indoor air concentrations and occupant acceptability. The research findings reviewed in this report suggest that a revised approach to a ventilation standard for commercial buildings is necessary, because the current prescriptivemore » ASHRAE 62.1 Ventilation Rate Procedure (VRP) apparently does not provide occupants with either sufficiently acceptable or sufficiently healthprotective air quality. One possible solution would be a dramatic increase in the minimum ventilation rates (VRs) prescribed by a VRP. This solution, however, is not feasible for at least three reasons: the current need to reduce energy use rather than increase it further, the problem of polluted outdoor air in many cities, and the apparent limited ability of increasing VRs to reduce all indoor airborne contaminants of concern (per Hodgson (2003)). Any feasible solution is thus likely to include methods of pollutant reduction other than increased outdoor air ventilation; e.g., source reduction or air cleaning. The alternative 62.1 Indoor Air Quality Procedure (IAQP) offers multiple possible benefits in this direction over the VRP, but seems too limited by insufficient specifications and inadequate available data to provide adequate protection for occupants. Ventilation system designers rarely choose to use it, finding it too arbitrary and requiring use of much non-engineering judgment and information that is not readily available. This report suggests strategies to revise the current ASHRAE IAQP to reduce its current limitations. These strategies, however, would make it more complex and more prescriptive, and would require substantial research. One practical intermediate strategy to save energy would be an alternate VRP, allowing VRs lower than currently prescribed, as long as indoor VOC concentrations were no higher than with VRs prescribed under the current VRP. This kind of hybrid, with source reduction and use of air cleaning optional but permitted, could eventually evolve, as data, materials, and air-cleaning technology allowed gradual lowering of allowable concentrations, into a fully developed IAQP. Ultimately, it seems that VR standards must evolve to resemble the IAQP, especially in California, where buildings must achieve zero net energy use within 20 years.« less
Assessing Thermal Comfort Due to a Ventilated Double Window
NASA Astrophysics Data System (ADS)
Carlos, Jorge S.; Corvacho, Helena
2017-10-01
Building design and its components are the result of a complex process, which should provide pleasant conditions to its inhabitants. Therefore, indoor acceptable comfort is influenced by the architectural design. ISO and ASHRAE standards define thermal comfort as the condition of mind that expresses satisfaction with the thermal environment. The energy demand for heating, beside the building’s physical properties, also depend on human behaviour, like opening or closing windows. Generally, windows are the weakest façade element concerning to thermal performance. A lower thermal resistance allows higher thermal conduction through it. When a window is very hot or cold, and the occupant is very close to it, it may result in thermal discomfort. The functionality of a ventilated double window introduces new physical considerations to a traditional window. In consequence, it is necessary to study the local effect on human comfort in function of the boundary conditions. Wind, solar availability, air temperature and therefore heating and indoor air quality conditions will affect the relationship between this passive system and the indoor environment. In the present paper, the influence of thermal performance and ventilation on human comfort resulting from the construction and geometry solutions is shown, helping to choose the best solution. The presented approach shows that in order to save energy it is possible to reduce the air changes of a room to the minimum, without compromising air quality, enhancing simultaneously local thermal performance and comfort. The results of the study on the effect of two parallel windows with a ventilated channel in the same fenestration on comfort conditions for several different room dimensions, are also presented. As the room dimensions’ rate changes so does the window to floor rate; therefore, under the same climatic conditions and same construction solution, different results are obtained.
Emergency navigation without an infrastructure.
Gelenbe, Erol; Bi, Huibo
2014-08-18
Emergency navigation systems for buildings and other built environments, such as sport arenas or shopping centres, typically rely on simple sensor networks to detect emergencies and, then, provide automatic signs to direct the evacuees. The major drawbacks of such static wireless sensor network (WSN)-based emergency navigation systems are the very limited computing capacity, which makes adaptivity very difficult, and the restricted battery power, due to the low cost of sensor nodes for unattended operation. If static wireless sensor networks and cloud-computing can be integrated, then intensive computations that are needed to determine optimal evacuation routes in the presence of time-varying hazards can be offloaded to the cloud, but the disadvantages of limited battery life-time at the client side, as well as the high likelihood of system malfunction during an emergency still remain. By making use of the powerful sensing ability of smart phones, which are increasingly ubiquitous, this paper presents a cloud-enabled indoor emergency navigation framework to direct evacuees in a coordinated fashion and to improve the reliability and resilience for both communication and localization. By combining social potential fields (SPF) and a cognitive packet network (CPN)-based algorithm, evacuees are guided to exits in dynamic loose clusters. Rather than relying on a conventional telecommunications infrastructure, we suggest an ad hoc cognitive packet network (AHCPN)-based protocol to adaptively search optimal communication routes between portable devices and the network egress nodes that provide access to cloud servers, in a manner that spares the remaining battery power of smart phones and minimizes the time latency. Experimental results through detailed simulations indicate that smart human motion and smart network management can increase the survival rate of evacuees and reduce the number of drained smart phones in an evacuation process.
Emergency Navigation without an Infrastructure
Gelenbe, Erol; Bi, Huibo
2014-01-01
Emergency navigation systems for buildings and other built environments, such as sport arenas or shopping centres, typically rely on simple sensor networks to detect emergencies and, then, provide automatic signs to direct the evacuees. The major drawbacks of such static wireless sensor network (WSN)-based emergency navigation systems are the very limited computing capacity, which makes adaptivity very difficult, and the restricted battery power, due to the low cost of sensor nodes for unattended operation. If static wireless sensor networks and cloud-computing can be integrated, then intensive computations that are needed to determine optimal evacuation routes in the presence of time-varying hazards can be offloaded to the cloud, but the disadvantages of limited battery life-time at the client side, as well as the high likelihood of system malfunction during an emergency still remain. By making use of the powerful sensing ability of smart phones, which are increasingly ubiquitous, this paper presents a cloud-enabled indoor emergency navigation framework to direct evacuees in a coordinated fashion and to improve the reliability and resilience for both communication and localization. By combining social potential fields (SPF) and a cognitive packet network (CPN)-based algorithm, evacuees are guided to exits in dynamic loose clusters. Rather than relying on a conventional telecommunications infrastructure, we suggest an ad hoc cognitive packet network (AHCPN)-based protocol to adaptively search optimal communication routes between portable devices and the network egress nodes that provide access to cloud servers, in a manner that spares the remaining battery power of smart phones and minimizes the time latency. Experimental results through detailed simulations indicate that smart human motion and smart network management can increase the survival rate of evacuees and reduce the number of drained smart phones in an evacuation process. PMID:25196014
2014-06-01
Speed xiii TEK Total Energy Compensated TSP traveling salesman problem UAV unmanned aerial vehicle UDP user datagram protocol UKF unscented...discretized map, and use the map to optimally solve the navigation task. The optimal navigation solution utilizes the well-known “ travelling salesman problem ...2 C. FORMULATION OF THE PROBLEM .................................................. 3 D
Connors, Erin C; Chrastil, Elizabeth R; Sánchez, Jaime; Merabet, Lotfi B
2014-01-01
For profoundly blind individuals, navigating in an unfamiliar building can represent a significant challenge. We investigated the use of an audio-based, virtual environment called Audio-based Environment Simulator (AbES) that can be explored for the purposes of learning the layout of an unfamiliar, complex indoor environment. Furthermore, we compared two modes of interaction with AbES. In one group, blind participants implicitly learned the layout of a target environment while playing an exploratory, goal-directed video game. By comparison, a second group was explicitly taught the same layout following a standard route and instructions provided by a sighted facilitator. As a control, a third group interacted with AbES while playing an exploratory, goal-directed video game however, the explored environment did not correspond to the target layout. Following interaction with AbES, a series of route navigation tasks were carried out in the virtual and physical building represented in the training environment to assess the transfer of acquired spatial information. We found that participants from both modes of interaction were able to transfer the spatial knowledge gained as indexed by their successful route navigation performance. This transfer was not apparent in the control participants. Most notably, the game-based learning strategy was also associated with enhanced performance when participants were required to find alternate routes and short cuts within the target building suggesting that a ludic-based training approach may provide for a more flexible mental representation of the environment. Furthermore, outcome comparisons between early and late blind individuals suggested that greater prior visual experience did not have a significant effect on overall navigation performance following training. Finally, performance did not appear to be associated with other factors of interest such as age, gender, and verbal memory recall. We conclude that the highly interactive and immersive exploration of the virtual environment greatly engages a blind user to develop skills akin to positive near transfer of learning. Learning through a game play strategy appears to confer certain behavioral advantages with respect to how spatial information is acquired and ultimately manipulated for navigation.
Connors, Erin C.; Chrastil, Elizabeth R.; Sánchez, Jaime; Merabet, Lotfi B.
2014-01-01
For profoundly blind individuals, navigating in an unfamiliar building can represent a significant challenge. We investigated the use of an audio-based, virtual environment called Audio-based Environment Simulator (AbES) that can be explored for the purposes of learning the layout of an unfamiliar, complex indoor environment. Furthermore, we compared two modes of interaction with AbES. In one group, blind participants implicitly learned the layout of a target environment while playing an exploratory, goal-directed video game. By comparison, a second group was explicitly taught the same layout following a standard route and instructions provided by a sighted facilitator. As a control, a third group interacted with AbES while playing an exploratory, goal-directed video game however, the explored environment did not correspond to the target layout. Following interaction with AbES, a series of route navigation tasks were carried out in the virtual and physical building represented in the training environment to assess the transfer of acquired spatial information. We found that participants from both modes of interaction were able to transfer the spatial knowledge gained as indexed by their successful route navigation performance. This transfer was not apparent in the control participants. Most notably, the game-based learning strategy was also associated with enhanced performance when participants were required to find alternate routes and short cuts within the target building suggesting that a ludic-based training approach may provide for a more flexible mental representation of the environment. Furthermore, outcome comparisons between early and late blind individuals suggested that greater prior visual experience did not have a significant effect on overall navigation performance following training. Finally, performance did not appear to be associated with other factors of interest such as age, gender, and verbal memory recall. We conclude that the highly interactive and immersive exploration of the virtual environment greatly engages a blind user to develop skills akin to positive near transfer of learning. Learning through a game play strategy appears to confer certain behavioral advantages with respect to how spatial information is acquired and ultimately manipulated for navigation. PMID:24822044
ERIC Educational Resources Information Center
Schultz, Fred C.
2001-01-01
Reveals how seeking simplicity can help bring indoor air quality (IAQ) solutions to grade schools by balancing IAQ needs, cost, and energy. Issues involving ventilation rate requirements are reexamined, as are compliance with outside-air requirements, dealing with variable-air-volume air distribution regulators, and retrofitting issues involving…
Invariants of the Jacobi-Porstendorfer room model for radon progeny in indoor air.
Thomas, Josef; Jilek, Karel
2012-06-01
The Jacobi-Porstendörfer room model, describing the dynamical behaviour of radon and radon progeny in indoor air, has been successfully used for decades. The inversion of the model-the determination of the five parameters from measured results which provide better information on the room environment than mere ratios of unattached and attached radon progeny-is treated as an algebraic task. The linear interdependence of the used equations strongly limits the algebraic invertibility of experimental results. For a unique solution, the fulfilment of two invariants of the room model for the measured results is required. Non-fulfilment of these model invariants by the measured results leads to a set of non-identical solutions and indicates the violation of the conditions required by the room model or the incorrectness or excessive uncertainties of the measured results. The limited and non-unique algebraic invertibility of the room model is analysed numerically using our own data for the radon progeny.
Navigation with noncoherent data - A demonstration for VEGA Venus flyby phase
NASA Technical Reports Server (NTRS)
Bhat, Ramachandra S.; Ellis, Jordan; Mcelrath, Timothy P.
1988-01-01
Deep Space navigation with noncoherent (one-way) data types is demonstrated for the VEGA Venus flyby phase under extreme conditions. Estimates and statistics are computed using one-way Doppler and wideband Very Long Baseline Interferometry (VLBI) data. The behavior of the onboard oscillator is modeled for both spacecraft to obtain useful orbit determination results. Even with this limitation, it is demonstrated that one-way data solutions are comparable with the solutions using both Soviet sparse coherent (two-way) and wideband VLBI data. During the useful life time of VEGA balloons, the two solutions differ by a maximum of 4.7 km in position and 7.6 cm/sec in velocity for VEGA 1 and by a maximum of 8 km and 42 cm/sec for VEGA 2.
