SLAM algorithm applied to robotics assistance for navigation in unknown environments.

PubMed

Cheein, Fernando A Auat; Lopez, Natalia; Soria, Carlos M; di Sciascio, Fernando A; Pereira, Fernando Lobo; Carelli, Ricardo

2010-02-17

The combination of robotic tools with assistance technology determines a slightly explored area of applications and advantages for disability or elder people in their daily tasks. Autonomous motorized wheelchair navigation inside an environment, behaviour based control of orthopaedic arms or user's preference learning from a friendly interface are some examples of this new field. In this paper, a Simultaneous Localization and Mapping (SLAM) algorithm is implemented to allow the environmental learning by a mobile robot while its navigation is governed by electromyographic signals. The entire system is part autonomous and part user-decision dependent (semi-autonomous). The environmental learning executed by the SLAM algorithm and the low level behaviour-based reactions of the mobile robot are robotic autonomous tasks, whereas the mobile robot navigation inside an environment is commanded by a Muscle-Computer Interface (MCI). In this paper, a sequential Extended Kalman Filter (EKF) feature-based SLAM algorithm is implemented. The features correspond to lines and corners -concave and convex- of the environment. From the SLAM architecture, a global metric map of the environment is derived. The electromyographic signals that command the robot's movements can be adapted to the patient's disabilities. For mobile robot navigation purposes, five commands were obtained from the MCI: turn to the left, turn to the right, stop, start and exit. A kinematic controller to control the mobile robot was implemented. A low level behavior strategy was also implemented to avoid robot's collisions with the environment and moving agents. The entire system was tested in a population of seven volunteers: three elder, two below-elbow amputees and two young normally limbed patients. The experiments were performed within a closed low dynamic environment. Subjects took an average time of 35 minutes to navigate the environment and to learn how to use the MCI. The SLAM results have shown a consistent reconstruction of the environment. The obtained map was stored inside the Muscle-Computer Interface. The integration of a highly demanding processing algorithm (SLAM) with a MCI and the communication between both in real time have shown to be consistent and successful. The metric map generated by the mobile robot would allow possible future autonomous navigation without direct control of the user, whose function could be relegated to choose robot destinations. Also, the mobile robot shares the same kinematic model of a motorized wheelchair. This advantage can be exploited for wheelchair autonomous navigation.

Coordinating sensing and local navigation

NASA Technical Reports Server (NTRS)

Slack, Marc G.

1991-01-01

Based on Navigation Templates (or NaTs), this work presents a new paradigm for local navigation which addresses the noisy and uncertain nature of sensor data. Rather than creating a new navigation plan each time the robot's perception of the world changes, the technique incorporates perceptual changes directly into the existing navigation plan. In this way, the robot's navigation plan is quickly and continuously modified, resulting in actions that remain coordinated with its changing perception of the world.

Robot navigation research at CESAR (Center for Engineering Systems Advanced Research)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barnett, D.L.; de Saussure, G.; Pin, F.G.

1989-01-01

A considerable amount of work has been reported on the problem of robot navigation in known static terrains. Algorithms have been proposed and implemented to search for an optimum path to the goal, taking into account the finite size and shape of the robot. Not as much work has been reported on robot navigation in unknown, unstructured, or dynamic environments. A robot navigating in an unknown environment must explore with its sensors, construct an abstract representation of its global environment to plan a path to the goal, and update or revise its plan based on accumulated data obtained and processedmore » in real-time. The core of the navigation program for the CESAR robots is a production system developed on the expert-system-shell CLIPS which runs on an NCUBE hypercube on board the robot. The production system can call on C-compiled navigation procedures. The production rules can read the sensor data and address the robot's effectors. This architecture was found efficient and flexible for the development and testing of the navigation algorithms; however, in order to process intelligently unexpected emergencies, it was found necessary to be able to control the production system through externally generated asynchronous data. This led to the design of a new asynchronous production system, APS, which is now being developed on the robot. This paper will review some of the navigation algorithms developed and tested at CESAR and will discuss the need for the new APS and how it is being integrated into the robot architecture. 18 refs., 3 figs., 1 tab.« less

Situationally driven local navigation for mobile robots. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Slack, Marc Glenn

1990-01-01

For mobile robots to autonomously accommodate dynamically changing navigation tasks in a goal-directed fashion, they must employ navigation plans. Any such plan must provide for the robot's immediate and continuous need for guidance while remaining highly flexible in order to avoid costly computation each time the robot's perception of the world changes. Due to the world's uncertainties, creation and maintenance of navigation plans cannot involve arbitrarily complex processes, as the robot's perception of the world will be in constant flux, requiring modifications to be made quickly if they are to be of any use. This work introduces navigation templates (NaT's) which are building blocks for the construction and maintenance of rough navigation plans which capture the relationship that objects in the world have to the current navigation task. By encoding only the critical relationship between the objects in the world and the navigation task, a NaT-based navigation plan is highly flexible; allowing new constraints to be quickly incorporated into the plan and existing constraints to be updated or deleted from the plan. To satisfy the robot's need for immediate local guidance, the NaT's forming the current navigation plan are passed to a transformation function. The transformation function analyzes the plan with respect to the robot's current location to quickly determine (a few times a second) the locally preferred direction of travel. This dissertation presents NaT's and the transformation function as well as the needed support systems to demonstrate the usefulness of the technique for controlling the actions of a mobile robot operating in an uncertain world.

Structured Kernel Subspace Learning for Autonomous Robot Navigation.

PubMed

Kim, Eunwoo; Choi, Sungjoon; Oh, Songhwai

2018-02-14

This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods.

Neural Network-Based Landmark Recognition and Navigation with IAMRs. Understanding the Principles of Thought and Behavior.

ERIC Educational Resources Information Center

Doty, Keith L.

1999-01-01

Research on neural networks and hippocampal function demonstrating how mammals construct mental maps and develop navigation strategies is being used to create Intelligent Autonomous Mobile Robots (IAMRs). Such robots are able to recognize landmarks and navigate without "vision." (SK)

Virtual local target method for avoiding local minimum in potential field based robot navigation.

PubMed

Zou, Xi-Yong; Zhu, Jing

2003-01-01

A novel robot navigation algorithm with global path generation capability is presented. Local minimum is a most intractable but is an encountered frequently problem in potential field based robot navigation. Through appointing appropriately some virtual local targets on the journey, it can be solved effectively. The key concept employed in this algorithm are the rules that govern when and how to appoint these virtual local targets. When the robot finds itself in danger of local minimum, a virtual local target is appointed to replace the global goal temporarily according to the rules. After the virtual target is reached, the robot continues on its journey by heading towards the global goal. The algorithm prevents the robot from running into local minima anymore. Simulation results showed that it is very effective in complex obstacle environments.

Memristive device based learning for navigation in robots.

PubMed

Sarim, Mohammad; Kumar, Manish; Jha, Rashmi; Minai, Ali A

2017-11-08

Biomimetic robots have gained attention recently for various applications ranging from resource hunting to search and rescue operations during disasters. Biological species are known to intuitively learn from the environment, gather and process data, and make appropriate decisions. Such sophisticated computing capabilities in robots are difficult to achieve, especially if done in real-time with ultra-low energy consumption. Here, we present a novel memristive device based learning architecture for robots. Two terminal memristive devices with resistive switching of oxide layer are modeled in a crossbar array to develop a neuromorphic platform that can impart active real-time learning capabilities in a robot. This approach is validated by navigating a robot vehicle in an unknown environment with randomly placed obstacles. Further, the proposed scheme is compared with reinforcement learning based algorithms using local and global knowledge of the environment. The simulation as well as experimental results corroborate the validity and potential of the proposed learning scheme for robots. The results also show that our learning scheme approaches an optimal solution for some environment layouts in robot navigation.

Robot navigation research using the HERMIES mobile robot

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barnett, D.L.

1989-01-01

In recent years robot navigation has attracted much attention from researchers around the world. Not only are theoretical studies being simulated on sophisticated computers, but many mobile robots are now used as test vehicles for these theoretical studies. Various algorithms have been perfected for navigation in a known static environment; but navigation in an unknown and dynamic environment poses a much more challenging problem for researchers. Many different methodologies have been developed for autonomous robot navigation, but each methodology is usually restricted to a particular type of environment. One important research focus of the Center for Engineering Systems Advanced researchmore » (CESAR) at Oak Ridge National Laboratory, is autonomous navigation in unknown and dynamic environments using the series of HERMIES mobile robots. The research uses an expert system for high-level planning interfaced with C-coded routines for implementing the plans, and for quick processing of data requested by the expert system. In using this approach, the navigation is not restricted to one methodology since the expert system can activate a rule module for the methodology best suited for the current situation. Rule modules can be added the rule base as they are developed and tested. Modules are being developed or enhanced for navigating from a map, searching for a target, exploring, artificial potential-field navigation, navigation using edge-detection, etc. This paper will report on the various rule modules and methods of navigation in use, or under development at CESAR, using the HERMIES-IIB robot as a testbed. 13 refs., 5 figs., 1 tab.« less

SLAM algorithm applied to robotics assistance for navigation in unknown environments

PubMed Central

2010-01-01

Background The combination of robotic tools with assistance technology determines a slightly explored area of applications and advantages for disability or elder people in their daily tasks. Autonomous motorized wheelchair navigation inside an environment, behaviour based control of orthopaedic arms or user's preference learning from a friendly interface are some examples of this new field. In this paper, a Simultaneous Localization and Mapping (SLAM) algorithm is implemented to allow the environmental learning by a mobile robot while its navigation is governed by electromyographic signals. The entire system is part autonomous and part user-decision dependent (semi-autonomous). The environmental learning executed by the SLAM algorithm and the low level behaviour-based reactions of the mobile robot are robotic autonomous tasks, whereas the mobile robot navigation inside an environment is commanded by a Muscle-Computer Interface (MCI). Methods In this paper, a sequential Extended Kalman Filter (EKF) feature-based SLAM algorithm is implemented. The features correspond to lines and corners -concave and convex- of the environment. From the SLAM architecture, a global metric map of the environment is derived. The electromyographic signals that command the robot's movements can be adapted to the patient's disabilities. For mobile robot navigation purposes, five commands were obtained from the MCI: turn to the left, turn to the right, stop, start and exit. A kinematic controller to control the mobile robot was implemented. A low level behavior strategy was also implemented to avoid robot's collisions with the environment and moving agents. Results The entire system was tested in a population of seven volunteers: three elder, two below-elbow amputees and two young normally limbed patients. The experiments were performed within a closed low dynamic environment. Subjects took an average time of 35 minutes to navigate the environment and to learn how to use the MCI. The SLAM results have shown a consistent reconstruction of the environment. The obtained map was stored inside the Muscle-Computer Interface. Conclusions The integration of a highly demanding processing algorithm (SLAM) with a MCI and the communication between both in real time have shown to be consistent and successful. The metric map generated by the mobile robot would allow possible future autonomous navigation without direct control of the user, whose function could be relegated to choose robot destinations. Also, the mobile robot shares the same kinematic model of a motorized wheelchair. This advantage can be exploited for wheelchair autonomous navigation. PMID:20163735

Neural Network Based Sensory Fusion for Landmark Detection

NASA Technical Reports Server (NTRS)

Kumbla, Kishan -K.; Akbarzadeh, Mohammad R.