Evolutionary Perspective on Collective Decision Making
NASA Astrophysics Data System (ADS)
Farrell, Dene; Sayama, Hiroki; Dionne, Shelley D.; Yammarino, Francis J.; Wilson, David Sloan
Team decision making dynamics are investigated from a novel perspective by shifting agency from decision makers to representations of potential solutions. We provide a new way to navigate social dynamics of collective decision making by interpreting decision makers as constituents of an evolutionary environment of an ecology of evolving solutions. We demonstrate distinct patterns of evolution with respect to three forms of variation: (1) Results with random variations in utility functions of individuals indicate that groups demonstrating minimal internal variation produce higher true utility values of group solutions and display better convergence; (2) analysis of variations in behavioral patterns within a group shows that a proper balance between selective and creative evolutionary forces is crucial to producing adaptive solutions; and (3) biased variations of the utility functions diminish the range of variation for potential solution utility, leaving only the differential of convergence performance static. We generally find that group cohesion (low random variation within a group) and composition (appropriate variation of behavioral patterns within a group) are necessary for a successful navigation of the solution space, but performance in both cases is susceptible to group level biases.
Relative Navigation of Formation Flying Satellites
NASA Technical Reports Server (NTRS)
Long, Anne; Kelbel, David; Lee, Taesul; Leung, Dominic; Carpenter, Russell; Gramling, Cheryl; Bauer, Frank (Technical Monitor)
2002-01-01
The Guidance, Navigation, and Control Center (GNCC) at Goddard Space Flight Center (GSFC) has successfully developed high-accuracy autonomous satellite navigation systems using the National Aeronautics and Space Administration's (NASA's) space and ground communications systems and the Global Positioning System (GPS). In addition, an autonomous navigation system that uses celestial object sensor measurements is currently under development and has been successfully tested using real Sun and Earth horizon measurements.The GNCC has developed advanced spacecraft systems that provide autonomous navigation and control of formation flyers in near-Earth, high-Earth, and libration point orbits. To support this effort, the GNCC is assessing the relative navigation accuracy achievable for proposed formations using GPS, intersatellite crosslink, ground-to-satellite Doppler, and celestial object sensor measurements. This paper evaluates the performance of these relative navigation approaches for three proposed missions with two or more vehicles maintaining relatively tight formations. High-fidelity simulations were performed to quantify the absolute and relative navigation accuracy as a function of navigation algorithm and measurement type. Realistically-simulated measurements were processed using the extended Kalman filter implemented in the GPS Enhanced Inboard Navigation System (GEONS) flight software developed by GSFC GNCC. Solutions obtained by simultaneously estimating all satellites in the formation were compared with the results obtained using a simpler approach based on differencing independently estimated state vectors.
NASA Astrophysics Data System (ADS)
Shaaban, Rana; Faruque, Saleh
2018-01-01
Light emitting diodes - LEDs are modernizing the indoor illumination and replacing current incandescent and fluorescent lamps rapidly. LEDs have multiple advantages such as extremely high energy efficient, longer lifespan, and lower heat generation. Due to the ability to switch to different light intensity at a very fast rate, LED has given rise to a unique communication technology (visible light communication - VLC) used for high speed data transmission. By studying various kinds of commonly used VLC channel analysis: diffuse and line of sight channels, we presented a simply improved indoor and intra-vehicle visible light communication transmission model. Employing optical wireless communications within the vehicle, not only enhance user mobility, but also alleviate radio frequency interference, and increase efficiency by lowering the complexity of copper cabling. Moreover, a solution to eliminate ambient noise caused by environmental conditions is examined by using optical differential receiver. The simulation results show the improved received power distribution and signal to noise ratio - SNR.
de Miguel-Bilbao, Silvia; Aguirre, Erik; Lopez Iturri, Peio; Azpilicueta, Leire; Roldán, José; Falcone, Francisco; Ramos, Victoria
2015-01-01
In the last decade the number of wireless devices operating at the frequency band of 2.4 GHz has increased in several settings, such as healthcare, occupational, and household. In this work, the emissions from Wi-Fi transceivers applicable to context aware scenarios are analyzed in terms of potential interference and assessment on exposure guideline compliance. Near field measurement results as well as deterministic simulation results on realistic indoor environments are presented, providing insight on the interaction between the Wi-Fi transceiver and implantable/body area network devices as well as other transceivers operating within an indoor environment, exhibiting topological and morphological complexity. By following approaches (near field estimation/deterministic estimation), colocated body situations as well as large indoor emissions can be determined. The results show in general compliance with exposure levels and the impact of overall network deployment, which can be optimized in order to reduce overall interference levels while maximizing system performance.
de Miguel-Bilbao, Silvia; Aguirre, Erik; Lopez Iturri, Peio; Azpilicueta, Leire; Roldán, José; Falcone, Francisco; Ramos, Victoria
2015-01-01
In the last decade the number of wireless devices operating at the frequency band of 2.4 GHz has increased in several settings, such as healthcare, occupational, and household. In this work, the emissions from Wi-Fi transceivers applicable to context aware scenarios are analyzed in terms of potential interference and assessment on exposure guideline compliance. Near field measurement results as well as deterministic simulation results on realistic indoor environments are presented, providing insight on the interaction between the Wi-Fi transceiver and implantable/body area network devices as well as other transceivers operating within an indoor environment, exhibiting topological and morphological complexity. By following approaches (near field estimation/deterministic estimation), colocated body situations as well as large indoor emissions can be determined. The results show in general compliance with exposure levels and the impact of overall network deployment, which can be optimized in order to reduce overall interference levels while maximizing system performance. PMID:25632400
Legal services: a necessary component of patient navigation.
Retkin, Randye; Antoniadis, Domna; Pepitone, Daniel F; Duval, Deanna
2013-05-01
Access to legal advocacy is an essential tool to help cancer patients and survivors through the continuum of care. This article examines delivery models that can seamlessly integrate into patient navigation programs. Technical reports, books, journal articles, and Web sites. Psychosocial obstacles are common barriers of low-income individuals facing a cancer diagnosis. Legal solutions can help to minimize these obstacles, yet patients rarely have access to these services. Training patient navigators to appropriately screen for legal issues and collaborate with attorneys can be used to help prevent, rather than just react to, legal issues by addressing them as a part of a treatment plan. Attorneys working with patient navigators, particularly nurse navigators, can impact oncology nursing practice by providing an innovative collaboration that is consistent with emerging trends in patient-centered treatment. Copyright © 2013. Published by Elsevier Inc.
Tightly-Coupled GNSS/Vision Using a Sky-Pointing Camera for Vehicle Navigation in Urban Areas
2018-01-01
This paper presents a method of fusing the ego-motion of a robot or a land vehicle estimated from an upward-facing camera with Global Navigation Satellite System (GNSS) signals for navigation purposes in urban environments. A sky-pointing camera is mounted on the top of a car and synchronized with a GNSS receiver. The advantages of this configuration are two-fold: firstly, for the GNSS signals, the upward-facing camera will be used to classify the acquired images into sky and non-sky (also known as segmentation). A satellite falling into the non-sky areas (e.g., buildings, trees) will be rejected and not considered for the final position solution computation. Secondly, the sky-pointing camera (with a field of view of about 90 degrees) is helpful for urban area ego-motion estimation in the sense that it does not see most of the moving objects (e.g., pedestrians, cars) and thus is able to estimate the ego-motion with fewer outliers than is typical with a forward-facing camera. The GNSS and visual information systems are tightly-coupled in a Kalman filter for the final position solution. Experimental results demonstrate the ability of the system to provide satisfactory navigation solutions and better accuracy than the GNSS-only and the loosely-coupled GNSS/vision, 20 percent and 82 percent (in the worst case) respectively, in a deep urban canyon, even in conditions with fewer than four GNSS satellites. PMID:29673230
Tightly-Coupled GNSS/Vision Using a Sky-Pointing Camera for Vehicle Navigation in Urban Areas.
Gakne, Paul Verlaine; O'Keefe, Kyle
2018-04-17
This paper presents a method of fusing the ego-motion of a robot or a land vehicle estimated from an upward-facing camera with Global Navigation Satellite System (GNSS) signals for navigation purposes in urban environments. A sky-pointing camera is mounted on the top of a car and synchronized with a GNSS receiver. The advantages of this configuration are two-fold: firstly, for the GNSS signals, the upward-facing camera will be used to classify the acquired images into sky and non-sky (also known as segmentation). A satellite falling into the non-sky areas (e.g., buildings, trees) will be rejected and not considered for the final position solution computation. Secondly, the sky-pointing camera (with a field of view of about 90 degrees) is helpful for urban area ego-motion estimation in the sense that it does not see most of the moving objects (e.g., pedestrians, cars) and thus is able to estimate the ego-motion with fewer outliers than is typical with a forward-facing camera. The GNSS and visual information systems are tightly-coupled in a Kalman filter for the final position solution. Experimental results demonstrate the ability of the system to provide satisfactory navigation solutions and better accuracy than the GNSS-only and the loosely-coupled GNSS/vision, 20 percent and 82 percent (in the worst case) respectively, in a deep urban canyon, even in conditions with fewer than four GNSS satellites.
Conic state extrapolation. [computer program for space shuttle navigation and guidance requirements
NASA Technical Reports Server (NTRS)
Shepperd, S. W.; Robertson, W. M.
1973-01-01
The Conic State Extrapolation Routine provides the capability to conically extrapolate any spacecraft inertial state vector either backwards or forwards as a function of time or as a function of transfer angle. It is merely the coded form of two versions of the solution of the two-body differential equations of motion of the spacecraft center of mass. Because of its relatively fast computation speed and moderate accuracy, it serves as a preliminary navigation tool and as a method of obtaining quick solutions for targeting and guidance functions. More accurate (but slower) results are provided by the Precision State Extrapolation Routine.
1993-12-01
5-6 5.6.1 Large Cycle Slip Simulation ............................. 5-7 5.6.2 Small Cycle Slip Simulation ........................... 5-9...Appendix J. Small Cycle Slip Simulation Results ............................. J-1 Bibliography ........................................................ BIB-I...when subjected to large and small cycle slips. Results of the simulations indicate that the PNRS can provide an improved navigation solution over
DOT National Transportation Integrated Search
2016-08-01
The John A. Volpe National Transportation Systems Center (Volpe Center) was asked by the NOAA Office of Space Commercialization to analyze dependencies on Global Positioning System (GPS) positioning, navigation, and timing (PNT) services within the U...
GPS/MEMS IMU/Microprocessor Board for Navigation
NASA Technical Reports Server (NTRS)
Gender, Thomas K.; Chow, James; Ott, William E.
2009-01-01
A miniaturized instrumentation package comprising a (1) Global Positioning System (GPS) receiver, (2) an inertial measurement unit (IMU) consisting largely of surface-micromachined sensors of the microelectromechanical systems (MEMS) type, and (3) a microprocessor, all residing on a single circuit board, is part of the navigation system of a compact robotic spacecraft intended to be released from a larger spacecraft [e.g., the International Space Station (ISS)] for exterior visual inspection of the larger spacecraft. Variants of the package may also be useful in terrestrial collision-detection and -avoidance applications. The navigation solution obtained by integrating the IMU outputs is fed back to a correlator in the GPS receiver to aid in tracking GPS signals. The raw GPS and IMU data are blended in a Kalman filter to obtain an optimal navigation solution, which can be supplemented by range and velocity data obtained by use of (l) a stereoscopic pair of electronic cameras aboard the robotic spacecraft and/or (2) a laser dynamic range imager aboard the ISS. The novelty of the package lies mostly in those aspects of the design of the MEMS IMU that pertain to controlling mechanical resonances and stabilizing scale factors and biases.
Analysis of Multi-Antenna GNSS Receiver Performance under Jamming Attacks.
Vagle, Niranjana; Broumandan, Ali; Lachapelle, Gérard
2016-11-17
Although antenna array-based Global Navigation Satellite System (GNSS) receivers can be used to mitigate both narrowband and wideband electronic interference sources, measurement distortions induced by array processing methods are not suitable for high precision applications. The measurement distortions have an adverse effect on the carrier phase ambiguity resolution, affecting the navigation solution. Depending on the array attitude information availability and calibration parameters, different spatial processing methods can be implemented although they distort carrier phase measurements in some cases. This paper provides a detailed investigation of the effect of different array processing techniques on array-based GNSS receiver measurements and navigation performance. The main novelty of the paper is to provide a thorough analysis of array-based GNSS receivers employing different beamforming techniques from tracking to navigation solution. Two beamforming techniques, namely Power Minimization (PM) and Minimum Power Distortionless Response (MPDR), are being investigated. In the tracking domain, the carrier Doppler, Phase Lock Indicator (PLI), and Carrier-to-Noise Ratio (C/N₀) are analyzed. Pseudorange and carrier phase measurement distortions and carrier phase position performance are also evaluated. Performance analyses results from simulated GNSS signals and field tests are provided.
A review of photocatalysts prepared by sol-gel method for VOCs removal.
Tseng, Ting Ke; Lin, Yi Shing; Chen, Yi Ju; Chu, Hsin
2010-05-28
The sol-gel process is a wet-chemical technique (chemical solution deposition), which has been widely used in the fields of materials science, ceramic engineering, and especially in the preparation of photocatalysts. Volatile organic compounds (VOCs) are prevalent components of indoor air pollution. Among the approaches to remove VOCs from indoor air, photocatalytic oxidation (PCO) is regarded as a promising method. This paper is a review of the status of research on the sol-gel method for photocatalyst preparation and for the PCO purification of VOCs. The review and discussion will focus on the preparation and coating of various photocatalysts, operational parameters, and will provide an overview of general PCO models described in the literature.
AFRL Commander's Challenge 2015: stopping the active shooter
NASA Astrophysics Data System (ADS)
McIntire, John P.; Boston, Jonathan; Smith, Brandon; Swartz, Pete; Whitney-Rawls, Amy; Martinez Calderon, Julian; Magin, Jonathan
2017-05-01
In this work, we describe a rapid-innovation challenge to combat and deal with the problem of internal, insider physical threats (e.g., active shooters) and associated first-responder situation awareness on military installations. Our team's research and development effort described within focused on several key tech development areas: (1) indoor acoustical gunshot detection, (2) indoor spatial tracking of first responders, (3) bystander safety and protection, (4) two-way mass alerting capability, and (5) spatial information displays for command and control. The technological solutions were specifically designed to be innovative, low-cost, and (relatively) easy-to-implement, and to provide support across the spectrum of possible users including potential victims/bystanders, first responders, dispatch, and incident command.
Patterns of task and network actions performed by navigators to facilitate cancer care.
Clark, Jack A; Parker, Victoria A; Battaglia, Tracy A; Freund, Karen M
2014-01-01
Patient navigation is a widely implemented intervention to facilitate access to care and reduce disparities in cancer care, but the activities of navigators are not well characterized. The aim of this study is to describe what patient navigators actually do and explore patterns of activity that clarify the roles they perform in facilitating cancer care. We conducted field observations of nine patient navigation programs operating in diverse health settings of the national patient navigation research program, including 34 patient navigators, each observed an average of four times. Trained observers used a structured observation protocol to code as they recorded navigator actions and write qualitative field notes capturing all activities in 15-minute intervals during observations ranging from 2 to 7 hours; yielding a total of 133 observations. Rates of coded activity were analyzed using numerical cluster analysis of identified patterns, informed by qualitative analysis of field notes. Six distinct patterns of navigator activity were identified, which differed most relative to how much time navigators spent directly interacting with patients and how much time they spent dealing with medical records and documentation tasks. Navigator actions reveal a complex set of roles in which navigators both provide the direct help to patients denoted by their title and also carry out a variety of actions that function to keep the health system operating smoothly. Working to navigate patients through complex health services entails working to repair the persistent challenges of health services that can render them inhospitable to patients. The organizations that deploy navigators might learn from navigators' efforts and explore alternative approaches, structures, or systems of care in addressing both the barriers patients face and the complex solutions navigators create in helping patients.
Impact of climate change on the domestic indoor environment and associated health risks in the UK.
Vardoulakis, Sotiris; Dimitroulopoulou, Chrysanthi; Thornes, John; Lai, Ka-Man; Taylor, Jonathon; Myers, Isabella; Heaviside, Clare; Mavrogianni, Anna; Shrubsole, Clive; Chalabi, Zaid; Davies, Michael; Wilkinson, Paul
2015-12-01
There is growing evidence that projected climate change has the potential to significantly affect public health. In the UK, much of this impact is likely to arise by amplifying existing risks related to heat exposure, flooding, and chemical and biological contamination in buildings. Identifying the health effects of climate change on the indoor environment, and risks and opportunities related to climate change adaptation and mitigation, can help protect public health. We explored a range of health risks in the domestic indoor environment related to climate change, as well as the potential health benefits and unintended harmful effects of climate change mitigation and adaptation policies in the UK housing sector. We reviewed relevant scientific literature, focusing on housing-related health effects in the UK likely to arise through either direct or indirect mechanisms of climate change or mitigation and adaptation measures in the built environment. We considered the following categories of effect: (i) indoor temperatures, (ii) indoor air quality, (iii) indoor allergens and infections, and (iv) flood damage and water contamination. Climate change may exacerbate health risks and inequalities across these categories and in a variety of ways, if adequate adaptation measures are not taken. Certain changes to the indoor environment can affect indoor air quality or promote the growth and propagation of pathogenic organisms. Measures aimed at reducing greenhouse gas emissions have the potential for ancillary public health benefits including reductions in health burdens related heat and cold, indoor exposure to air pollution derived from outdoor sources, and mould growth. However, increasing airtightness of dwellings in pursuit of energy efficiency could also have negative effects by increasing concentrations of pollutants (such as PM2.5, CO and radon) derived from indoor or ground sources, and biological contamination. These effects can largely be ameliorated by mechanical ventilation with heat recovery (MVHR) and air filtration, where such solution is feasible and when the system is properly installed, operated and maintained. Groups at high risk of these adverse health effects include the elderly (especially those living on their own), individuals with pre-existing illnesses, people living in overcrowded accommodation, and the socioeconomically deprived. A better understanding of how current and emerging building infrastructure design, construction, and materials may affect health in the context of climate change and mitigation and adaptation measures is needed in the UK and other high income countries. Long-term, energy efficient building design interventions, ensuring adequate ventilation, need to be promoted. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.
Stereotaxy, navigation and the temporal concatenation.
Apuzzo, M L; Chen, J C
1999-01-01
Nautical and cerebral navigation share similar elements of functional need and similar developmental pathways. The need for orientation necessitates the development of appropriate concepts, and such concepts are dependent on technology for practical realization. Occasionally, a concept precedes technology in time and requires periods of delay for appropriate development. A temporal concatenation exists where time allows the additive as need, concept and technology ultimately provide an endpoint of elegant solution. Nautical navigation has proceeded through periods of dead reckoning and celestial navigation to satellite orientation with associated refinements of instrumentation and charts for guidance. Cerebral navigation has progressed from craniometric orientation and burr hole mounted guidance systems to simple rectolinear and arc-centered devices based on radiographs to guidance by complex anatomical and functional maps provided as an amalgam of modern imaging modes. These maps are now augmented by complex frame and frameless systems which allow not only precise orientation, but also point and volumetric action. These complex technical modalities required and developed in part from elements of maritime navigation that have been translated to cerebral navigation in a temporal concatenation. Copyright 2000 S. Karger AG, Basel
Li, Fangmin; Liu, Guo; Liu, Jian; Chen, Xiaochuang; Ma, Xiaolin
2016-10-28
Most location-based services are based on a global positioning system (GPS), which only works well in outdoor environments. Compared to outdoor environments, indoor localization has created more buzz in recent years as people spent most of their time indoors working at offices and shopping at malls, etc. Existing solutions mainly rely on inertial sensors (i.e., accelerometer and gyroscope) embedded in mobile devices, which are usually not accurate enough to be useful due to the mobile devices' random movements while people are walking. In this paper, we propose the use of shoe sensing (i.e., sensors attached to shoes) to achieve 3D indoor positioning. Specifically, a short-time energy-based approach is used to extract the gait pattern. Moreover, in order to improve the accuracy of vertical distance estimation while the person is climbing upstairs, a state classification is designed to distinguish the walking status including plane motion (i.e., normal walking and jogging horizontally), walking upstairs, and walking downstairs. Furthermore, we also provide a mechanism to reduce the vertical distance accumulation error. Experimental results show that we can achieve nearly 100% accuracy when extracting gait patterns from walking/jogging with a low-cost shoe sensor, and can also achieve 3D indoor real-time positioning with high accuracy.
Zhang, L-Z; Zhang, X-R; Miao, Q-Z; Pei, L-X
2012-08-01
Fresh air ventilation is central to indoor environmental control. Total heat exchangers can be key equipment for energy conservation in ventilation. Membranes have been used for total heat exchangers for more than a decade. Much effort has been spent to achieve water vapor permeability of various membranes; however, relatively little attention has been paid to the selectivity of moisture compared with volatile organic compounds (VOCs) through such membranes. In this investigation, the most commonly used membranes, both hydrophilic and hydrophobic ones, are tested for their permeability for moisture and five VOCs (acetic acid, formaldehyde, acetaldehyde, toluene, and ethane). The selectivity of moisture vs. VOCs in these membranes is then evaluated. With a solution-diffusion model, the solubility and diffusivity of moisture and VOCs in these membranes are calculated. The resulting data could provide some reference for future material selection. Total heat exchangers are important equipment for fresh air ventilation with energy conservation. However, their implications for indoor air quality in terms of volatile organic compound permeation have not been known. The data in this article help us to clarify the impacts on indoor VOC levels of membrane-based heat exchangers. Guidelines for material selection can be obtained for future use total heat exchangers for building ventilation. © 2011 John Wiley & Sons A/S.
Sources and perceptions of indoor and ambient air pollution in rural Alaska.
Ware, Desirae; Lewis, Johnnye; Hopkins, Scarlett; Boyer, Bert; Noonan, Curtis; Ward, Tony
2013-08-01
Even though Alaska is the largest state in the United States, much of the population resides in rural and underserved areas with documented disparities in respiratory health. This is especially true in the Yukon-Kuskokwim (southwest) and Ahtna (southcentral) Regions of Alaska. In working with community members, the goal of this study was to identify the air pollution issues (both indoors and outdoors) of concern within these two regions. Over a two-year period, 328 air quality surveys were disseminated within seven communities in rural Alaska. The surveys focused on understanding the demographics, home heating practices, indoor activities, community/outdoor activities, and air quality perceptions within each community. Results from these surveys showed that there is elevated potential for PM10/PM2.5 exposures in rural Alaska communities. Top indoor air quality concerns included mold, lack of ventilation or fresh air, and dust. Top outdoor air pollution concerns identified were open burning/smoke, road dust, and vehicle exhaust (e.g., snow machines, ATVs, etc.). These data can now be used to seek additional funding for interventions, implementing long-term, sustainable solutions to the identified problems. Further research is needed to assess exposures to PM10/PM2.5 and the associated impacts on respiratory health, particularly among susceptible populations such as young children.
Hub, Andreas; Hartter, Tim; Kombrink, Stefan; Ertl, Thomas
2008-01-01
PURPOSE.: This study describes the development of a multi-functional assistant system for the blind which combines localisation, real and virtual navigation within modelled environments and the identification and tracking of fixed and movable objects. The approximate position of buildings is determined with a global positioning sensor (GPS), then the user establishes exact position at a specific landmark, like a door. This location initialises indoor navigation, based on an inertial sensor, a step recognition algorithm and map. Tracking of movable objects is provided by another inertial sensor and a head-mounted stereo camera, combined with 3D environmental models. This study developed an algorithm based on shape and colour to identify objects and used a common face detection algorithm to inform the user of the presence and position of others. The system allows blind people to determine their position with approximately 1 metre accuracy. Virtual exploration of the environment can be accomplished by moving one's finger on a touch screen of a small portable tablet PC. The name of rooms, building features and hazards, modelled objects and their positions are presented acoustically or in Braille. Given adequate environmental models, this system offers blind people the opportunity to navigate independently and safely, even within unknown environments. Additionally, the system facilitates education and rehabilitation by providing, in several languages, object names, features and relative positions.
NASA Astrophysics Data System (ADS)
Zhang, Yachu; Zhao, Yuejin; Liu, Ming; Dong, Liquan; Kong, Lingqin; Liu, Lingling
2017-09-01
In contrast to humans, who use only visual information for navigation, many mobile robots use laser scanners and ultrasonic sensors along with vision cameras to navigate. This work proposes a vision-based robot control algorithm based on deep convolutional neural networks. We create a large 15-layer convolutional neural network learning system and achieve the advanced recognition performance. Our system is trained from end to end to map raw input images to direction in supervised mode. The images of data sets are collected in a wide variety of weather conditions and lighting conditions. Besides, the data sets are augmented by adding Gaussian noise and Salt-and-pepper noise to avoid overfitting. The algorithm is verified by two experiments, which are line tracking and obstacle avoidance. The line tracking experiment is proceeded in order to track the desired path which is composed of straight and curved lines. The goal of obstacle avoidance experiment is to avoid the obstacles indoor. Finally, we get 3.29% error rate on the training set and 5.1% error rate on the test set in the line tracking experiment, 1.8% error rate on the training set and less than 5% error rate on the test set in the obstacle avoidance experiment. During the actual test, the robot can follow the runway centerline outdoor and avoid the obstacle in the room accurately. The result confirms the effectiveness of the algorithm and our improvement in the network structure and train parameters
The Development of a Simulator System and Hardware Test Bed for Deep Space X-Ray Navigation
NASA Astrophysics Data System (ADS)
Doyle, Patrick T.