1997-01-01

NASA is planning to send numerous unmanned planetary missions to explore the space. This requires autonomous robotic vehicles which can navigate in an unstructured, unknown, and uncertain environment. Landmark based navigation is a new area of research which differs from the traditional goal-oriented navigation, where a mobile robot starts from an initial point and reaches a destination in accordance with a pre-planned path. The landmark based navigation has the advantage of allowing the robot to find its way without communication with the mission control station and without exact knowledge of its coordinates. Current algorithms based on landmark navigation however pose several constraints. First, they require large memories to store the images. Second, the task of comparing the images using traditional methods is computationally intensive and consequently real-time implementation is difficult. The method proposed here consists of three stages, First stage utilizes a heuristic-based algorithm to identify significant objects. The second stage utilizes a neural network (NN) to efficiently classify images of the identified objects. The third stage combines distance information with the classification results of neural networks for efficient and intelligent navigation.

An Outdoor Navigation Platform with a 3D Scanner and Gyro-assisted Odometry

NASA Astrophysics Data System (ADS)

Yoshida, Tomoaki; Irie, Kiyoshi; Koyanagi, Eiji; Tomono, Masahiro

This paper proposes a light-weight navigation platform that consists of gyro-assisted odometry, a 3D laser scanner and map-based localization for human-scale robots. The gyro-assisted odometry provides highly accurate positioning only by dead-reckoning. The 3D laser scanner has a wide field of view and uniform measuring-point distribution. The map-based localization is robust and computationally inexpensive by utilizing a particle filter on a 2D grid map generated by projecting 3D points on to the ground. The system uses small and low-cost sensors, and can be applied to a variety of mobile robots in human-scale environments. Outdoor navigation experiments were conducted at the Tsukuba Challenge held in 2009 and 2010, which is an open proving ground for human-scale robots. Our robot successfully navigated the assigned 1-km courses in a fully autonomous mode multiple times.

Olfaction and Hearing Based Mobile Robot Navigation for Odor/Sound Source Search

PubMed Central

Song, Kai; Liu, Qi; Wang, Qi

2011-01-01

Bionic technology provides a new elicitation for mobile robot navigation since it explores the way to imitate biological senses. In the present study, the challenging problem was how to fuse different biological senses and guide distributed robots to cooperate with each other for target searching. This paper integrates smell, hearing and touch to design an odor/sound tracking multi-robot system. The olfactory robot tracks the chemical odor plume step by step through information fusion from gas sensors and airflow sensors, while two hearing robots localize the sound source by time delay estimation (TDE) and the geometrical position of microphone array. Furthermore, this paper presents a heading direction based mobile robot navigation algorithm, by which the robot can automatically and stably adjust its velocity and direction according to the deviation between the current heading direction measured by magnetoresistive sensor and the expected heading direction acquired through the odor/sound localization strategies. Simultaneously, one robot can communicate with the other robots via a wireless sensor network (WSN). Experimental results show that the olfactory robot can pinpoint the odor source within the distance of 2 m, while two hearing robots can quickly localize and track the olfactory robot in 2 min. The devised multi-robot system can achieve target search with a considerable success ratio and high stability. PMID:22319401

Convolutional Neural Network-Based Robot Navigation Using Uncalibrated Spherical Images †

PubMed Central

Ran, Lingyan; Zhang, Yanning; Zhang, Qilin; Yang, Tao

2017-01-01

Vision-based mobile robot navigation is a vibrant area of research with numerous algorithms having been developed, the vast majority of which either belong to the scene-oriented simultaneous localization and mapping (SLAM) or fall into the category of robot-oriented lane-detection/trajectory tracking. These methods suffer from high computational cost and require stringent labelling and calibration efforts. To address these challenges, this paper proposes a lightweight robot navigation framework based purely on uncalibrated spherical images. To simplify the orientation estimation, path prediction and improve computational efficiency, the navigation problem is decomposed into a series of classification tasks. To mitigate the adverse effects of insufficient negative samples in the “navigation via classification” task, we introduce the spherical camera for scene capturing, which enables 360° fisheye panorama as training samples and generation of sufficient positive and negative heading directions. The classification is implemented as an end-to-end Convolutional Neural Network (CNN), trained on our proposed Spherical-Navi image dataset, whose category labels can be efficiently collected. This CNN is capable of predicting potential path directions with high confidence levels based on a single, uncalibrated spherical image. Experimental results demonstrate that the proposed framework outperforms competing ones in realistic applications. PMID:28604624

Convolutional Neural Network-Based Robot Navigation Using Uncalibrated Spherical Images.

PubMed

Ran, Lingyan; Zhang, Yanning; Zhang, Qilin; Yang, Tao

2017-06-12

Vision-based mobile robot navigation is a vibrant area of research with numerous algorithms having been developed, the vast majority of which either belong to the scene-oriented simultaneous localization and mapping (SLAM) or fall into the category of robot-oriented lane-detection/trajectory tracking. These methods suffer from high computational cost and require stringent labelling and calibration efforts. To address these challenges, this paper proposes a lightweight robot navigation framework based purely on uncalibrated spherical images. To simplify the orientation estimation, path prediction and improve computational efficiency, the navigation problem is decomposed into a series of classification tasks. To mitigate the adverse effects of insufficient negative samples in the "navigation via classification" task, we introduce the spherical camera for scene capturing, which enables 360° fisheye panorama as training samples and generation of sufficient positive and negative heading directions. The classification is implemented as an end-to-end Convolutional Neural Network (CNN), trained on our proposed Spherical-Navi image dataset, whose category labels can be efficiently collected. This CNN is capable of predicting potential path directions with high confidence levels based on a single, uncalibrated spherical image. Experimental results demonstrate that the proposed framework outperforms competing ones in realistic applications.

Development of a Novel Locomotion Algorithm for Snake Robot

NASA Astrophysics Data System (ADS)

Khan, Raisuddin; Masum Billah, Md; Watanabe, Mitsuru; Shafie, A. A.

2013-12-01

A novel algorithm for snake robot locomotion is developed and analyzed in this paper. Serpentine is one of the renowned locomotion for snake robot in disaster recovery mission to overcome narrow space navigation. Several locomotion for snake navigation, such as concertina or rectilinear may be suitable for narrow spaces, but is highly inefficient if the same type of locomotion is used even in open spaces resulting friction reduction which make difficulties for snake movement. A novel locomotion algorithm has been proposed based on the modification of the multi-link snake robot, the modifications include alterations to the snake segments as well elements that mimic scales on the underside of the snake body. Snake robot can be able to navigate in the narrow space using this developed locomotion algorithm. The developed algorithm surmount the others locomotion limitation in narrow space navigation.

Neurosurgical robotic arm drilling navigation system.

PubMed

Lin, Chung-Chih; Lin, Hsin-Cheng; Lee, Wen-Yo; Lee, Shih-Tseng; Wu, Chieh-Tsai

2017-09-01

The aim of this work was to develop a neurosurgical robotic arm drilling navigation system that provides assistance throughout the complete bone drilling process. The system comprised neurosurgical robotic arm navigation combining robotic and surgical navigation, 3D medical imaging based surgical planning that could identify lesion location and plan the surgical path on 3D images, and automatic bone drilling control that would stop drilling when the bone was to be drilled-through. Three kinds of experiment were designed. The average positioning error deduced from 3D images of the robotic arm was 0.502 ± 0.069 mm. The correlation between automatically and manually planned paths was 0.975. The average distance error between automatically planned paths and risky zones was 0.279 ± 0.401 mm. The drilling auto-stopping algorithm had 0.00% unstopped cases (26.32% in control group 1) and 70.53% non-drilled-through cases (8.42% and 4.21% in control groups 1 and 2). The system may be useful for neurosurgical robotic arm drilling navigation. Copyright © 2016 John Wiley & Sons, Ltd.

Volunteers Oriented Interface Design for the Remote Navigation of Rescue Robots at Large-Scale Disaster Sites

NASA Astrophysics Data System (ADS)

Yang, Zhixiao; Ito, Kazuyuki; Saijo, Kazuhiko; Hirotsune, Kazuyuki; Gofuku, Akio; Matsuno, Fumitoshi

This paper aims at constructing an efficient interface being similar to those widely used in human daily life, to fulfill the need of many volunteer rescuers operating rescue robots at large-scale disaster sites. The developed system includes a force feedback steering wheel interface and an artificial neural network (ANN) based mouse-screen interface. The former consists of a force feedback steering control and a six monitors’ wall. It provides a manual operation like driving cars to navigate a rescue robot. The latter consists of a mouse and a camera’s view displayed in a monitor. It provides a semi-autonomous operation by mouse clicking to navigate a rescue robot. Results of experiments show that a novice volunteer can skillfully navigate a tank rescue robot through both interfaces after 20 to 30 minutes of learning their operation respectively. The steering wheel interface has high navigating speed in open areas, without restriction of terrains and surface conditions of a disaster site. The mouse-screen interface is good at exact navigation in complex structures, while bringing little tension to operators. The two interfaces are designed to switch into each other at any time to provide a combined efficient navigation method.