2013-03-01
Currently, there is a considerable interest in developing technologies that will allow using photon measurements from celestial x-ray sources for deep space navigation. The impetus for this is that many envisioned future space missions will require spacecraft to have autonomous navigation capabilities. For missions close to Earth, Global Navigation Satellite Systems (GNSS) such as GPS are readily available for use, but for missions far from Earth, other alternatives must be provided. While existing systems such as the Deep Space Network (DSN) can be used, latencies associated with servicing a fleet of vehicles may not be compatible with some autonomous operations requiring timely updates of their navigation solution. Because of their somewhat predictable emissions, pulsars are the ideal candidates for x-ray sources that can be used to provide key parameters for navigation. Algorithms and simulation tools that will enable designing and analyzing x-ray navigation concepts are presented. The development of a compact x-ray detector system is pivotal to the eventual deployment of such navigation systems. Therefore, results of a high altitude balloon test to evaluate the design of a compact x-ray detector system are described as well.
Modular Building Supplement: A Quick, Quality Solution for Schools.
ERIC Educational Resources Information Center
Goodmiller, Brian D.; Schendell, Derek G.
2003-01-01
This supplement presents three articles on modular construction that look at: "Fast Track Expansion for a New Jersey School" (involving a modular addition); "Precast Construction Helps Schools Meet Attendance Boom" (precast concrete components are quick, durable, and flexible); and "Airing HVAC Concerns" (poor indoor air quality in prefabricated…
NASA Astrophysics Data System (ADS)
van Oosterom, Matthias Nathanaël; Engelen, Myrthe Adriana; van den Berg, Nynke Sjoerdtje; KleinJan, Gijs Hendrik; van der Poel, Henk Gerrit; Wendler, Thomas; van de Velde, Cornelis Jan Hadde; Navab, Nassir; van Leeuwen, Fijs Willem Bernhard
2016-08-01
Robot-assisted laparoscopic surgery is becoming an established technique for prostatectomy and is increasingly being explored for other types of cancer. Linking intraoperative imaging techniques, such as fluorescence guidance, with the three-dimensional insights provided by preoperative imaging remains a challenge. Navigation technologies may provide a solution, especially when directly linked to both the robotic setup and the fluorescence laparoscope. We evaluated the feasibility of such a setup. Preoperative single-photon emission computed tomography/X-ray computed tomography (SPECT/CT) or intraoperative freehand SPECT (fhSPECT) scans were used to navigate an optically tracked robot-integrated fluorescence laparoscope via an augmented reality overlay in the laparoscopic video feed. The navigation accuracy was evaluated in soft tissue phantoms, followed by studies in a human-like torso phantom. Navigation accuracies found for SPECT/CT-based navigation were 2.25 mm (coronal) and 2.08 mm (sagittal). For fhSPECT-based navigation, these were 1.92 mm (coronal) and 2.83 mm (sagittal). All errors remained below the <1-cm detection limit for fluorescence imaging, allowing refinement of the navigation process using fluorescence findings. The phantom experiments performed suggest that SPECT-based navigation of the robot-integrated fluorescence laparoscope is feasible and may aid fluorescence-guided surgery procedures.
NASA Astrophysics Data System (ADS)
Thomas, Romain; Donikian, Stéphane
Many articles dealing with agent navigation in an urban environment involve the use of various heuristics. Among them, one is prevalent: the search of the shortest path between two points. This strategy impairs the realism of the resulting behaviour. Indeed, psychological studies state that such a navigation behaviour is conditioned by the knowledge the subject has of its environment. Furthermore, the path a city dweller can follow may be influenced by many factors like his daily habits, or the path simplicity in term of minimum of direction changes. It appeared interesting to us to investigate how to mimic human navigation behavior with an autonomous agent. The solution we propose relies on an architecture based on a generic model of informed environment, a spatial cognitive map model merged with a human-like memory model, representing the agent's temporal knowledge of the environment, it gained along its experiences of navigation.
The key technique study of a kind of personal navigation oriented LBS system
NASA Astrophysics Data System (ADS)
Yan, Lei; Zheng, Jianghua; Zhang, Xin; Peng, Chunhua; He, Lina
2005-11-01
With the integration of GIS, IT technology and wireless communication techniques, LBS is fast developing and caused wide concern. Personal navigation is the critical application of LBS. It has higher requirement of data quality, positioning accuracy and multi-model services. The study discusses the key techniques of a personal navigation oriented LBS system. As an example for service platform of China Unicom, NAVISTAR especially emphasizes the importance of spatial data organization. Based-on CDMA1X network, it adopts gpsOne\\MS-Assisted dynamic positioning technique, and puts forward a data organization solution to realize multi-scale representation.
Indoor Spatial Updating with Reduced Visual Information
Legge, Gordon E.; Gage, Rachel; Baek, Yihwa; Bochsler, Tiana M.
2016-01-01
Purpose Spatial updating refers to the ability to keep track of position and orientation while moving through an environment. People with impaired vision may be less accurate in spatial updating with adverse consequences for indoor navigation. In this study, we asked how artificial restrictions on visual acuity and field size affect spatial updating, and also judgments of the size of rooms. Methods Normally sighted young adults were tested with artificial restriction of acuity in Mild Blur (Snellen 20/135) and Severe Blur (Snellen 20/900) conditions, and a Narrow Field (8°) condition. The subjects estimated the dimensions of seven rectangular rooms with and without these visual restrictions. They were also guided along three-segment paths in the rooms. At the end of each path, they were asked to estimate the distance and direction to the starting location. In Experiment 1, the subjects walked along the path. In Experiment 2, they were pushed in a wheelchair to determine if reduced proprioceptive input would result in poorer spatial updating. Results With unrestricted vision, mean Weber fractions for room-size estimates were near 20%. Severe Blur but not Mild Blur yielded larger errors in room-size judgments. The Narrow Field was associated with increased error, but less than with Severe Blur. There was no effect of visual restriction on estimates of distance back to the starting location, and only Severe Blur yielded larger errors in the direction estimates. Contrary to expectation, the wheelchair subjects did not exhibit poorer updating performance than the walking subjects, nor did they show greater dependence on visual condition. Discussion If our results generalize to people with low vision, severe deficits in acuity or field will adversely affect the ability to judge the size of indoor spaces, but updating of position and orientation may be less affected by visual impairment. PMID:26943674
Indoor Spatial Updating with Reduced Visual Information.
Legge, Gordon E; Gage, Rachel; Baek, Yihwa; Bochsler, Tiana M
2016-01-01
Spatial updating refers to the ability to keep track of position and orientation while moving through an environment. People with impaired vision may be less accurate in spatial updating with adverse consequences for indoor navigation. In this study, we asked how artificial restrictions on visual acuity and field size affect spatial updating, and also judgments of the size of rooms. Normally sighted young adults were tested with artificial restriction of acuity in Mild Blur (Snellen 20/135) and Severe Blur (Snellen 20/900) conditions, and a Narrow Field (8°) condition. The subjects estimated the dimensions of seven rectangular rooms with and without these visual restrictions. They were also guided along three-segment paths in the rooms. At the end of each path, they were asked to estimate the distance and direction to the starting location. In Experiment 1, the subjects walked along the path. In Experiment 2, they were pushed in a wheelchair to determine if reduced proprioceptive input would result in poorer spatial updating. With unrestricted vision, mean Weber fractions for room-size estimates were near 20%. Severe Blur but not Mild Blur yielded larger errors in room-size judgments. The Narrow Field was associated with increased error, but less than with Severe Blur. There was no effect of visual restriction on estimates of distance back to the starting location, and only Severe Blur yielded larger errors in the direction estimates. Contrary to expectation, the wheelchair subjects did not exhibit poorer updating performance than the walking subjects, nor did they show greater dependence on visual condition. If our results generalize to people with low vision, severe deficits in acuity or field will adversely affect the ability to judge the size of indoor spaces, but updating of position and orientation may be less affected by visual impairment.
Intelligent Behavioral Action Aiding for Improved Autonomous Image Navigation
2012-09-13
odometry, SICK laser scanning unit ( Lidar ), Inertial Measurement Unit (IMU) and ultrasonic distance measurement system (Figure 32). The Lidar , IMU...2010, July) GPS world. [Online]. http://www.gpsworld.com/tech-talk- blog/gnss-independent-navigation-solution-using-integrated- lidar -data-11378 [4...Milford, David McKinnon, Michael Warren, Gordon Wyeth, and Ben Upcroft, "Feature-based Visual Odometry and Featureless Place Recognition for SLAM in
Hill, Claire; Martin, Jennifer L; Thomson, Simon; Scott-Ram, Nick; Penfold, Hugh; Creswell, Cathy
2017-08-01
This article presents an analysis of challenges and considerations when developing digital mental health innovations. Recommendations include collaborative working between clinicians, researchers, industry and service users in order to successfully navigate challenges and to ensure e-therapies are engaging, acceptable, evidence based, scalable and sustainable. © The Royal College of Psychiatrists 2017.
Minimally invasive surgical video analysis: a powerful tool for surgical training and navigation.
Sánchez-González, P; Oropesa, I; Gómez, E J
2013-01-01
Analysis of minimally invasive surgical videos is a powerful tool to drive new solutions for achieving reproducible training programs, objective and transparent assessment systems and navigation tools to assist surgeons and improve patient safety. This paper presents how video analysis contributes to the development of new cognitive and motor training and assessment programs as well as new paradigms for image-guided surgery.
Junction detection and pathway selection
NASA Astrophysics Data System (ADS)
Peck, Alex N.; Lim, Willie Y.; Breul, Harry T.
1992-02-01
The ability to detect junctions and make choices among the possible pathways is important for autonomous navigation. In our script-based navigation approach where a journey is specified as a script of high-level instructions, actions are frequently referenced to junctions, e.g., `turn left at the intersection.' In order for the robot to carry out these kind of instructions, it must be able (1) to detect an intersection (i.e., an intersection of pathways), (2) know that there are several possible pathways it can take, and (3) pick the pathway consistent with the high level instruction. In this paper we describe our implementation of the ability to detect junctions in an indoor environment, such as corners, T-junctions and intersections, using sonar. Our approach uses a combination of partial scan of the local environment and recognition of sonar signatures of certain features of the junctions. In the case where the environment is known, we use additional sensor information (such as compass bearings) to help recognize the specific junction. In general, once a junction is detected and its type known, the number of possible pathways can be deduced and the correct pathway selected. Then the appropriate behavior for negotiating the junction is activated.
Particle swarm optimization algorithm based low cost magnetometer calibration
NASA Astrophysics Data System (ADS)
Ali, A. S.; Siddharth, S., Syed, Z., El-Sheimy, N.
2011-12-01
Inertial Navigation Systems (INS) consist of accelerometers, gyroscopes and a microprocessor provide inertial digital data from which position and orientation is obtained by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the absolute user heading based on Earth's magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are corrupted by several errors including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO) based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometer. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. The estimated bias and scale factor errors from the proposed algorithm improve the heading accuracy and the results are also statistically significant. Also, it can help in the development of the Pedestrian Navigation Devices (PNDs) when combined with the INS and GPS/Wi-Fi especially in the indoor environments
Port sedimentation solutions for the Tennessee-Tombigbee Waterway in Mississippi.
DOT National Transportation Integrated Search
2004-01-08
Sedimentation of the navigation channel and ports on the Tennessee-Tombigbee Waterway has averaged over 800,000 yd3 per year since completion of the Waterway. The standard solution for the past 17 years has been to dredge the accumulated sediment and...
Using Grid Cells for Navigation.
Bush, Daniel; Barry, Caswell; Manson, Daniel; Burgess, Neil
2015-08-05
Mammals are able to navigate to hidden goal locations by direct routes that may traverse previously unvisited terrain. Empirical evidence suggests that this "vector navigation" relies on an internal representation of space provided by the hippocampal formation. The periodic spatial firing patterns of grid cells in the hippocampal formation offer a compact combinatorial code for location within large-scale space. Here, we consider the computational problem of how to determine the vector between start and goal locations encoded by the firing of grid cells when this vector may be much longer than the largest grid scale. First, we present an algorithmic solution to the problem, inspired by the Fourier shift theorem. Second, we describe several potential neural network implementations of this solution that combine efficiency of search and biological plausibility. Finally, we discuss the empirical predictions of these implementations and their relationship to the anatomy and electrophysiology of the hippocampal formation. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
Expanding the Detection of Traversable Area with RealSense for the Visually Impaired
Yang, Kailun; Wang, Kaiwei; Hu, Weijian; Bai, Jian
2016-01-01
The introduction of RGB-Depth (RGB-D) sensors into the visually impaired people (VIP)-assisting area has stirred great interest of many researchers. However, the detection range of RGB-D sensors is limited by narrow depth field angle and sparse depth map in the distance, which hampers broader and longer traversability awareness. This paper proposes an effective approach to expand the detection of traversable area based on a RGB-D sensor, the Intel RealSense R200, which is compatible with both indoor and outdoor environments. The depth image of RealSense is enhanced with IR image large-scale matching and RGB image-guided filtering. Traversable area is obtained with RANdom SAmple Consensus (RANSAC) segmentation and surface normal vector estimation, preliminarily. A seeded growing region algorithm, combining the depth image and RGB image, enlarges the preliminary traversable area greatly. This is critical not only for avoiding close obstacles, but also for allowing superior path planning on navigation. The proposed approach has been tested on a score of indoor and outdoor scenarios. Moreover, the approach has been integrated into an assistance system, which consists of a wearable prototype and an audio interface. Furthermore, the presented approach has been proved to be useful and reliable by a field test with eight visually impaired volunteers. PMID:27879634
"Creative solutions": selling cigarettes in a smoke-free world
Smith, E; Malone, R
2004-01-01
Objective: To analyse the development and execution of the "Creative Solutions" Benson & Hedges advertising campaign to understand its social, political, and commercial implications. Methods: Searches of the Philip Morris documents and Legacy Tobacco Documents websites for relevant materials; Lexis/Nexis searches of major news and business publications; and denotative and connotative analyses of the advertising imagery. Results: Philip Morris developed the Creative Solutions campaign in an effort to directly confront the successes of the tobacco control movement in establishing new laws and norms that promoted clean indoor air. The campaign's imagery attempted to help smokers and potential smokers overcome the physical and social downsides of smoking cigarettes by managing risk and resolving internal conflict. The slogans suggested a variety of ways for smokers to respond to restrictions on their habit. The campaign also featured information about the Accommodation Program, Philip Morris's attempt to organise opposition to clean indoor air laws. Conclusion: The campaign was a commercial failure, with little impact on sales of the brand. Philip Morris got some exposure for the Accommodation Program and its anti-regulatory position. The lack of commercial response to the ads suggests that they were unable to successfully resolve the contradictions that smokers were increasingly experiencing and confirms the power of changing social norms to counter tobacco industry tactics. PMID:14985598
a Weighted Closed-Form Solution for Rgb-D Data Registration
NASA Astrophysics Data System (ADS)
Vestena, K. M.; Dos Santos, D. R.; Oilveira, E. M., Jr.; Pavan, N. L.; Khoshelham, K.
2016-06-01
Existing 3D indoor mapping of RGB-D data are prominently point-based and feature-based methods. In most cases iterative closest point (ICP) and its variants are generally used for pairwise registration process. Considering that the ICP algorithm requires an relatively accurate initial transformation and high overlap a weighted closed-form solution for RGB-D data registration is proposed. In this solution, we weighted and normalized the 3D points based on the theoretical random errors and the dual-number quaternions are used to represent the 3D rigid body motion. Basically, dual-number quaternions provide a closed-form solution by minimizing a cost function. The most important advantage of the closed-form solution is that it provides the optimal transformation in one-step, it does not need to calculate good initial estimates and expressively decreases the demand for computer resources in contrast to the iterative method. Basically, first our method exploits RGB information. We employed a scale invariant feature transformation (SIFT) for extracting, detecting, and matching features. It is able to detect and describe local features that are invariant to scaling and rotation. To detect and filter outliers, we used random sample consensus (RANSAC) algorithm, jointly with an statistical dispersion called interquartile range (IQR). After, a new RGB-D loop-closure solution is implemented based on the volumetric information between pair of point clouds and the dispersion of the random errors. The loop-closure consists to recognize when the sensor revisits some region. Finally, a globally consistent map is created to minimize the registration errors via a graph-based optimization. The effectiveness of the proposed method is demonstrated with a Kinect dataset. The experimental results show that the proposed method can properly map the indoor environment with an absolute accuracy around 1.5% of the travel of a trajectory.
Passivhaus: indoor comfort and energy dynamic analysis.
NASA Astrophysics Data System (ADS)
Guida, Antonella; Pagliuca, Antonello; Cardinale, Nicola; Rospi, Gianluca
2013-04-01
The research aims to verify the energy performance as well as the indoor comfort of an energy class A+ building, built so that the sum of the heat passive contributions of solar radiation, transmitted through the windows, and the heat generated inside the building, are adeguate to compensate for the envelope loss during the cold season. The building, located in Emilia Romagna (Italy), was built using a wooden structure, an envelope realized using a pinewood sandwich panels (transmittance U = 0.250 W/m2K) and, inside, a wool flax insulation layer and thermal window frame with low-emissivity glass (U = 0524 W/m2K). The building design and construction process has followed the guidelines set by "CasaClima". The building has been modeled in the code of dynamic calculation "Energy Plus" by the Design Builder application and divided it into homogenous thermal zones, characterized by winter indoor temperature set at 20 ° (+ / - 1 °) and summer indoor temperature set at 26 ° (+ / - 1 °). It has modeled: the envelope, as described above, the "free" heat contributions, the air conditioning system, the Mechanical Ventilation system as well as home automation solutions. The air conditioning system is an heat pump, able to guarantee an optimization of energy consumption (in fact, it uses the "free" heat offered by the external environment for conditioning indoor environment). As regards the air recirculation system, it has been used a mechanical ventilation system with internal heat cross-flow exchanger, with an efficiency equal to 50%. The domotic solutions, instead, regard a system for the control of windows external screening using reeds, adjustable as a function of incident solar radiation and a lighting management system adjusted automatically using a dimmer. A so realized building meets the requirement imposed from Italian standard UNI/TS 11300 1, UNI/TS 11300 2 and UNI/TS 11300 3. The analysis was performed according to two different configurations: in "spontaneous-state analysis" (that provides the only energy performance of the structure) and considering the "building-equipments" as a system (which provides the overall performance of the "building system"). The first analysis shows as the absence of thermal mass and the envelope super-heating prevent to incoming heat to exit, overheating the indoor environment. The analysis of the overall performance of the "building system" highlights, instead, as the thermal load is much greater during the summer than in winter; this means that, using a low inertia envelopes, the energy saved in the winter can be used to satisfy the thermal performance in the summer. This is further demonstrated by comparing the performance of indoor temperatures and the relative energy consumption of a similar building with greater thermal inertia. Further analysis involved a critical comparison between the "semisteady-state analysis" ("CasaClima" methodology) and the analysis in dynamic conditions (using "Energy Plus" software).
GPS Navigation Results from the Low Power Transceiver CANDOS Experiment on STS-107
NASA Technical Reports Server (NTRS)
Haas, Lin; Massey, Chris; Baraban, Dmitri; Kelbel, David; Lee, Taesul; Long, Anne; Carpenter, J. Russell
2003-01-01
This paper presents the Global Positioning System (GPS) navigation results from the Communications and Savigation Demonstration on Shuttle (CANDOS) experiment flown on STS- 107. The CAkDOS experiment consisted of the Low Power Transceiver (LPT) that hosted the GPS Enhanced Orbit Determination Experiment (GEODE) orbit determination software. All CANDOS test data were recovered during the mission using the LPT's Tracking and Data Relay Satellite System (TDRSS) uplinh'downlink communications capabilit! . An overview of the LPT's navigation software and the GPS experiment timeline is presented. In addition. this paper discusses GEODE performance results. including comparisons ibith the Best Estimate of Trajectory (BET). N.ASA Johnson Space Center (JSC) real-time ground navigation vectors. and post-processed solutions using the Goddard Trajectory Determination System (GTDS).
Autonomous optical navigation using nanosatellite-class instruments: a Mars approach case study
NASA Astrophysics Data System (ADS)
Enright, John; Jovanovic, Ilija; Kazemi, Laila; Zhang, Harry; Dzamba, Tom
2018-02-01
This paper examines the effectiveness of small star trackers for orbital estimation. Autonomous optical navigation has been used for some time to provide local estimates of orbital parameters during close approach to celestial bodies. These techniques have been used extensively on spacecraft dating back to the Voyager missions, but often rely on long exposures and large instrument apertures. Using a hyperbolic Mars approach as a reference mission, we present an EKF-based navigation filter suitable for nanosatellite missions. Observations of Mars and its moons allow the estimator to correct initial errors in both position and velocity. Our results show that nanosatellite-class star trackers can produce good quality navigation solutions with low position (<300 {m}) and velocity (<0.15 {m/s}) errors as the spacecraft approaches periapse.
DOT National Transportation Integrated Search
2002-11-01
Sedimentation of the navigation channel and ports on the Tennessee-Tombigbee : Waterway has averaged over 800,000 yd3 per year since completion of the Waterway. : The standard solution for the past 17 years has been to dredge the accumulated : sedime...
A Review of Photocatalysts Prepared by Sol-Gel Method for VOCs Removal
Tseng, Ting Ke; Lin, Yi Shing; Chen, Yi Ju; Chu, Hsin
2010-01-01
The sol-gel process is a wet-chemical technique (chemical solution deposition), which has been widely used in the fields of materials science, ceramic engineering, and especially in the preparation of photocatalysts. Volatile organic compounds (VOCs) are prevalent components of indoor air pollution. Among the approaches to remove VOCs from indoor air, photocatalytic oxidation (PCO) is regarded as a promising method. This paper is a review of the status of research on the sol-gel method for photocatalyst preparation and for the PCO purification of VOCs. The review and discussion will focus on the preparation and coating of various photocatalysts, operational parameters, and will provide an overview of general PCO models described in the literature. PMID:20640156
Formaldehyde (HCHO) has been of special concern as an indoor air pollutant because of its existence in a wide range of products and its adverse health effects. The air-water partitioning behavior of volatile organic compounds (VOCs) such as formaldehyde is an important process th...
Stereo vision tracking of multiple objects in complex indoor environments.
Marrón-Romera, Marta; García, Juan C; Sotelo, Miguel A; Pizarro, Daniel; Mazo, Manuel; Cañas, José M; Losada, Cristina; Marcos, Alvaro
2010-01-01
This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot's environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors' proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found.
Map based navigation for autonomous underwater vehicles
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tuohy, S.T.; Leonard, J.J.; Bellingham, J.G.
1995-12-31
In this work, a map based navigation algorithm is developed wherein measured geophysical properties are matched to a priori maps. The objectives is a complete algorithm applicable to a small, power-limited AUV which performs in real time to a required resolution with bounded position error. Interval B-Splines are introduced for the non-linear representation of two-dimensional geophysical parameters that have measurement uncertainty. Fine-scale position determination involves the solution of a system of nonlinear polynomial equations with interval coefficients. This system represents the complete set of possible vehicle locations and is formulated as the intersection of contours established on each map frommore » the simultaneous measurement of associated geophysical parameters. A standard filter mechanisms, based on a bounded interval error model, predicts the position of the vehicle and, therefore, screens extraneous solutions. When multiple solutions are found, a tracking mechanisms is applied until a unique vehicle location is determined.« less
Navigation in Difficult Environments: Multi-Sensor Fusion Techniques
2010-03-01
Hwang , Introduction to Random Signals and Applied Kalman Filtering, 3rd ed., John Wiley & Sons, Inc., New York, 1997. [17] J. L. Farrell, “GPS/INS...nav solution Navigation outputs Estimation of inertial errors ( Kalman filter) Error estimates Core sensor Incoming signal INS Estimates of signal...the INS drift terms is performed using the mechanism of a complementary Kalman filter. The idea is that a signal parameter can be generally
Inertial Navigation System/Doppler Velocity Log (INS/DVL) Fusion with Partial DVL Measurements
Tal, Asaf; Klein, Itzik; Katz, Reuven
2017-01-01
The Technion autonomous underwater vehicle (TAUV) is an ongoing project aiming to develop and produce a small AUV to carry on research missions, including payload dropping, and to demonstrate acoustic communication. Its navigation system is based on an inertial navigation system (INS) aided by a Doppler velocity log (DVL), magnetometer, and pressure sensor (PS). In many INSs, such as the one used in TAUV, only the velocity vector (provided by the DVL) can be used for aiding the INS, i.e., enabling only a loosely coupled integration approach. In cases of partial DVL measurements, such as failure to maintain bottom lock, the DVL cannot estimate the vehicle velocity. Thus, in partial DVL situations no velocity data can be integrated into the TAUV INS, and as a result its navigation solution will drift in time. To circumvent that problem, we propose a DVL-based vehicle velocity solution using the measured partial raw data of the DVL and additional information, thereby deriving an extended loosely coupled (ELC) approach. The implementation of the ELC approach requires only software modification. In addition, we present the TAUV six degrees of freedom (6DOF) simulation that includes all functional subsystems. Using this simulation, the proposed approach is evaluated and the benefit of using it is shown. PMID:28241410
Inertial Navigation System/Doppler Velocity Log (INS/DVL) Fusion with Partial DVL Measurements.