Preliminary study on magnetic tracking-based planar shape sensing and navigation for flexible surgical robots in transoral surgery: methods and phantom experiments.

PubMed

Song, Shuang; Zhang, Changchun; Liu, Li; Meng, Max Q-H

2018-02-01

Flexible surgical robot can work in confined and complex environments, which makes it a good option for minimally invasive surgery. In order to utilize flexible manipulators in complicated and constrained surgical environments, it is of great significance to monitor the position and shape of the curvilinear manipulator in real time during the procedures. In this paper, we propose a magnetic tracking-based planar shape sensing and navigation system for flexible surgical robots in the transoral surgery. The system can provide the real-time tip position and shape information of the robot during the operation. We use wire-driven flexible robot to serve as the manipulator. It has three degrees of freedom. A permanent magnet is mounted at the distal end of the robot. Its magnetic field can be sensed with a magnetic sensor array. Therefore, position and orientation of the tip can be estimated utilizing a tracking method. A shape sensing algorithm is then carried out to estimate the real-time shape based on the tip pose. With the tip pose and shape display in the 3D reconstructed CT model, navigation can be achieved. Using the proposed system, we carried out planar navigation experiments on a skull phantom to touch three different target positions under the navigation of the skull display interface. During the experiments, the real-time shape has been well monitored and distance errors between the robot tip and the targets in the skull have been recorded. The mean navigation error is [Formula: see text] mm, while the maximum error is 3.2 mm. The proposed method provides the advantages that no sensors are needed to mount on the robot and no line-of-sight problem. Experimental results verified the feasibility of the proposed method.

Fuzzy Logic Based Control for Autonomous Mobile Robot Navigation

PubMed Central

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

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.

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.

Evolutionary programming-based univector field navigation method for past mobile robots.

PubMed

Kim, Y J; Kim, J H; Kwon, D S

2001-01-01

Most of navigation techniques with obstacle avoidance do not consider the robot orientation at the target position. These techniques deal with the robot position only and are independent of its orientation and velocity. To solve these problems this paper proposes a novel univector field method for fast mobile robot navigation which introduces a normalized two dimensional vector field. The method provides fast moving robots with the desired posture at the target position and obstacle avoidance. To obtain the sub-optimal vector field, a function approximator is used and trained by evolutionary programming. Two kinds of vector fields are trained, one for the final posture acquisition and the other for obstacle avoidance. Computer simulations and real experiments are carried out for a fast moving mobile robot to demonstrate the effectiveness of the proposed scheme.

BatSLAM: Simultaneous localization and mapping using biomimetic sonar.

PubMed

Steckel, Jan; Peremans, Herbert

2013-01-01

We propose to combine a biomimetic navigation model which solves a simultaneous localization and mapping task with a biomimetic sonar mounted on a mobile robot to address two related questions. First, can robotic sonar sensing lead to intelligent interactions with complex environments? Second, can we model sonar based spatial orientation and the construction of spatial maps by bats? To address these questions we adapt the mapping module of RatSLAM, a previously published navigation system based on computational models of the rodent hippocampus. We analyze the performance of the proposed robotic implementation operating in the real world. We conclude that the biomimetic navigation model operating on the information from the biomimetic sonar allows an autonomous agent to map unmodified (office) environments efficiently and consistently. Furthermore, these results also show that successful navigation does not require the readings of the biomimetic sonar to be interpreted in terms of individual objects/landmarks in the environment. We argue that the system has applications in robotics as well as in the field of biology as a simple, first order, model for sonar based spatial orientation and map building.

BatSLAM: Simultaneous Localization and Mapping Using Biomimetic Sonar

PubMed Central

Steckel, Jan; Peremans, Herbert

2013-01-01

We propose to combine a biomimetic navigation model which solves a simultaneous localization and mapping task with a biomimetic sonar mounted on a mobile robot to address two related questions. First, can robotic sonar sensing lead to intelligent interactions with complex environments? Second, can we model sonar based spatial orientation and the construction of spatial maps by bats? To address these questions we adapt the mapping module of RatSLAM, a previously published navigation system based on computational models of the rodent hippocampus. We analyze the performance of the proposed robotic implementation operating in the real world. We conclude that the biomimetic navigation model operating on the information from the biomimetic sonar allows an autonomous agent to map unmodified (office) environments efficiently and consistently. Furthermore, these results also show that successful navigation does not require the readings of the biomimetic sonar to be interpreted in terms of individual objects/landmarks in the environment. We argue that the system has applications in robotics as well as in the field of biology as a simple, first order, model for sonar based spatial orientation and map building. PMID:23365647

Modelling and Experiment Based on a Navigation System for a Cranio-Maxillofacial Surgical Robot.

PubMed

Duan, Xingguang; Gao, Liang; Wang, Yonggui; Li, Jianxi; Li, Haoyuan; Guo, Yanjun

2018-01-01

In view of the characteristics of high risk and high accuracy in cranio-maxillofacial surgery, we present a novel surgical robot system that can be used in a variety of surgeries. The surgical robot system can assist surgeons in completing biopsy of skull base lesions, radiofrequency thermocoagulation of the trigeminal ganglion, and radioactive particle implantation of skull base malignant tumors. This paper focuses on modelling and experimental analyses of the robot system based on navigation technology. Firstly, the transformation relationship between the subsystems is realized based on the quaternion and the iterative closest point registration algorithm. The hand-eye coordination model based on optical navigation is established to control the end effector of the robot moving to the target position along the planning path. The closed-loop control method, "kinematics + optics" hybrid motion control method, is presented to improve the positioning accuracy of the system. Secondly, the accuracy of the system model was tested by model experiments. And the feasibility of the closed-loop control method was verified by comparing the positioning accuracy before and after the application of the method. Finally, the skull model experiments were performed to evaluate the function of the surgical robot system. The results validate its feasibility and are consistent with the preoperative surgical planning.

Modelling and Experiment Based on a Navigation System for a Cranio-Maxillofacial Surgical Robot

PubMed Central

Duan, Xingguang; Gao, Liang; Li, Jianxi; Li, Haoyuan; Guo, Yanjun

2018-01-01

In view of the characteristics of high risk and high accuracy in cranio-maxillofacial surgery, we present a novel surgical robot system that can be used in a variety of surgeries. The surgical robot system can assist surgeons in completing biopsy of skull base lesions, radiofrequency thermocoagulation of the trigeminal ganglion, and radioactive particle implantation of skull base malignant tumors. This paper focuses on modelling and experimental analyses of the robot system based on navigation technology. Firstly, the transformation relationship between the subsystems is realized based on the quaternion and the iterative closest point registration algorithm. The hand-eye coordination model based on optical navigation is established to control the end effector of the robot moving to the target position along the planning path. The closed-loop control method, “kinematics + optics” hybrid motion control method, is presented to improve the positioning accuracy of the system. Secondly, the accuracy of the system model was tested by model experiments. And the feasibility of the closed-loop control method was verified by comparing the positioning accuracy before and after the application of the method. Finally, the skull model experiments were performed to evaluate the function of the surgical robot system. The results validate its feasibility and are consistent with the preoperative surgical planning. PMID:29599948

Two modular neuro-fuzzy system for mobile robot navigation

NASA Astrophysics Data System (ADS)

Bobyr, M. V.; Titov, V. S.; Kulabukhov, S. A.; Syryamkin, V. I.

2018-05-01

The article considers the fuzzy model for navigation of a mobile robot operating in two modes. In the first mode the mobile robot moves along a line. In the second mode, the mobile robot looks for an target in unknown space. Structural and schematic circuit of four-wheels mobile robot are presented in the article. The article describes the movement of a mobile robot based on two modular neuro-fuzzy system. The algorithm of neuro-fuzzy inference used in two modular control system for movement of a mobile robot is given in the article. The experimental model of the mobile robot and the simulation of the neuro-fuzzy algorithm used for its control are presented in the article.

A Behavior-Based Strategy for Single and Multi-Robot Autonomous Exploration

PubMed Central

Cepeda, Jesus S.; Chaimowicz, Luiz; Soto, Rogelio; Gordillo, José L.; Alanís-Reyes, Edén A.; Carrillo-Arce, Luis C.

2012-01-01

In this paper, we consider the problem of autonomous exploration of unknown environments with single and multiple robots. This is a challenging task, with several potential applications. We propose a simple yet effective approach that combines a behavior-based navigation with an efficient data structure to store previously visited regions. This allows robots to safely navigate, disperse and efficiently explore the environment. A series of experiments performed using a realistic robotic simulator and a real testbed scenario demonstrate that our technique effectively distributes the robots over the environment and allows them to quickly accomplish their mission in large open spaces, narrow cluttered environments, dead-end corridors, as well as rooms with minimum exits.

Computer-assisted hip and knee arthroplasty. Navigation and active robotic systems: an evidence-based analysis.

PubMed

2004-01-01

The Medical Advisory Secretariat undertook a review of the evidence on the effectiveness and cost-effectiveness of computer assisted hip and knee arthroplasty. The two computer assisted arthroplasty systems that are the topics of this review are (1) navigation and (2) robotic-assisted hip and knee arthroplasty. Computer-assisted arthroplasty consists of navigation and robotic systems. Surgical navigation is a visualization system that provides positional information about surgical tools or implants relative to a target bone on a computer display. Most of the navigation-assisted arthroplasty devices that are the subject of this review are licensed by Health Canada. Robotic systems are active robots that mill bone according to information from a computer-assisted navigation system. The robotic-assisted arthroplasty devices that are the subject of this review are not currently licensed by Health Canada. The Cochrane and International Network of Agencies for Health Technology Assessment databases did not identify any health technology assessments on navigation or robotic-assisted hip or knee arthroplasty. The MEDLINE and EMBASE databases were searched for articles published between January 1, 1996 and November 30, 2003. This search produced 367 studies, of which 9 met the inclusion criteria. NAVIGATION-ASSISTED ARTHROPLASTY: Five studies were identified that examined navigation-assisted arthroplasty.A Level 1 evidence study from Germany found a statistically significant difference in alignment and angular deviation between navigation-assisted and free-hand total knee arthroplasty in favour of navigation-assisted surgery. However, the endpoints in this study were short-term. To date, the long-term effects (need for revision, implant longevity, pain, functional performance) are unknown.(1)A Level 2 evidence short-term study found that navigation-assisted total knee arthroplasty was significantly better than a non-navigated procedure for one of five postoperative measured angles.(2)A Level 2 evidence short-term study found no statistically significant difference in the variation of the abduction angle between navigation-assisted and conventional total hip arthroplasty.(3)Level 3 evidence observational studies of navigation-assisted total knee arthroplasty and unicompartmental knee arthroplasty have been conducted. Two studies reported that "the follow-up of the navigated prostheses is currently too short to know if clinical outcome or survival rates are improved. Longer follow-up is required to determine the respective advantages and disadvantages of both techniques."(4;5) ROBOTIC-ASSISTED ARTHROPLASTY: Four studies were identified that examined robotic-assisted arthroplasty.A Level 1 evidence study revealed that there was no statistically significant difference between functional hip scores at 24 months post implantation between patients who underwent robotic-assisted primary hip arthroplasty and those that were treated with manual implantation.(6)Robotic-assisted arthroplasty had advantages in terms of preoperative planning and the accuracy of the intraoperative procedure.(6)Patients who underwent robotic-assisted hip arthroplasty had a higher dislocation rate and more revisions.(6)Robotic-assisted arthroplasty may prove effective with certain prostheses (e.g., anatomic) because their use may result in less muscle detachment.(6)An observational study (Level 3 evidence) found that the incidence of severe embolic events during hip relocation was lower with robotic arthroplasty than with manual surgery.(7)An observational study (Level 3 evidence) found that there was no significant difference in gait analyses of patients who underwent robotic-assisted total hip arthroplasty using robotic surgery compared to patients who were treated with conventional cementless total hip arthroplasty.(8)An observational study (Level 3 evidence) compared outcomes of total knee arthroplasty between patients undergoing robotic surgery and patients who were historical controls. Brief, qualitative results suggested that there was much broader variation of angles after manual total knee arthroplasty compared to the robotic technique and that there was no difference in knee functional scores or implant position at the 3 and 6 month follow-up.(9).

Composite Configuration Interventional Therapy Robot for the Microwave Ablation of Liver Tumors

NASA Astrophysics Data System (ADS)

Cao, Ying-Yu; Xue, Long; Qi, Bo-Jin; Jiang, Li-Pei; Deng, Shuang-Cheng; Liang, Ping; Liu, Jia

2017-11-01

The existing interventional therapy robots for the microwave ablation of liver tumors have a poor clinical applicability with a large volume, low positioning speed and complex automatic navigation control. To solve above problems, a composite configuration interventional therapy robot with passive and active joints is developed. The design of composite configuration reduces the size of the robot under the premise of a wide range of movement, and the robot with composite configuration can realizes rapid positioning with operation safety. The cumulative error of positioning is eliminated and the control complexity is reduced by decoupling active parts. The navigation algorithms for the robot are proposed based on solution of the inverse kinematics and geometric analysis. A simulation clinical test method is designed for the robot, and the functions of the robot and the navigation algorithms are verified by the test method. The mean error of navigation is 1.488 mm and the maximum error is 2.056 mm, and the positioning time for the ablation needle is in 10 s. The experimental results show that the designed robot can meet the clinical requirements for the microwave ablation of liver tumors. The composite configuration is proposed in development of the interventional therapy robot for the microwave ablation of liver tumors, which provides a new idea for the structural design of medical robots.

On learning navigation behaviors for small mobile robots with reservoir computing architectures.

PubMed

Antonelo, Eric Aislan; Schrauwen, Benjamin

2015-04-01

This paper proposes a general reservoir computing (RC) learning framework that can be used to learn navigation behaviors for mobile robots in simple and complex unknown partially observable environments. RC provides an efficient way to train recurrent neural networks by letting the recurrent part of the network (called reservoir) be fixed while only a linear readout output layer is trained. The proposed RC framework builds upon the notion of navigation attractor or behavior that can be embedded in the high-dimensional space of the reservoir after learning. The learning of multiple behaviors is possible because the dynamic robot behavior, consisting of a sensory-motor sequence, can be linearly discriminated in the high-dimensional nonlinear space of the dynamic reservoir. Three learning approaches for navigation behaviors are shown in this paper. The first approach learns multiple behaviors based on the examples of navigation behaviors generated by a supervisor, while the second approach learns goal-directed navigation behaviors based only on rewards. The third approach learns complex goal-directed behaviors, in a supervised way, using a hierarchical architecture whose internal predictions of contextual switches guide the sequence of basic navigation behaviors toward the goal.

Vision-based mapping with cooperative robots

NASA Astrophysics Data System (ADS)

Little, James J.; Jennings, Cullen; Murray, Don

1998-10-01

Two stereo-vision-based mobile robots navigate and autonomously explore their environment safely while building occupancy grid maps of the environment. The robots maintain position estimates within a global coordinate frame using landmark recognition. This allows them to build a common map by sharing position information and stereo data. Stereo vision processing and map updates are done at 3 Hz and the robots move at speeds of 200 cm/s. Cooperative mapping is achieved through autonomous exploration of unstructured and dynamic environments. The map is constructed conservatively, so as to be useful for collision-free path planning. Each robot maintains a separate copy of a shared map, and then posts updates to the common map when it returns to observe a landmark at home base. Issues include synchronization, mutual localization, navigation, exploration, registration of maps, merging repeated views (fusion), centralized vs decentralized maps.

[Force-based local navigation in robot-assisted implantation bed anlage in the lateral skull base. An experimental study].

PubMed

Plinkert, P K; Federspil, P A; Plinkert, B; Henrich, D

2002-03-01

Excellent precision, miss of retiring, reproducibility are main characteristics of robots in the operating theatre. Because of these facts their use for surgery in the lateral scull base is of great interest. In recent experiments we determined process parameters for robot assisted reaming of a cochlea implant bed and for a mastoidectomy. These results suggested that optimizing parameters for thrilling with the robot is needed. Therefore we implemented a suitable reaming curve from the geometrical data of the implant and a force controlled process control for robot assisted reaming at the lateral scull base. Experiments were performed with an industrial robot on animal and human scull base specimen. Because of online force detection and feedback of sensory data the reaming with the robot was controlled. With increasing force values above a defined limit feed rates were automatically regulated. Furthermore we were able to detect contact of the thrill to dura mater by analyzing the force values. With the new computer program the desired implant bed was exactly prepared. Our examinations showed a successful reaming of an implant bed in the lateral scull base with a robot. Because of a force controlled reaming process locale navigation is possible and enables careful thrilling with a robot.

Designing speech-based interfaces for telepresence robots for people with disabilities.

PubMed

Tsui, Katherine M; Flynn, Kelsey; McHugh, Amelia; Yanco, Holly A; Kontak, David

2013-06-01

People with cognitive and/or motor impairments may benefit from using telepresence robots to engage in social activities. To date, these robots, their user interfaces, and their navigation behaviors have not been designed for operation by people with disabilities. We conducted an experiment in which participants (n=12) used a telepresence robot in a scavenger hunt task to determine how they would use speech to command the robot. Based upon the results, we present design guidelines for speech-based interfaces for telepresence robots.

Ground Simulation of an Autonomous Satellite Rendezvous and Tracking System Using Dual Robotic Systems

NASA Technical Reports Server (NTRS)

Trube, Matthew J.; Hyslop, Andrew M.; Carignan, Craig R.; Easley, Joseph W.

2012-01-01

A hardware-in-the-loop ground system was developed for simulating a robotic servicer spacecraft tracking a target satellite at short range. A relative navigation sensor package "Argon" is mounted on the end-effector of a Fanuc 430 manipulator, which functions as the base platform of the robotic spacecraft servicer. Machine vision algorithms estimate the pose of the target spacecraft, mounted on a Rotopod R-2000 platform, relay the solution to a simulation of the servicer spacecraft running in "Freespace", which performs guidance, navigation and control functions, integrates dynamics, and issues motion commands to a Fanuc platform controller so that it tracks the simulated servicer spacecraft. Results will be reviewed for several satellite motion scenarios at different ranges. Key words: robotics, satellite, servicing, guidance, navigation, tracking, control, docking.

A biologically inspired meta-control navigation system for the Psikharpax rat robot.

PubMed

Caluwaerts, K; Staffa, M; N'Guyen, S; Grand, C; Dollé, L; Favre-Félix, A; Girard, B; Khamassi, M

2012-06-01

A biologically inspired navigation system for the mobile rat-like robot named Psikharpax is presented, allowing for self-localization and autonomous navigation in an initially unknown environment. The ability of parts of the model (e.g. the strategy selection mechanism) to reproduce rat behavioral data in various maze tasks has been validated before in simulations. But the capacity of the model to work on a real robot platform had not been tested. This paper presents our work on the implementation on the Psikharpax robot of two independent navigation strategies (a place-based planning strategy and a cue-guided taxon strategy) and a strategy selection meta-controller. We show how our robot can memorize which was the optimal strategy in each situation, by means of a reinforcement learning algorithm. Moreover, a context detector enables the controller to quickly adapt to changes in the environment-recognized as new contexts-and to restore previously acquired strategy preferences when a previously experienced context is recognized. This produces adaptivity closer to rat behavioral performance and constitutes a computational proposition of the role of the rat prefrontal cortex in strategy shifting. Moreover, such a brain-inspired meta-controller may provide an advancement for learning architectures in robotics.

An egocentric vision based assistive co-robot.