Tal, Asaf; Klein, Itzik; Katz, Reuven
2017-02-22
The Technion autonomous underwater vehicle (TAUV) is an ongoing project aiming to develop and produce a small AUV to carry on research missions, including payload dropping, and to demonstrate acoustic communication. Its navigation system is based on an inertial navigation system (INS) aided by a Doppler velocity log (DVL), magnetometer, and pressure sensor (PS). In many INSs, such as the one used in TAUV, only the velocity vector (provided by the DVL) can be used for aiding the INS, i.e., enabling only a loosely coupled integration approach. In cases of partial DVL measurements, such as failure to maintain bottom lock, the DVL cannot estimate the vehicle velocity. Thus, in partial DVL situations no velocity data can be integrated into the TAUV INS, and as a result its navigation solution will drift in time. To circumvent that problem, we propose a DVL-based vehicle velocity solution using the measured partial raw data of the DVL and additional information, thereby deriving an extended loosely coupled (ELC) approach. The implementation of the ELC approach requires only software modification. In addition, we present the TAUV six degrees of freedom (6DOF) simulation that includes all functional subsystems. Using this simulation, the proposed approach is evaluated and the benefit of using it is shown.
Neal, Chrishanae D; Weaver, Davis T; Raphel, Tiana J; Lietz, Anna P; Flores, Efren J; Percac-Lima, Sanja; Knudsen, Amy B; Pandharipande, Pari V
2018-04-20
Our goal is to define patient navigation for an imaging audience, present a focused selection of published experiences with navigation programs for breast and colorectal cancer screening, and expose principal barriers to the success of such programs. Despite numerous advances in the early detection of cancers, many patients still present with advanced disease. A disproportionate number are low-income minority patients who experience worse health outcomes than their white or more financially stable counterparts. Patient navigation, which aims to assist the medically underserved by overcoming specific barriers to care, may represent one solution to narrowing disparities. Related research suggests that in general, patient navigation programs that have addressed breast or colorectal cancer screening have been successful in improving screening rates and timeliness of follow-up care. However, although beneficial, navigation is expensive and may present an unmanageable financial burden for many health care centers. To overcome this challenge, navigation efforts will likely need to target those patients that are most likely to benefit. Further research to identify such patients will be critically important for improving the sustainability of navigation programs, and, in turn, for realizing the benefits of such programs in reducing cancer disparities. Copyright © 2018. Published by Elsevier Inc.
Pollard, Suzanne L; Williams, D'Ann L; Breysse, Patrick N; Baron, Patrick A; Grajeda, Laura M; Gilman, Robert H; Miranda, J Jaime; Checkley, William
2014-03-24
Burning biomass fuels indoors for cooking is associated with high concentrations of particulate matter (PM) and carbon monoxide (CO). More efficient biomass-burning stoves and chimneys for ventilation have been proposed as solutions to reduce indoor pollution. We sought to quantify indoor PM and CO exposures in urban and rural households and determine factors associated with higher exposures. A secondary objective was to identify chronic vs. acute changes in cardiopulmonary biomarkers associated with exposure to biomass smoke. We conducted a census survey followed by a cross-sectional study of indoor environmental exposures and cardiopulmonary biomarkers in the main household cook in Puno, Peru. We measured 24-hour indoor PM and CO concentrations in 86 households. We also measured PM2.5 and PM10 concentrations gravimetrically for 24 hours in urban households and during cook times in rural households, and generated a calibration equation using PM2.5 measurements. In a census of 4903 households, 93% vs. 16% of rural vs. urban households used an open-fire stove; 22% of rural households had a homemade chimney; and <3% of rural households participated in a national program encouraging installation of a chimney. Median 24-hour indoor PM2.5 and CO concentrations were 130 vs. 22 μg/m3 and 5.8 vs. 0.4 ppm (all p<0.001) in rural vs. urban households. Having a chimney did not significantly reduce median concentrations in 24-hour indoor PM2.5 (119 vs. 137 μg/m3; p=0.40) or CO (4.6 vs. 7.2 ppm; p=0.23) among rural households with and without chimneys. Having a chimney did not significantly reduce median cook-time PM2.5 (360 vs. 298 μg/m3, p=0.45) or cook-time CO concentrations (15.2 vs. 9.4 ppm, p=0.23). Having a thatched roof (p=0.007) and hours spent cooking (p=0.02) were associated with higher 24-hour average PM concentrations. Rural participants had higher median exhaled CO (10 vs. 6 ppm; p=0.01) and exhaled carboxyhemoglobin (1.6% vs. 1.0%; p=0.04) than urban participants. Indoor air concentrations associated with biomass smoke were six-fold greater in rural vs. urban households. Having a homemade chimney did not reduce environmental exposures significantly. Measures of exhaled CO provide useful cardiopulmonary biomarkers for chronic exposure to biomass smoke.
2014-01-01
Background Burning biomass fuels indoors for cooking is associated with high concentrations of particulate matter (PM) and carbon monoxide (CO). More efficient biomass-burning stoves and chimneys for ventilation have been proposed as solutions to reduce indoor pollution. We sought to quantify indoor PM and CO exposures in urban and rural households and determine factors associated with higher exposures. A secondary objective was to identify chronic vs. acute changes in cardiopulmonary biomarkers associated with exposure to biomass smoke. Methods We conducted a census survey followed by a cross-sectional study of indoor environmental exposures and cardiopulmonary biomarkers in the main household cook in Puno, Peru. We measured 24-hour indoor PM and CO concentrations in 86 households. We also measured PM2.5 and PM10 concentrations gravimetrically for 24 hours in urban households and during cook times in rural households, and generated a calibration equation using PM2.5 measurements. Results In a census of 4903 households, 93% vs. 16% of rural vs. urban households used an open-fire stove; 22% of rural households had a homemade chimney; and <3% of rural households participated in a national program encouraging installation of a chimney. Median 24-hour indoor PM2.5 and CO concentrations were 130 vs. 22 μg/m3 and 5.8 vs. 0.4 ppm (all p<0.001) in rural vs. urban households. Having a chimney did not significantly reduce median concentrations in 24-hour indoor PM2.5 (119 vs. 137 μg/m3; p=0.40) or CO (4.6 vs. 7.2 ppm; p=0.23) among rural households with and without chimneys. Having a chimney did not significantly reduce median cook-time PM2.5 (360 vs. 298 μg/m3, p=0.45) or cook-time CO concentrations (15.2 vs. 9.4 ppm, p=0.23). Having a thatched roof (p=0.007) and hours spent cooking (p=0.02) were associated with higher 24-hour average PM concentrations. Rural participants had higher median exhaled CO (10 vs. 6 ppm; p=0.01) and exhaled carboxyhemoglobin (1.6% vs. 1.0%; p=0.04) than urban participants. Conclusions Indoor air concentrations associated with biomass smoke were six-fold greater in rural vs. urban households. Having a homemade chimney did not reduce environmental exposures significantly. Measures of exhaled CO provide useful cardiopulmonary biomarkers for chronic exposure to biomass smoke. PMID:24655424
The problem of the driverless vehicle specified path stability control
NASA Astrophysics Data System (ADS)
Buznikov, S. E.; Endachev, D. V.; Elkin, D. S.; Strukov, V. O.
2018-02-01
Currently the effort of many leading foreign companies is focused on creation of driverless transport for transportation of cargo and passengers. Among many practical problems arising while creating driverless vehicles, the problem of the specified path stability control occupies a central place. The purpose of this paper is formalization of the problem in question in terms of the quadratic functional of the control quality, the comparative analysis of the possible solutions and justification of the choice of the optimum technical solution. As square value of the integral of the deviation from the specified path is proposed as the quadratic functional of the control quality. For generation of the set of software and hardware solution variants the Zwicky “morphological box” method is used within the hardware and software environments. The heading control algorithms use the wheel steering angle data and the deviation from the lane centerline (specified path) calculated based on the navigation data and the data from the video system. Where the video system does not detect the road marking, the control is carried out based on the wheel navigation system data and where recognizable road marking exits - based on to the video system data. The analysis of the test results allows making the conclusion that the application of the combined navigation system algorithms that provide quasi-optimum solution of the problem while meeting the strict functional limits for the technical and economic indicators of the driverless vehicle control system under development is effective.
Sensor-Data Fusion for Multi-Person Indoor Location Estimation
2017-01-01
We consider the problem of estimating the location of people as they move and work in indoor environments. More specifically, we focus on the scenario where one of the persons of interest is unable or unwilling to carry a smartphone, or any other “wearable” device, which frequently arises in caregiver/cared-for situations. We consider the case of indoor spaces populated with anonymous binary sensors (Passive Infrared motion sensors) and eponymous wearable sensors (smartphones interacting with Estimote beacons), and we propose a solution to the resulting sensor-fusion problem. Using a data set with sensor readings collected from one-person and two-person sessions engaged in a variety of activities of daily living, we investigate the relative merits of relying solely on anonymous sensors, solely on eponymous sensors, or on their combination. We examine how the lack of synchronization across different sensing sources impacts the quality of location estimates, and discuss how it could be mitigated without resorting to device-level mechanisms. Finally, we examine the trade-off between the sensors’ coverage of the monitored space and the quality of the location estimates. PMID:29057812
A Low Complexity System Based on Multiple Weighted Decision Trees for Indoor Localization
Sánchez-Rodríguez, David; Hernández-Morera, Pablo; Quinteiro, José Ma.; Alonso-González, Itziar
2015-01-01
Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important characteristics, because both the processor power and energy availability are limited. Hence, an indoor localization system with high computational complexity can cause complete battery drain within a few hours. In our research, we use a data mining technique named boosting to develop a localization system based on multiple weighted decision trees to predict the device location, since it has high accuracy and low computational complexity. The localization system is built using a dataset from sensor fusion, which combines the strength of radio signals from different wireless local area network access points and device orientation information from a digital compass built-in mobile device, so that extra sensors are unnecessary. Experimental results indicate that the proposed system leads to substantial improvements on computational complexity over the widely-used traditional fingerprinting methods, and it has a better accuracy than they have. PMID:26110413
Sensor-Data Fusion for Multi-Person Indoor Location Estimation.
Mohebbi, Parisa; Stroulia, Eleni; Nikolaidis, Ioanis
2017-10-18
We consider the problem of estimating the location of people as they move and work in indoor environments. More specifically, we focus on the scenario where one of the persons of interest is unable or unwilling to carry a smartphone, or any other "wearable" device, which frequently arises in caregiver/cared-for situations. We consider the case of indoor spaces populated with anonymous binary sensors (Passive Infrared motion sensors) and eponymous wearable sensors (smartphones interacting with Estimote beacons), and we propose a solution to the resulting sensor-fusion problem. Using a data set with sensor readings collected from one-person and two-person sessions engaged in a variety of activities of daily living, we investigate the relative merits of relying solely on anonymous sensors, solely on eponymous sensors, or on their combination. We examine how the lack of synchronization across different sensing sources impacts the quality of location estimates, and discuss how it could be mitigated without resorting to device-level mechanisms. Finally, we examine the trade-off between the sensors' coverage of the monitored space and the quality of the location estimates.
CSAC Characterization and Its Impact on GNSS Clock Augmentation Performance
Fernández, Enric; Calero, David; Parés, M. Eulàlia
2017-01-01
Chip Scale Atomic Clocks (CSAC) are recently-developed electronic instruments that, when used together with a Global Navigation Satellite Systems (GNSS) receiver, help improve the performance of GNSS navigation solutions in certain conditions (i.e., low satellite visibility). Current GNSS receivers include a Temperature Compensated Cristal Oscillator (TCXO) clock characterized by a short-term stability (τ = 1 s) of 10−9 s that leads to an error of 0.3 m in pseudorange measurements. The CSAC can achieve a short-term stability of 2.5 × 10−12 s, which implies a range error of 0.075 m, making for an 87.5% improvement over TCXO. Replacing the internal TCXO clock of GNSS receivers with a higher frequency stability clock such as a CSAC oscillator improves the navigation solution in terms of low satellite visibility positioning accuracy, solution availability, signal recovery (holdover), multipath and jamming mitigation and spoofing attack detection. However, CSAC suffers from internal systematic instabilities and errors that should be minimized if optimal performance is desired. Hence, for operating CSAC at its best, the deterministic errors from the CSAC need to be properly modelled. Currently, this modelling is done by determining and predicting the clock frequency stability (i.e., clock bias and bias rate) within the positioning estimation process. The research presented in this paper aims to go a step further, analysing the correlation between temperature and clock stability noise and the impact of its proper modelling in the holdover recovery time and in the positioning performance. Moreover, it shows the potential of fine clock coasting modelling. With the proposed model, an improvement in vertical positioning precision of around 50% with only three satellites can be achieved. Moreover, an increase in the navigation solution availability is also observed, a reduction of holdover recovery time from dozens of seconds to only a few can be achieved. PMID:28216600
CSAC Characterization and Its Impact on GNSS Clock Augmentation Performance.