PubMed

Zhang, Jingzhe; Zhuang, Lishuo; Wang, Yang; Zhou, Yameng; Meng, Yan; Hua, Gang

2013-06-01

We present the prototype of an egocentric vision based assistive co-robot system. In this co-robot system, the user is wearing a pair of glasses with a forward looking camera, and is actively engaged in the control loop of the robot in navigational tasks. The egocentric vision glasses serve for two purposes. First, it serves as a source of visual input to request the robot to find a certain object in the environment. Second, the motion patterns computed from the egocentric video associated with a specific set of head movements are exploited to guide the robot to find the object. These are especially helpful for quadriplegic individuals who do not have needed hand functionality for interaction and control with other modalities (e.g., joystick). In our co-robot system, when the robot does not fulfill the object finding task in a pre-specified time window, it would actively solicit user controls for guidance. Then the users can use the egocentric vision based gesture interface to orient the robot towards the direction of the object. After that the robot will automatically navigate towards the object until it finds it. Our experiments validated the efficacy of the closed-loop design to engage the human in the loop.

Non-destructive inspection in industrial equipment using robotic mobile manipulation

NASA Astrophysics Data System (ADS)

Maurtua, Iñaki; Susperregi, Loreto; Ansuategui, Ander; Fernández, Ane; Ibarguren, Aitor; Molina, Jorge; Tubio, Carlos; Villasante, Cristobal; Felsch, Torsten; Pérez, Carmen; Rodriguez, Jorge R.; Ghrissi, Meftah

2016-05-01

MAINBOT project has developed service robots based applications to autonomously execute inspection tasks in extensive industrial plants in equipment that is arranged horizontally (using ground robots) or vertically (climbing robots). The industrial objective has been to provide a means to help measuring several physical parameters in multiple points by autonomous robots, able to navigate and climb structures, handling non-destructive testing sensors. MAINBOT has validated the solutions in two solar thermal plants (cylindrical-parabolic collectors and central tower), that are very demanding from mobile manipulation point of view mainly due to the extension (e.g. a thermal solar plant of 50Mw, with 400 hectares, 400.000 mirrors, 180 km of absorber tubes, 140m height tower), the variability of conditions (outdoor, day-night), safety requirements, etc. Once the technology was validated in simulation, the system was deployed in real setups and different validation tests carried out. In this paper two of the achievements related with the ground mobile inspection system are presented: (1) Autonomous navigation localization and planning algorithms to manage navigation in huge extensions and (2) Non-Destructive Inspection operations: thermography based detection algorithms to provide automatic inspection abilities to the robots.

Solar-based navigation for robotic explorers

NASA Astrophysics Data System (ADS)

Shillcutt, Kimberly Jo

2000-12-01

This thesis introduces the application of solar position and shadowing information to robotic exploration. Power is a critical resource for robots with remote, long-term missions, so this research focuses on the power generation capabilities of robotic explorers during navigational tasks, in addition to power consumption. Solar power is primarily considered, with the possibility of wind power also contemplated. Information about the environment, including the solar ephemeris, terrain features, time of day, and surface location, is incorporated into a planning structure, allowing robots to accurately predict shadowing and thus potential costs and gains during navigational tasks. By evaluating its potential to generate and expend power, a robot can extend its lifetime and accomplishments. The primary tasks studied are coverage patterns, with a variety of plans developed for this research. The use of sun, terrain and temporal information also enables new capabilities of identifying and following sun-synchronous and sun-seeking paths. Digital elevation maps are combined with an ephemeris algorithm to calculate the altitude and azimuth of the sun from surface locations, and to identify and map shadows. Solar navigation path simulators use this information to perform searches through two-dimensional space, while considering temporal changes. Step by step simulations of coverage patterns also incorporate time in addition to location. Evaluations of solar and wind power generation, power consumption, area coverage, area overlap, and time are generated for sets of coverage patterns, with on-board environmental information linked to the simulations. This research is implemented on the Nomad robot for the Robotic Antarctic Meteorite Search. Simulators have been developed for coverage pattern tests, as well as for sun-synchronous and sun-seeking path searches. Results of field work and simulations are reported and analyzed, with demonstrated improvements in efficiency, productivity and lifetime of robotic explorers, along with new solar navigation abilities.

Bio-robots automatic navigation with electrical reward stimulation.

PubMed

Sun, Chao; Zhang, Xinlu; Zheng, Nenggan; Chen, Weidong; Zheng, Xiaoxiang

2012-01-01

Bio-robots that controlled by outer stimulation through brain computer interface (BCI) suffer from the dependence on realtime guidance of human operators. Current automatic navigation methods for bio-robots focus on the controlling rules to force animals to obey man-made commands, with animals' intelligence ignored. This paper proposes a new method to realize the automatic navigation for bio-robots with electrical micro-stimulation as real-time rewards. Due to the reward-seeking instinct and trial-and-error capability, bio-robot can be steered to keep walking along the right route with rewards and correct its direction spontaneously when rewards are deprived. In navigation experiments, rat-robots learn the controlling methods in short time. The results show that our method simplifies the controlling logic and realizes the automatic navigation for rat-robots successfully. Our work might have significant implication for the further development of bio-robots with hybrid intelligence.

IntelliTable: Inclusively-Designed Furniture with Robotic Capabilities.

PubMed

Prescott, Tony J; Conran, Sebastian; Mitchinson, Ben; Cudd, Peter

2017-01-01

IntelliTable is a new proof-of-principle assistive technology system with robotic capabilities in the form of an elegant universal cantilever table able to move around by itself, or under user control. We describe the design and current capabilities of the table and the human-centered design methodology used in its development and initial evaluation. The IntelliTable study has delivered robotic platform programmed by a smartphone that can navigate around a typical home or care environment, avoiding obstacles, and positioning itself at the user's command. It can also be configured to navigate itself to pre-ordained places positions within an environment using ceiling tracking, responsive optical guidance and object-based sonar navigation.

Development of a force-reflecting robotic platform for cardiac catheter navigation.

PubMed

Park, Jun Woo; Choi, Jaesoon; Pak, Hui-Nam; Song, Seung Joon; Lee, Jung Chan; Park, Yongdoo; Shin, Seung Min; Sun, Kyung

2010-11-01

Electrophysiological catheters are used for both diagnostics and clinical intervention. To facilitate more accurate and precise catheter navigation, robotic cardiac catheter navigation systems have been developed and commercialized. The authors have developed a novel force-reflecting robotic catheter navigation system. The system is a network-based master-slave configuration having a 3-degree of freedom robotic manipulator for operation with a conventional cardiac ablation catheter. The master manipulator implements a haptic user interface device with force feedback using a force or torque signal either measured with a sensor or estimated from the motor current signal in the slave manipulator. The slave manipulator is a robotic motion control platform on which the cardiac ablation catheter is mounted. The catheter motions-forward and backward movements, rolling, and catheter tip bending-are controlled by electromechanical actuators located in the slave manipulator. The control software runs on a real-time operating system-based workstation and implements the master/slave motion synchronization control of the robot system. The master/slave motion synchronization response was assessed with step, sinusoidal, and arbitrarily varying motion commands, and showed satisfactory performance with insignificant steady-state motion error. The current system successfully implemented the motion control function and will undergo safety and performance evaluation by means of animal experiments. Further studies on the force feedback control algorithm and on an active motion catheter with an embedded actuation mechanism are underway. © 2010, Copyright the Authors. Artificial Organs © 2010, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Mobile Robot Designed with Autonomous Navigation System

NASA Astrophysics Data System (ADS)

An, Feng; Chen, Qiang; Zha, Yanfang; Tao, Wenyin

2017-10-01

With the rapid development of robot technology, robots appear more and more in all aspects of life and social production, people also ask more requirements for the robot, one is that robot capable of autonomous navigation, can recognize the road. Take the common household sweeping robot as an example, which could avoid obstacles, clean the ground and automatically find the charging place; Another example is AGV tracking car, which can following the route and reach the destination successfully. This paper introduces a new type of robot navigation scheme: SLAM, which can build the environment map in a totally strange environment, and at the same time, locate its own position, so as to achieve autonomous navigation function.

Obstacle Avoidance On Roadways Using Range Data

NASA Astrophysics Data System (ADS)

Dunlay, R. Terry; Morgenthaler, David G.

1987-02-01

This report describes range data based obstacle avoidance techniques developed for use on an autonomous road-following robot vehicle. The purpose of these techniques is to detect and locate obstacles present in a road environment for navigation of a robot vehicle equipped with an active laser-based range sensor. Techniques are presented for obstacle detection, obstacle location, and coordinate transformations needed in the construction of Scene Models (symbolic structures representing the 3-D obstacle boundaries used by the vehicle's Navigator for path planning). These techniques have been successfully tested on an outdoor robotic vehicle, the Autonomous Land Vehicle (ALV), at speeds up to 3.5 km/hour.

Object Detection Techniques Applied on Mobile Robot Semantic Navigation

PubMed Central

Astua, Carlos; Barber, Ramon; Crespo, Jonathan; Jardon, Alberto

2014-01-01

The future of robotics predicts that robots will integrate themselves more every day with human beings and their environments. To achieve this integration, robots need to acquire information about the environment and its objects. There is a big need for algorithms to provide robots with these sort of skills, from the location where objects are needed to accomplish a task up to where these objects are considered as information about the environment. This paper presents a way to provide mobile robots with the ability-skill to detect objets for semantic navigation. This paper aims to use current trends in robotics and at the same time, that can be exported to other platforms. Two methods to detect objects are proposed, contour detection and a descriptor based technique, and both of them are combined to overcome their respective limitations. Finally, the code is tested on a real robot, to prove its accuracy and efficiency. PMID:24732101

30 Years of Neurosurgical Robots: Review and Trends for Manipulators and Associated Navigational Systems.

PubMed

Smith, James Andrew; Jivraj, Jamil; Wong, Ronnie; Yang, Victor

2016-04-01

This review provides an examination of contemporary neurosurgical robots and the developments that led to them. Improvements in localization, microsurgery and minimally invasive surgery have made robotic neurosurgery viable, as seen by the success of platforms such as the CyberKnife and neuromate. Neurosurgical robots can now perform specific surgical tasks such as skull-base drilling and craniotomies, as well as pedicle screw and cochlear electrode insertions. Growth trends in neurosurgical robotics are likely to continue but may be tempered by concerns over recent surgical robot recalls, commercially-driven surgeon training, and studies that show operational costs for surgical robotic procedures are often higher than traditional surgical methods. We point out that addressing performance issues related to navigation-related registration is an active area of research and will aid in improving overall robot neurosurgery performance and associated costs.

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.

Fuzzy Behavior Modulation with Threshold Activation for Autonomous Vehicle Navigation

NASA Technical Reports Server (NTRS)

Tunstel, Edward

2000-01-01

This paper describes fuzzy logic techniques used in a hierarchical behavior-based architecture for robot navigation. An architectural feature for threshold activation of fuzzy-behaviors is emphasized, which is potentially useful for tuning navigation performance in real world applications. The target application is autonomous local navigation of a small planetary rover. Threshold activation of low-level navigation behaviors is the primary focus. A preliminary assessment of its impact on local navigation performance is provided based on computer simulations.

Toward perception-based navigation using EgoSphere

NASA Astrophysics Data System (ADS)

Kawamura, Kazuhiko; Peters, R. Alan; Wilkes, Don M.; Koku, Ahmet B.; Sekman, Ali

2002-02-01

A method for perception-based egocentric navigation of mobile robots is described. Each robot has a local short-term memory structure called the Sensory EgoSphere (SES), which is indexed by azimuth, elevation, and time. Directional sensory processing modules write information on the SES at the location corresponding to the source direction. Each robot has a partial map of its operational area that it has received a priori. The map is populated with landmarks and is not necessarily metrically accurate. Each robot is given a goal location and a route plan. The route plan is a set of via-points that are not used directly. Instead, a robot uses each point to construct a Landmark EgoSphere (LES) a circular projection of the landmarks from the map onto an EgoSphere centered at the via-point. Under normal circumstances, the LES will be mostly unaffected by slight variations in the via-point location. Thus, the route plan is transformed into a set of via-regions each described by an LES. A robot navigates by comparing the next LES in its route plan to the current contents of its SES. It heads toward the indicated landmarks until its SES matches the LES sufficiently to indicate that the robot is near the suggested via-point. The proposed method is particularly useful for enabling the exchange of robust route informa-tion between robots under low data rate communications constraints. An example of such an exchange is given.

Hierarchical HMM based learning of navigation primitives for cooperative robotic endovascular catheterization.

PubMed

Rafii-Tari, Hedyeh; Liu, Jindong; Payne, Christopher J; Bicknell, Colin; Yang, Guang-Zhong

2014-01-01

Despite increased use of remote-controlled steerable catheter navigation systems for endovascular intervention, most current designs are based on master configurations which tend to alter natural operator tool interactions. This introduces problems to both ergonomics and shared human-robot control. This paper proposes a novel cooperative robotic catheterization system based on learning-from-demonstration. By encoding the higher-level structure of a catheterization task as a sequence of primitive motions, we demonstrate how to achieve prospective learning for complex tasks whilst incorporating subject-specific variations. A hierarchical Hidden Markov Model is used to model each movement primitive as well as their sequential relationship. This model is applied to generation of motion sequences, recognition of operator input, and prediction of future movements for the robot. The framework is validated by comparing catheter tip motions against the manual approach, showing significant improvements in the quality of catheterization. The results motivate the design of collaborative robotic systems that are intuitive to use, while reducing the cognitive workload of the operator.

A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots.

PubMed

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

PubMed Central

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

Sensor Fusion Based Model for Collision Free Mobile Robot Navigation.

PubMed

Almasri, Marwah; Elleithy, Khaled; Alajlan, Abrar

2015-12-26

Autonomous mobile robots have become a very popular and interesting topic in the last decade. Each of them are equipped with various types of sensors such as GPS, camera, infrared and ultrasonic sensors. These sensors are used to observe the surrounding environment. However, these sensors sometimes fail and have inaccurate readings. Therefore, the integration of sensor fusion will help to solve this dilemma and enhance the overall performance. This paper presents a collision free mobile robot navigation based on the fuzzy logic fusion model. Eight distance sensors and a range finder camera are used for the collision avoidance approach where three ground sensors are used for the line or path following approach. The fuzzy system is composed of nine inputs which are the eight distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot's wheels, and 24 fuzzy rules for the robot's movement. Webots Pro simulator is used for modeling the environment and the robot. The proposed methodology, which includes the collision avoidance based on fuzzy logic fusion model and line following robot, has been implemented and tested through simulation and real time experiments. Various scenarios have been presented with static and dynamic obstacles using one robot and two robots while avoiding obstacles in different shapes and sizes.

Tandem mobile robot system

DOEpatents

Buttz, James H.; Shirey, David L.; Hayward, David R.

2003-01-01

A robotic vehicle system for terrain navigation mobility provides a way to climb stairs, cross crevices, and navigate across difficult terrain by coupling two or more mobile robots with a coupling device and controlling the robots cooperatively in tandem.

Ultra wide-band localization and SLAM: a comparative study for mobile robot navigation.

PubMed

Segura, Marcelo J; Auat Cheein, Fernando A; Toibero, Juan M; Mut, Vicente; Carelli, Ricardo

2011-01-01

In this work, a comparative study between an Ultra Wide-Band (UWB) localization system and a Simultaneous Localization and Mapping (SLAM) algorithm is presented. Due to its high bandwidth and short pulses length, UWB potentially allows great accuracy in range measurements based on Time of Arrival (TOA) estimation. SLAM algorithms recursively estimates the map of an environment and the pose (position and orientation) of a mobile robot within that environment. The comparative study presented here involves the performance analysis of implementing in parallel an UWB localization based system and a SLAM algorithm on a mobile robot navigating within an environment. Real time results as well as error analysis are also shown in this work.

Robotic navigation and ablation.

PubMed

Malcolme-Lawes, L; Kanagaratnam, P

2010-12-01

Robotic technologies have been developed to allow optimal catheter stability and reproducible catheter movements with the aim of achieving contiguous and transmural lesion delivery. Two systems for remote navigation of catheters within the heart have been developed; the first is based on a magnetic navigation system (MNS) Niobe, Stereotaxis, Saint-Louis, Missouri, USA, the second is based on a steerable sheath system (Sensei, Hansen Medical, Mountain View, CA, USA). Both robotic and magnetic navigation systems have proven to be feasible for performing ablation of both simple and complex arrhythmias, particularly atrial fibrillation. Studies to date have shown similar success rates for AF ablation compared to that of manual ablation, with many groups finding a reduction in fluoroscopy times. However, the early learning curve of cases demonstrated longer procedure times, mainly due to additional setup times. With centres performing increasing numbers of robotic ablations and the introduction of a pressure monitoring system, lower power settings and instinctive driving software, complication rates are reducing, and fluoroscopy times have been lower than manual ablation in many studies. As the demand for catheter ablation for arrhythmias such as atrial fibrillation increases and the number of centres performing these ablations increases, the demand for systems which reduce the hand skill requirement and improve the comfort of the operator will also increase.

Primate-inspired vehicle navigation using optic flow and mental rotations

NASA Astrophysics Data System (ADS)

Arkin, Ronald C.; Dellaert, Frank; Srinivasan, Natesh; Kerwin, Ryan

2013-05-01

Robot navigation already has many relatively efficient solutions: reactive control, simultaneous localization and mapping (SLAM), Rapidly-Exploring Random Trees (RRTs), etc. But many primates possess an additional inherent spatial reasoning capability: mental rotation. Our research addresses the question of what role, if any, mental rotations can play in enhancing existing robot navigational capabilities. To answer this question we explore the use of optical flow as a basis for extracting abstract representations of the world, comparing these representations with a goal state of similar format and then iteratively providing a control signal to a robot to allow it to move in a direction consistent with achieving that goal state. We study a range of transformation methods to implement the mental rotation component of the architecture, including correlation and matching based on cognitive studies. We also include a discussion of how mental rotations may play a key role in understanding spatial advice giving, particularly from other members of the species, whether in map-based format, gestures, or other means of communication. Results to date are presented on our robotic platform.

Computer-Assisted Hip and Knee Arthroplasty. Navigation and Active Robotic Systems