Fernández, Enric; Calero, David; Parés, M Eulàlia
2017-02-14
Chip Scale Atomic Clocks (CSAC) are recently-developed electronic instruments that, when used together with a Global Navigation Satellite Systems (GNSS) receiver, help improve the performance of GNSS navigation solutions in certain conditions (i.e., low satellite visibility). Current GNSS receivers include a Temperature Compensated Cristal Oscillator (TCXO) clock characterized by a short-term stability ( τ = 1 s) of 10 -9 s that leads to an error of 0.3 m in pseudorange measurements. The CSAC can achieve a short-term stability of 2.5 × 10 -12 s, which implies a range error of 0.075 m, making for an 87.5% improvement over TCXO. Replacing the internal TCXO clock of GNSS receivers with a higher frequency stability clock such as a CSAC oscillator improves the navigation solution in terms of low satellite visibility positioning accuracy, solution availability, signal recovery (holdover), multipath and jamming mitigation and spoofing attack detection. However, CSAC suffers from internal systematic instabilities and errors that should be minimized if optimal performance is desired. Hence, for operating CSAC at its best, the deterministic errors from the CSAC need to be properly modelled. Currently, this modelling is done by determining and predicting the clock frequency stability (i.e., clock bias and bias rate) within the positioning estimation process. The research presented in this paper aims to go a step further, analysing the correlation between temperature and clock stability noise and the impact of its proper modelling in the holdover recovery time and in the positioning performance. Moreover, it shows the potential of fine clock coasting modelling. With the proposed model, an improvement in vertical positioning precision of around 50% with only three satellites can be achieved. Moreover, an increase in the navigation solution availability is also observed, a reduction of holdover recovery time from dozens of seconds to only a few can be achieved.
Li, Hong; Liu, Mingyong; Zhang, Feihu
2017-01-01
This paper presents a multi-objective evolutionary algorithm of bio-inspired geomagnetic navigation for Autonomous Underwater Vehicle (AUV). Inspired by the biological navigation behavior, the solution was proposed without using a priori information, simply by magnetotaxis searching. However, the existence of the geomagnetic anomalies has significant influence on the geomagnetic navigation system, which often disrupts the distribution of the geomagnetic field. An extreme value region may easily appear in abnormal regions, which makes AUV lost in the navigation phase. This paper proposes an improved bio-inspired algorithm with behavior constraints, for sake of making AUV escape from the abnormal region. First, the navigation problem is considered as the optimization problem. Second, the environmental monitoring operator is introduced, to determine whether the algorithm falls into the geomagnetic anomaly region. Then, the behavior constraint operator is employed to get out of the abnormal region. Finally, the termination condition is triggered. Compared to the state-of- the-art, the proposed approach effectively overcomes the disturbance of the geomagnetic abnormal. The simulation result demonstrates the reliability and feasibility of the proposed approach in complex environments.
Li, Hong; Liu, Mingyong; Zhang, Feihu
2017-01-01
This paper presents a multi-objective evolutionary algorithm of bio-inspired geomagnetic navigation for Autonomous Underwater Vehicle (AUV). Inspired by the biological navigation behavior, the solution was proposed without using a priori information, simply by magnetotaxis searching. However, the existence of the geomagnetic anomalies has significant influence on the geomagnetic navigation system, which often disrupts the distribution of the geomagnetic field. An extreme value region may easily appear in abnormal regions, which makes AUV lost in the navigation phase. This paper proposes an improved bio-inspired algorithm with behavior constraints, for sake of making AUV escape from the abnormal region. First, the navigation problem is considered as the optimization problem. Second, the environmental monitoring operator is introduced, to determine whether the algorithm falls into the geomagnetic anomaly region. Then, the behavior constraint operator is employed to get out of the abnormal region. Finally, the termination condition is triggered. Compared to the state-of- the-art, the proposed approach effectively overcomes the disturbance of the geomagnetic abnormal. The simulation result demonstrates the reliability and feasibility of the proposed approach in complex environments. PMID:28747884
Embedded Relative Navigation Sensor Fusion Algorithms for Autonomous Rendezvous and Docking Missions
NASA Technical Reports Server (NTRS)
DeKock, Brandon K.; Betts, Kevin M.; McDuffie, James H.; Dreas, Christine B.
2008-01-01
bd Systems (a subsidiary of SAIC) has developed a suite of embedded relative navigation sensor fusion algorithms to enable NASA autonomous rendezvous and docking (AR&D) missions. Translational and rotational Extended Kalman Filters (EKFs) were developed for integrating measurements based on the vehicles' orbital mechanics and high-fidelity sensor error models and provide a solution with increased accuracy and robustness relative to any single relative navigation sensor. The filters were tested tinough stand-alone covariance analysis, closed-loop testing with a high-fidelity multi-body orbital simulation, and hardware-in-the-loop (HWIL) testing in the Marshall Space Flight Center (MSFC) Flight Robotics Laboratory (FRL).
Use of Earth's magnetic field for mitigating gyroscope errors regardless of magnetic perturbation.
Afzal, Muhammad Haris; Renaudin, Valérie; Lachapelle, Gérard
2011-01-01
Most portable systems like smart-phones are equipped with low cost consumer grade sensors, making them useful as Pedestrian Navigation Systems (PNS). Measurements of these sensors are severely contaminated by errors caused due to instrumentation and environmental issues rendering the unaided navigation solution with these sensors of limited use. The overall navigation error budget associated with pedestrian navigation can be categorized into position/displacement errors and attitude/orientation errors. Most of the research is conducted for tackling and reducing the displacement errors, which either utilize Pedestrian Dead Reckoning (PDR) or special constraints like Zero velocity UPdaTes (ZUPT) and Zero Angular Rate Updates (ZARU). This article targets the orientation/attitude errors encountered in pedestrian navigation and develops a novel sensor fusion technique to utilize the Earth's magnetic field, even perturbed, for attitude and rate gyroscope error estimation in pedestrian navigation environments where it is assumed that Global Navigation Satellite System (GNSS) navigation is denied. As the Earth's magnetic field undergoes severe degradations in pedestrian navigation environments, a novel Quasi-Static magnetic Field (QSF) based attitude and angular rate error estimation technique is developed to effectively use magnetic measurements in highly perturbed environments. The QSF scheme is then used for generating the desired measurements for the proposed Extended Kalman Filter (EKF) based attitude estimator. Results indicate that the QSF measurements are capable of effectively estimating attitude and gyroscope errors, reducing the overall navigation error budget by over 80% in urban canyon environment.
Use of Earth’s Magnetic Field for Mitigating Gyroscope Errors Regardless of Magnetic Perturbation
Afzal, Muhammad Haris; Renaudin, Valérie; Lachapelle, Gérard
2011-01-01
Most portable systems like smart-phones are equipped with low cost consumer grade sensors, making them useful as Pedestrian Navigation Systems (PNS). Measurements of these sensors are severely contaminated by errors caused due to instrumentation and environmental issues rendering the unaided navigation solution with these sensors of limited use. The overall navigation error budget associated with pedestrian navigation can be categorized into position/displacement errors and attitude/orientation errors. Most of the research is conducted for tackling and reducing the displacement errors, which either utilize Pedestrian Dead Reckoning (PDR) or special constraints like Zero velocity UPdaTes (ZUPT) and Zero Angular Rate Updates (ZARU). This article targets the orientation/attitude errors encountered in pedestrian navigation and develops a novel sensor fusion technique to utilize the Earth’s magnetic field, even perturbed, for attitude and rate gyroscope error estimation in pedestrian navigation environments where it is assumed that Global Navigation Satellite System (GNSS) navigation is denied. As the Earth’s magnetic field undergoes severe degradations in pedestrian navigation environments, a novel Quasi-Static magnetic Field (QSF) based attitude and angular rate error estimation technique is developed to effectively use magnetic measurements in highly perturbed environments. The QSF scheme is then used for generating the desired measurements for the proposed Extended Kalman Filter (EKF) based attitude estimator. Results indicate that the QSF measurements are capable of effectively estimating attitude and gyroscope errors, reducing the overall navigation error budget by over 80% in urban canyon environment. PMID:22247672
Ye, Wei; Zhang, Xu; Gao, Jun; Cao, Guangyu; Zhou, Xiang; Su, Xing
2017-05-15
After nearly twenty years of rapid modernization and urbanization in China, huge achievements have transformed the daily lives of the Chinese people. However, unprecedented environmental consequences in both indoor and outdoor environments have accompanied this progress and have triggered public awareness and demands for improved living standards, especially in residential environments. Indoor pollution data measured for >7000 dwellings (approximately 1/3 were newly decorated and were tested for volatile organic compound (VOC) measurements, while the rest were tested for particles, phthalates and other semi-volatile organic compounds (SVOCs), moisture/mold, inorganic gases and radon) in China within the last ten years were reviewed, summarized and compared with indoor concentration recommendations based on sensory or health end-points. Ubiquitous pollutants that exceed the concentration recommendations, including particulate matter, formaldehyde, benzene and other VOCs, moisture/mold, inorganic gases and radon, were found, indicating a common indoor air quality (IAQ) issue in Chinese dwellings. With very little prevention, oral, inhalation and dermal exposure to those pollutants at unhealthy concentration levels is almost inevitable. CO 2 , VOCs, humidity and radon can serve as ventilation determinants, each with different ventilation demands and strategies, at typical occupant densities in China; and particle reduction should be a prerequisite for determining ventilation requirements. Two directional ventilation modes would have profound impacts on improving IAQ for Chinese residences are: 1) natural (or window) ventilation with an air cleaner and 2) mechanical ventilation with an air filtration unit, these two modes were reviewed and compared for their applicability and advantages and disadvantages for reducing human exposure to indoor air pollutants. In general, mode 2 can more reliably ensure good IAQ for occupants; while mode 1 is more applicable due to its low cost and low energy consumption. However, besides a roadmap, substantial efforts are still needed to develop affordable, applicable and general ventilation solutions to improve the IAQ of residential buildings in China. Copyright © 2017 Elsevier B.V. All rights reserved.
A research on the positioning technology of vehicle navigation system from single source to "ASPN"
NASA Astrophysics Data System (ADS)
Zhang, Jing; Li, Haizhou; Chen, Yu; Chen, Hongyue; Sun, Qian
2017-10-01
Due to the suddenness and complexity of modern warfare, land-based weapon systems need to have precision strike capability on roads and railways. The vehicle navigation system is one of the most important equipments for the land-based weapon systems that have precision strick capability. There are inherent shortcomings for single source navigation systems to provide continuous and stable navigation information. To overcome the shortcomings, the multi-source positioning technology is developed. The All Source Positioning and Navigaiton (ASPN) program was proposed in 2010, which seeks to enable low cost, robust, and seamless navigation solutions for military to use on any operational platform and in any environment with or without GPS. The development trend of vehicle positioning technology was reviewed in this paper. The trend indicates that the positioning technology is developed from single source and multi-source to ASPN. The data fusion techniques based on multi-source and ASPN was analyzed in detail.
Navigation Aiding by a Hybrid Laser-Camera Motion Estimator for Micro Aerial Vehicles.
Atman, Jamal; Popp, Manuel; Ruppelt, Jan; Trommer, Gert F
2016-09-16
Micro Air Vehicles (MAVs) equipped with various sensors are able to carry out autonomous flights. However, the self-localization of autonomous agents is mostly dependent on Global Navigation Satellite Systems (GNSS). In order to provide an accurate navigation solution in absence of GNSS signals, this article presents a hybrid sensor. The hybrid sensor is a deep integration of a monocular camera and a 2D laser rangefinder so that the motion of the MAV is estimated. This realization is expected to be more flexible in terms of environments compared to laser-scan-matching approaches. The estimated ego-motion is then integrated in the MAV's navigation system. However, first, the knowledge about the pose between both sensors is obtained by proposing an improved calibration method. For both calibration and ego-motion estimation, 3D-to-2D correspondences are used and the Perspective-3-Point (P3P) problem is solved. Moreover, the covariance estimation of the relative motion is presented. The experiments show very accurate calibration and navigation results.
Design and testing of a multi-sensor pedestrian location and navigation platform.