PubMed Central

2004-01-01

Executive Summary Objective The Medical Advisory Secretariat undertook a review of the evidence on the effectiveness and cost-effectiveness of computer assisted hip and knee arthroplasty. The two computer assisted arthroplasty systems that are the topics of this review are (1) navigation and (2) robotic-assisted hip and knee arthroplasty. The Technology Computer-assisted arthroplasty consists of navigation and robotic systems. Surgical navigation is a visualization system that provides positional information about surgical tools or implants relative to a target bone on a computer display. Most of the navigation-assisted arthroplasty devices that are the subject of this review are licensed by Health Canada. Robotic systems are active robots that mill bone according to information from a computer-assisted navigation system. The robotic-assisted arthroplasty devices that are the subject of this review are not currently licensed by Health Canada. Review Strategy The Cochrane and International Network of Agencies for Health Technology Assessment databases did not identify any health technology assessments on navigation or robotic-assisted hip or knee arthroplasty. The MEDLINE and EMBASE databases were searched for articles published between January 1, 1996 and November 30, 2003. This search produced 367 studies, of which 9 met the inclusion criteria. Summary of Findings Navigation-Assisted Arthroplasty Five studies were identified that examined navigation-assisted arthroplasty. A Level 1 evidence study from Germany found a statistically significant difference in alignment and angular deviation between navigation-assisted and free-hand total knee arthroplasty in favour of navigation-assisted surgery. However, the endpoints in this study were short-term. To date, the long-term effects (need for revision, implant longevity, pain, functional performance) are unknown.(1) A Level 2 evidence short-term study found that navigation-assisted total knee arthroplasty was significantly better than a non-navigated procedure for one of five postoperative measured angles.(2) A Level 2 evidence short-term study found no statistically significant difference in the variation of the abduction angle between navigation-assisted and conventional total hip arthroplasty.(3) Level 3 evidence observational studies of navigation-assisted total knee arthroplasty and unicompartmental knee arthroplasty have been conducted. Two studies reported that “the follow-up of the navigated prostheses is currently too short to know if clinical outcome or survival rates are improved. Longer follow-up is required to determine the respective advantages and disadvantages of both techniques.”(4;5) Robotic-Assisted Arthroplasty Four studies were identified that examined robotic-assisted arthroplasty. A Level 1 evidence study revealed that there was no statistically significant difference between functional hip scores at 24 months post implantation between patients who underwent robotic-assisted primary hip arthroplasty and those that were treated with manual implantation.(6) Robotic-assisted arthroplasty had advantages in terms of preoperative planning and the accuracy of the intraoperative procedure.(6) Patients who underwent robotic-assisted hip arthroplasty had a higher dislocation rate and more revisions.(6) Robotic-assisted arthroplasty may prove effective with certain prostheses (e.g., anatomic) because their use may result in less muscle detachment.(6) An observational study (Level 3 evidence) found that the incidence of severe embolic events during hip relocation was lower with robotic arthroplasty than with manual surgery.(7) An observational study (Level 3 evidence) found that there was no significant difference in gait analyses of patients who underwent robotic-assisted total hip arthroplasty using robotic surgery compared to patients who were treated with conventional cementless total hip arthroplasty.(8) An observational study (Level 3 evidence) compared outcomes of total knee arthroplasty between patients undergoing robotic surgery and patients who were historical controls. Brief, qualitative results suggested that there was much broader variation of angles after manual total knee arthroplasty compared to the robotic technique and that there was no difference in knee functional scores or implant position at the 3 and 6 month follow-up.(9) PMID:23074452

Multi Sensor Fusion Framework for Indoor-Outdoor Localization of Limited Resource Mobile Robots

PubMed Central

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.

PubMed

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.

Hitchhiking Robots: A Collaborative Approach for Efficient Multi-Robot Navigation in Indoor Environments

PubMed Central

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

Hitchhiking Robots: A Collaborative Approach for Efficient Multi-Robot Navigation in Indoor Environments.

PubMed

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.

The Evolution of Computer-Assisted Total Hip Arthroplasty and Relevant Applications.

PubMed

Chang, Jun-Dong; Kim, In-Sung; Bhardwaj, Atul M; Badami, Ramachandra N

2017-03-01

In total hip arthroplasty (THA), the accurate positioning of implants is the key to achieve a good clinical outcome. Computer-assisted orthopaedic surgery (CAOS) has been developed for more accurate positioning of implants during the THA. There are passive, semi-active, and active systems in CAOS for THA. Navigation is a passive system that only provides information and guidance to the surgeon. There are 3 types of navigation: imageless navigation, computed tomography (CT)-based navigation, and fluoroscopy-based navigation. In imageless navigation system, a new method of registration without the need to register the anterior pelvic plane was introduced. CT-based navigation can be efficiently used for pelvic plane reference, the functional pelvic plane in supine which adjusts anterior pelvic plane sagittal tilt for targeting the cup orientation. Robot-assisted system can be either active or semi-active. The active robotic system performs the preparation for implant positioning as programmed preoperatively. It has been used for only femoral implant cavity preparation. Recently, program for cup positioning was additionally developed. Alternatively, for ease of surgeon acceptance, semi-active robot systems are developed. It was initially applied only for cup positioning. However, with the development of enhanced femoral workflows, this system can now be used to position both cup and stem. Though there have been substantial advancements in computer-assisted THA, its use can still be controversial at present due to the steep learning curve, intraoperative technical issues, high cost and etc. However, in the future, CAOS will certainly enable the surgeon to operate more accurately and lead to improved outcomes in THA as the technology continues to evolve rapidly.

Navigation and Self-Semantic Location of Drones in Indoor Environments by Combining the Visual Bug Algorithm and Entropy-Based Vision.

PubMed

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.

Navigation and Self-Semantic Location of Drones in Indoor Environments by Combining the Visual Bug Algorithm and Entropy-Based Vision

PubMed Central

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

AEKF-SLAM: A New Algorithm for Robotic Underwater Navigation

PubMed Central

Yuan, Xin; Martínez-Ortega, José-Fernán; Fernández, José Antonio Sánchez; Eckert, Martina

2017-01-01

In this work, we focus on key topics related to underwater Simultaneous Localization and Mapping (SLAM) applications. Moreover, a detailed review of major studies in the literature and our proposed solutions for addressing the problem are presented. The main goal of this paper is the enhancement of the accuracy and robustness of the SLAM-based navigation problem for underwater robotics with low computational costs. Therefore, we present a new method called AEKF-SLAM that employs an Augmented Extended Kalman Filter (AEKF)-based SLAM algorithm. The AEKF-based SLAM approach stores the robot poses and map landmarks in a single state vector, while estimating the state parameters via a recursive and iterative estimation-update process. Hereby, the prediction and update state (which exist as well in the conventional EKF) are complemented by a newly proposed augmentation stage. Applied to underwater robot navigation, the AEKF-SLAM has been compared with the classic and popular FastSLAM 2.0 algorithm. Concerning the dense loop mapping and line mapping experiments, it shows much better performances in map management with respect to landmark addition and removal, which avoid the long-term accumulation of errors and clutters in the created map. Additionally, the underwater robot achieves more precise and efficient self-localization and a mapping of the surrounding landmarks with much lower processing times. Altogether, the presented AEKF-SLAM method achieves reliably map revisiting, and consistent map upgrading on loop closure. PMID:28531135

Ultra Wide-Band Localization and SLAM: A Comparative Study for Mobile Robot Navigation

PubMed Central

Segura, Marcelo J.; Auat Cheein, Fernando A.; Toibero, Juan M.; Mut, Vicente; Carelli, Ricardo

2011-01-01

In this work, a comparative study between an Ultra Wide-Band (UWB) localization system and a Simultaneous Localization and Mapping (SLAM) algorithm is presented. Due to its high bandwidth and short pulses length, UWB potentially allows great accuracy in range measurements based on Time of Arrival (TOA) estimation. SLAM algorithms recursively estimates the map of an environment and the pose (position and orientation) of a mobile robot within that environment. The comparative study presented here involves the performance analysis of implementing in parallel an UWB localization based system and a SLAM algorithm on a mobile robot navigating within an environment. Real time results as well as error analysis are also shown in this work. PMID:22319397

Three-dimensional motor schema based navigation

NASA Technical Reports Server (NTRS)

Arkin, Ronald C.

1989-01-01

Reactive schema-based navigation is possible in space domains by extending the methods developed for ground-based navigation found within the Autonomous Robot Architecture (AuRA). Reformulation of two dimensional motor schemas for three dimensional applications is a straightforward process. The manifold advantages of schema-based control persist, including modular development, amenability to distributed processing, and responsiveness to environmental sensing. Simulation results show the feasibility of this methodology for space docking operations in a cluttered work area.

Trajectory and navigation system design for robotic and piloted missions to Mars

NASA Technical Reports Server (NTRS)

Thurman, S. W.; Matousek, S. E.

1991-01-01

Future Mars exploration missions, both robotic and piloted, may utilize Earth to Mars transfer trajectories that are significantly different from one another, depending upon the type of mission being flown and the time period during which the flight takes place. The use of new or emerging technologies for future missions to Mars, such as aerobraking and nuclear rocket propulsion, may yield navigation requirements that are much more stringent than those of past robotic missions, and are very difficult to meet for some trajectories. This article explores the interdependencies between the properties of direct Earth to Mars trajectories and the Mars approach navigation accuracy that can be achieved using different radio metric data types, such as ranging measurements between an approaching spacecraft and Mars orbiting relay satellites, or Earth based measurements such as coherent Doppler and very long baseline interferometry. The trajectory characteristics affecting navigation performance are identified, and the variations in accuracy that might be experienced over the range of different Mars approach trajectories are discussed. The results predict that three sigma periapsis altitude navigation uncertainties of 2 to 10 km can be achieved when a Mars orbiting satellite is used as a navigation aid.

Experiments in teleoperator and autonomous control of space robotic vehicles

NASA Technical Reports Server (NTRS)

Alexander, Harold L.

1990-01-01

A research program and strategy are described which include fundamental teleoperation issues and autonomous-control issues of sensing and navigation for satellite robots. The program consists of developing interfaces for visual operation and studying the consequences of interface designs as well as developing navigation and control technologies based on visual interaction. A space-robot-vehicle simulator is under development for use in virtual-environment teleoperation experiments and neutral-buoyancy investigations. These technologies can be utilized in a study of visual interfaces to address tradeoffs between head-tracking and manual remote cameras, panel-mounted and helmet-mounted displays, and stereoscopic and monoscopic display systems. The present program can provide significant data for the development of control experiments for autonomously controlled satellite robots.

Reactive, Safe Navigation for Lunar and Planetary Robots

NASA Technical Reports Server (NTRS)

Utz, Hans; Ruland, Thomas

2008-01-01

When humans return to the moon, Astronauts will be accompanied by robotic helpers. Enabling robots to safely operate near astronauts on the lunar surface has the potential to significantly improve the efficiency of crew surface operations. Safely operating robots in close proximity to astronauts on the lunar surface requires reactive obstacle avoidance capabilities not available on existing planetary robots. In this paper we present work on safe, reactive navigation using a stereo based high-speed terrain analysis and obstacle avoidance system. Advances in the design of the algorithms allow it to run terrain analysis and obstacle avoidance algorithms at full frame rate (30Hz) on off the shelf hardware. The results of this analysis are fed into a fast, reactive path selection module, enforcing the safety of the chosen actions. The key components of the system are discussed and test results are presented.