Morrison, Aiden; Renaudin, Valérie; Bancroft, Jared B; Lachapelle, Gérard
2012-01-01
Navigation and location technologies are continually advancing, allowing ever higher accuracies and operation under ever more challenging conditions. The development of such technologies requires the rapid evaluation of a large number of sensors and related utilization strategies. The integration of Global Navigation Satellite Systems (GNSSs) such as the Global Positioning System (GPS) with accelerometers, gyros, barometers, magnetometers and other sensors is allowing for novel applications, but is hindered by the difficulties to test and compare integrated solutions using multiple sensor sets. In order to achieve compatibility and flexibility in terms of multiple sensors, an advanced adaptable platform is required. This paper describes the design and testing of the NavCube, a multi-sensor navigation, location and timing platform. The system provides a research tool for pedestrian navigation, location and body motion analysis in an unobtrusive form factor that enables in situ data collections with minimal gait and posture impact. Testing and examples of applications of the NavCube are provided.
Jiang, Weiping; Wang, Li; Niu, Xiaoji; Zhang, Quan; Zhang, Hui; Tang, Min; Hu, Xiangyun
2014-01-01
A high-precision image-aided inertial navigation system (INS) is proposed as an alternative to the carrier-phase-based differential Global Navigation Satellite Systems (CDGNSSs) when satellite-based navigation systems are unavailable. In this paper, the image/INS integrated algorithm is modeled by a tightly-coupled iterative extended Kalman filter (IEKF). Tightly-coupled integration ensures that the integrated system is reliable, even if few known feature points (i.e., less than three) are observed in the images. A new global observability analysis of this tightly-coupled integration is presented to guarantee that the system is observable under the necessary conditions. The analysis conclusions were verified by simulations and field tests. The field tests also indicate that high-precision position (centimeter-level) and attitude (half-degree-level)-integrated solutions can be achieved in a global reference. PMID:25330046
Design and Development of a Mobile Sensor Based the Blind Assistance Wayfinding System
NASA Astrophysics Data System (ADS)
Barati, F.; Delavar, M. R.
2015-12-01
The blind and visually impaired people are facing a number of challenges in their daily life. One of the major challenges is finding their way both indoor and outdoor. For this reason, routing and navigation independently, especially in urban areas are important for the blind. Most of the blind undertake route finding and navigation with the help of a guide. In addition, other tools such as a cane, guide dog or electronic aids are used by the blind. However, in some cases these aids are not efficient enough in a wayfinding around obstacles and dangerous areas for the blind. As a result, the need to develop effective methods as decision support using a non-visual media is leading to improve quality of life for the blind through their increased mobility and independence. In this study, we designed and implemented an outdoor mobile sensor-based wayfinding system for the blind. The objectives of this study are to guide the blind for the obstacle recognition and the design and implementation of a wayfinding and navigation mobile sensor system for them. In this study an ultrasonic sensor is used to detect obstacles and GPS is employed for positioning and navigation in the wayfinding. This type of ultrasonic sensor measures the interval between sending waves and receiving the echo signals with respect to the speed of sound in the environment to estimate the distance to the obstacles. In this study the coordinates and characteristics of all the obstacles in the study area are already stored in a GIS database. All of these obstacles were labeled on the map. The ultrasonic sensor designed and constructed in this study has the ability to detect the obstacles in a distance of 2cm to 400cm. The implementation and the results obtained from the interview of a number of blind persons who employed the sensor verified that the designed mobile sensor system for wayfinding was very satisfactory.
Driving a car with custom-designed fuzzy inferencing VLSI chips and boards
NASA Technical Reports Server (NTRS)
Pin, Francois G.; Watanabe, Yutaka
1993-01-01
Vehicle control in a-priori unknown, unpredictable, and dynamic environments requires many calculational and reasoning schemes to operate on the basis of very imprecise, incomplete, or unreliable data. For such systems, in which all the uncertainties can not be engineered away, approximate reasoning may provide an alternative to the complexity and computational requirements of conventional uncertainty analysis and propagation techniques. Two types of computer boards including custom-designed VLSI chips were developed to add a fuzzy inferencing capability to real-time control systems. All inferencing rules on a chip are processed in parallel, allowing execution of the entire rule base in about 30 microseconds, and therefore, making control of 'reflex-type' of motions envisionable. The use of these boards and the approach using superposition of elemental sensor-based behaviors for the development of qualitative reasoning schemes emulating human-like navigation in a-priori unknown environments are first discussed. Then how the human-like navigation scheme implemented on one of the qualitative inferencing boards was installed on a test-bed platform to investigate two control modes for driving a car in a-priori unknown environments on the basis of sparse and imprecise sensor data is described. In the first mode, the car navigates fully autonomously, while in the second mode, the system acts as a driver's aid providing the driver with linguistic (fuzzy) commands to turn left or right and speed up or slow down depending on the obstacles perceived by the sensors. Experiments with both modes of control are described in which the system uses only three acoustic range (sonar) sensor channels to perceive the environment. Simulation results as well as indoors and outdoors experiments are presented and discussed to illustrate the feasibility and robustness of autonomous navigation and/or safety enhancing driver's aid using the new fuzzy inferencing hardware system and some human-like reasoning schemes which may include as little as six elemental behaviors embodied in fourteen qualitative rules.
Stereo Correspondence Using Moment Invariants
NASA Astrophysics Data System (ADS)
Premaratne, Prashan; Safaei, Farzad
Autonomous navigation is seen as a vital tool in harnessing the enormous potential of Unmanned Aerial Vehicles (UAV) and small robotic vehicles for both military and civilian use. Even though, laser based scanning solutions for Simultaneous Location And Mapping (SLAM) is considered as the most reliable for depth estimation, they are not feasible for use in UAV and land-based small vehicles due to their physical size and weight. Stereovision is considered as the best approach for any autonomous navigation solution as stereo rigs are considered to be lightweight and inexpensive. However, stereoscopy which estimates the depth information through pairs of stereo images can still be computationally expensive and unreliable. This is mainly due to some of the algorithms used in successful stereovision solutions require high computational requirements that cannot be met by small robotic vehicles. In our research, we implement a feature-based stereovision solution using moment invariants as a metric to find corresponding regions in image pairs that will reduce the computational complexity and improve the accuracy of the disparity measures that will be significant for the use in UAVs and in small robotic vehicles.
An Improved Multi-Sensor Fusion Navigation Algorithm Based on the Factor Graph
Zeng, Qinghua; Chen, Weina; Liu, Jianye; Wang, Huizhe
2017-01-01
An integrated navigation system coupled with additional sensors can be used in the Micro Unmanned Aerial Vehicle (MUAV) applications because the multi-sensor information is redundant and complementary, which can markedly improve the system accuracy. How to deal with the information gathered from different sensors efficiently is an important problem. The fact that different sensors provide measurements asynchronously may complicate the processing of these measurements. In addition, the output signals of some sensors appear to have a non-linear character. In order to incorporate these measurements and calculate a navigation solution in real time, the multi-sensor fusion algorithm based on factor graph is proposed. The global optimum solution is factorized according to the chain structure of the factor graph, which allows for a more general form of the conditional probability density. It can convert the fusion matter into connecting factors defined by these measurements to the graph without considering the relationship between the sensor update frequency and the fusion period. An experimental MUAV system has been built and some experiments have been performed to prove the effectiveness of the proposed method. PMID:28335570
An Improved Multi-Sensor Fusion Navigation Algorithm Based on the Factor Graph.
Zeng, Qinghua; Chen, Weina; Liu, Jianye; Wang, Huizhe
2017-03-21
An integrated navigation system coupled with additional sensors can be used in the Micro Unmanned Aerial Vehicle (MUAV) applications because the multi-sensor information is redundant and complementary, which can markedly improve the system accuracy. How to deal with the information gathered from different sensors efficiently is an important problem. The fact that different sensors provide measurements asynchronously may complicate the processing of these measurements. In addition, the output signals of some sensors appear to have a non-linear character. In order to incorporate these measurements and calculate a navigation solution in real time, the multi-sensor fusion algorithm based on factor graph is proposed. The global optimum solution is factorized according to the chain structure of the factor graph, which allows for a more general form of the conditional probability density. It can convert the fusion matter into connecting factors defined by these measurements to the graph without considering the relationship between the sensor update frequency and the fusion period. An experimental MUAV system has been built and some experiments have been performed to prove the effectiveness of the proposed method.
Data on the natural ventilation performance of windcatcher with anti-short-circuit device (ASCD).
Nejat, Payam; Calautit, John Kaiser; Majid, Muhd Zaimi Abd; Hughes, Ben Richard; Jomehzadeh, Fatemeh
2016-12-01
This article presents the datasets which were the results of the study explained in the research paper 'Anti-short-circuit device: a new solution for short-circuiting in windcatcher and improvement of natural ventilation performance' (P. Nejat, J.K. Calautit, M.Z. Abd. Majid, B.R. Hughes, F. Jomehzadeh, 2016) [1] which introduces a new technique to reduce or prevent short-circuiting in a two-sided windcatcher and also lowers the indoor CO2 concentration and improve the ventilation distribution. Here, we provide details of the numerical modeling set-up and data collection method to facilitate reproducibility. The datasets includes indoor airflow, ventilation rates and CO2 concentration data at several points in the flow field. The CAD geometry of the windcatcher models are also included.
Autonomous Navigation of Small Uavs Based on Vehicle Dynamic Model
NASA Astrophysics Data System (ADS)
Khaghani, M.; Skaloud, J.
2016-03-01
This paper presents a novel approach to autonomous navigation for small UAVs, in which the vehicle dynamic model (VDM) serves as the main process model within the navigation filter. The proposed method significantly increases the accuracy and reliability of autonomous navigation, especially for small UAVs with low-cost IMUs on-board. This is achieved with no extra sensor added to the conventional INS/GNSS setup. This improvement is of special interest in case of GNSS outages, where inertial coasting drifts very quickly. In the proposed architecture, the solution to VDM equations provides the estimate of position, velocity, and attitude, which is updated within the navigation filter based on available observations, such as IMU data or GNSS measurements. The VDM is also fed with the control input to the UAV, which is available within the control/autopilot system. The filter is capable of estimating wind velocity and dynamic model parameters, in addition to navigation states and IMU sensor errors. Monte Carlo simulations reveal major improvements in navigation accuracy compared to conventional INS/GNSS navigation system during the autonomous phase, when satellite signals are not available due to physical obstruction or electromagnetic interference for example. In case of GNSS outages of a few minutes, position and attitude accuracy experiences improvements of orders of magnitude compared to inertial coasting. It means that during such scenario, the position-velocity-attitude (PVA) determination is sufficiently accurate to navigate the UAV to a home position without any signal that depends on vehicle environment.
Salamone, Francesco; Belussi, Lorenzo; Currò, Cristian; Danza, Ludovico; Ghellere, Matteo; Guazzi, Giulia; Lenzi, Bruno; Megale, Valentino; Meroni, Italo
2018-05-17
Thermal comfort has become a topic issue in building performance assessment as well as energy efficiency. Three methods are mainly recognized for its assessment. Two of them based on standardized methodologies, face the problem by considering the indoor environment in steady-state conditions (PMV and PPD) and users as active subjects whose thermal perception is influenced by outdoor climatic conditions (adaptive approach). The latter method is the starting point to investigate thermal comfort from an overall perspective by considering endogenous variables besides the traditional physical and environmental ones. Following this perspective, the paper describes the results of an in-field investigation of thermal conditions through the use of nearable and wearable solutions, parametric models and machine learning techniques. The aim of the research is the exploration of the reliability of IoT-based solutions combined with advanced algorithms, in order to create a replicable framework for the assessment and improvement of user thermal satisfaction. For this purpose, an experimental test in real offices was carried out involving eight workers. Parametric models are applied for the assessment of thermal comfort; IoT solutions are used to monitor the environmental variables and the users' parameters; the machine learning CART method allows to predict the users' profile and the thermal comfort perception respect to the indoor environment.
Currò, Cristian; Danza, Ludovico; Ghellere, Matteo; Guazzi, Giulia; Lenzi, Bruno; Megale, Valentino; Meroni, Italo
2018-01-01
Thermal comfort has become a topic issue in building performance assessment as well as energy efficiency. Three methods are mainly recognized for its assessment. Two of them based on standardized methodologies, face the problem by considering the indoor environment in steady-state conditions (PMV and PPD) and users as active subjects whose thermal perception is influenced by outdoor climatic conditions (adaptive approach). The latter method is the starting point to investigate thermal comfort from an overall perspective by considering endogenous variables besides the traditional physical and environmental ones. Following this perspective, the paper describes the results of an in-field investigation of thermal conditions through the use of nearable and wearable solutions, parametric models and machine learning techniques. The aim of the research is the exploration of the reliability of IoT-based solutions combined with advanced algorithms, in order to create a replicable framework for the assessment and improvement of user thermal satisfaction. For this purpose, an experimental test in real offices was carried out involving eight workers. Parametric models are applied for the assessment of thermal comfort; IoT solutions are used to monitor the environmental variables and the users’ parameters; the machine learning CART method allows to predict the users’ profile and the thermal comfort perception respect to the indoor environment. PMID:29772818