Autonomous navigation system and method

DOEpatents

Bruemmer, David J [Idaho Falls, ID; Few, Douglas A [Idaho Falls, ID

2009-09-08

A robot platform includes perceptors, locomotors, and a system controller, which executes instructions for autonomously navigating a robot. The instructions repeat, on each iteration through an event timing loop, the acts of defining an event horizon based on the robot's current velocity, detecting a range to obstacles around the robot, testing for an event horizon intrusion by determining if any range to the obstacles is within the event horizon, and adjusting rotational and translational velocity of the robot accordingly. If the event horizon intrusion occurs, rotational velocity is modified by a proportion of the current rotational velocity reduced by a proportion of the range to the nearest obstacle and translational velocity is modified by a proportion of the range to the nearest obstacle. If no event horizon intrusion occurs, translational velocity is set as a ratio of a speed factor relative to a maximum speed.

Sensor Fusion Based Model for Collision Free Mobile Robot Navigation

PubMed Central

Almasri, Marwah; Elleithy, Khaled; Alajlan, Abrar

2015-01-01

Autonomous mobile robots have become a very popular and interesting topic in the last decade. Each of them are equipped with various types of sensors such as GPS, camera, infrared and ultrasonic sensors. These sensors are used to observe the surrounding environment. However, these sensors sometimes fail and have inaccurate readings. Therefore, the integration of sensor fusion will help to solve this dilemma and enhance the overall performance. This paper presents a collision free mobile robot navigation based on the fuzzy logic fusion model. Eight distance sensors and a range finder camera are used for the collision avoidance approach where three ground sensors are used for the line or path following approach. The fuzzy system is composed of nine inputs which are the eight distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot’s wheels, and 24 fuzzy rules for the robot’s movement. Webots Pro simulator is used for modeling the environment and the robot. The proposed methodology, which includes the collision avoidance based on fuzzy logic fusion model and line following robot, has been implemented and tested through simulation and real time experiments. Various scenarios have been presented with static and dynamic obstacles using one robot and two robots while avoiding obstacles in different shapes and sizes. PMID:26712766

Nonparametric Online Learning Control for Soft Continuum Robot: An Enabling Technique for Effective Endoscopic Navigation

PubMed Central

Lee, Kit-Hang; Fu, Denny K.C.; Leong, Martin C.W.; Chow, Marco; Fu, Hing-Choi; Althoefer, Kaspar; Sze, Kam Yim; Yeung, Chung-Kwong

2017-01-01

Abstract Bioinspired robotic structures comprising soft actuation units have attracted increasing research interest. Taking advantage of its inherent compliance, soft robots can assure safe interaction with external environments, provided that precise and effective manipulation could be achieved. Endoscopy is a typical application. However, previous model-based control approaches often require simplified geometric assumptions on the soft manipulator, but which could be very inaccurate in the presence of unmodeled external interaction forces. In this study, we propose a generic control framework based on nonparametric and online, as well as local, training to learn the inverse model directly, without prior knowledge of the robot's structural parameters. Detailed experimental evaluation was conducted on a soft robot prototype with control redundancy, performing trajectory tracking in dynamically constrained environments. Advanced element formulation of finite element analysis is employed to initialize the control policy, hence eliminating the need for random exploration in the robot's workspace. The proposed control framework enabled a soft fluid-driven continuum robot to follow a 3D trajectory precisely, even under dynamic external disturbance. Such enhanced control accuracy and adaptability would facilitate effective endoscopic navigation in complex and changing environments. PMID:29251567

Nonparametric Online Learning Control for Soft Continuum Robot: An Enabling Technique for Effective Endoscopic Navigation.

PubMed

Lee, Kit-Hang; Fu, Denny K C; Leong, Martin C W; Chow, Marco; Fu, Hing-Choi; Althoefer, Kaspar; Sze, Kam Yim; Yeung, Chung-Kwong; Kwok, Ka-Wai

2017-12-01

Bioinspired robotic structures comprising soft actuation units have attracted increasing research interest. Taking advantage of its inherent compliance, soft robots can assure safe interaction with external environments, provided that precise and effective manipulation could be achieved. Endoscopy is a typical application. However, previous model-based control approaches often require simplified geometric assumptions on the soft manipulator, but which could be very inaccurate in the presence of unmodeled external interaction forces. In this study, we propose a generic control framework based on nonparametric and online, as well as local, training to learn the inverse model directly, without prior knowledge of the robot's structural parameters. Detailed experimental evaluation was conducted on a soft robot prototype with control redundancy, performing trajectory tracking in dynamically constrained environments. Advanced element formulation of finite element analysis is employed to initialize the control policy, hence eliminating the need for random exploration in the robot's workspace. The proposed control framework enabled a soft fluid-driven continuum robot to follow a 3D trajectory precisely, even under dynamic external disturbance. Such enhanced control accuracy and adaptability would facilitate effective endoscopic navigation in complex and changing environments.

A spatial registration method for navigation system combining O-arm with spinal surgery robot

NASA Astrophysics Data System (ADS)

Bai, H.; Song, G. L.; Zhao, Y. W.; Liu, X. Z.; Jiang, Y. X.

2018-05-01

The minimally invasive surgery in spinal surgery has become increasingly popular in recent years as it reduces the chances of complications during post-operation. However, the procedure of spinal surgery is complicated and the surgical vision of minimally invasive surgery is limited. In order to increase the quality of percutaneous pedicle screw placement, the O-arm that is a mobile intraoperative imaging system is used to assist surgery. The robot navigation system combined with O-arm is also increasing, with the extensive use of O-arm. One of the major problems in the surgical navigation system is to associate the patient space with the intra-operation image space. This study proposes a spatial registration method of spinal surgical robot navigation system, which uses the O-arm to scan a calibration phantom with metal calibration spheres. First, the metal artifacts were reduced in the CT slices and then the circles in the images based on the moments invariant could be identified. Further, the position of the calibration sphere in the image space was obtained. Moreover, the registration matrix is obtained based on the ICP algorithm. Finally, the position error is calculated to verify the feasibility and accuracy of the registration method.

The Evolution of Computer-Assisted Total Hip Arthroplasty and Relevant Applications

PubMed Central

Kim, In-Sung; Bhardwaj, Atul M.; Badami, Ramachandra N.

2017-01-01

In total hip arthroplasty (THA), the accurate positioning of implants is the key to achieve a good clinical outcome. Computer-assisted orthopaedic surgery (CAOS) has been developed for more accurate positioning of implants during the THA. There are passive, semi-active, and active systems in CAOS for THA. Navigation is a passive system that only provides information and guidance to the surgeon. There are 3 types of navigation: imageless navigation, computed tomography (CT)-based navigation, and fluoroscopy-based navigation. In imageless navigation system, a new method of registration without the need to register the anterior pelvic plane was introduced. CT-based navigation can be efficiently used for pelvic plane reference, the functional pelvic plane in supine which adjusts anterior pelvic plane sagittal tilt for targeting the cup orientation. Robot-assisted system can be either active or semi-active. The active robotic system performs the preparation for implant positioning as programmed preoperatively. It has been used for only femoral implant cavity preparation. Recently, program for cup positioning was additionally developed. Alternatively, for ease of surgeon acceptance, semi-active robot systems are developed. It was initially applied only for cup positioning. However, with the development of enhanced femoral workflows, this system can now be used to position both cup and stem. Though there have been substantial advancements in computer-assisted THA, its use can still be controversial at present due to the steep learning curve, intraoperative technical issues, high cost and etc. However, in the future, CAOS will certainly enable the surgeon to operate more accurately and lead to improved outcomes in THA as the technology continues to evolve rapidly. PMID:28316957

ARK: Autonomous mobile robot in an industrial environment

NASA Technical Reports Server (NTRS)

Nickerson, S. B.; Jasiobedzki, P.; Jenkin, M.; Jepson, A.; Milios, E.; Down, B.; Service, J. R. R.; Terzopoulos, D.; Tsotsos, J.; Wilkes, D.

1994-01-01

This paper describes research on the ARK (Autonomous Mobile Robot in a Known Environment) project. The technical objective of the project is to build a robot that can navigate in a complex industrial environment using maps with permanent structures. The environment is not altered in any way by adding easily identifiable beacons and the robot relies on naturally occurring objects to use as visual landmarks for navigation. The robot is equipped with various sensors that can detect unmapped obstacles, landmarks and objects. In this paper we describe the robot's industrial environment, it's architecture, a novel combined range and vision sensor and our recent results in controlling the robot in the real-time detection of objects using their color and in the processing of the robot's range and vision sensor data for navigation.

Current state of computer navigation and robotics in unicompartmental and total knee arthroplasty: a systematic review with meta-analysis.

PubMed

van der List, Jelle P; Chawla, Harshvardhan; Joskowicz, Leo; Pearle, Andrew D

2016-11-01

Recently, there is a growing interest in surgical variables that are intraoperatively controlled by orthopaedic surgeons, including lower leg alignment, component positioning and soft tissues balancing. Since more tight control over these factors is associated with improved outcomes of unicompartmental knee arthroplasty and total knee arthroplasty (TKA), several computer navigation and robotic-assisted systems have been developed. Although mechanical axis accuracy and component positioning have been shown to improve with computer navigation, no superiority in functional outcomes has yet been shown. This could be explained by the fact that many differences exist between the number and type of surgical variables these systems control. Most systems control lower leg alignment and component positioning, while some in addition control soft tissue balancing. Finally, robotic-assisted systems have the additional advantage of improving surgical precision. A systematic search in PubMed, Embase and Cochrane Library resulted in 40 comparative studies and three registries on computer navigation reporting outcomes of 474,197 patients, and 21 basic science and clinical studies on robotic-assisted knee arthroplasty. Twenty-eight of these comparative computer navigation studies reported Knee Society Total scores in 3504 patients. Stratifying by type of surgical variables, no significant differences were noted in outcomes between surgery with computer-navigated TKA controlling for alignment and component positioning versus conventional TKA (p = 0.63). However, significantly better outcomes were noted following computer-navigated TKA that also controlled for soft tissue balancing versus conventional TKA (mean difference 4.84, 95 % Confidence Interval 1.61, 8.07, p = 0.003). A literature review of robotic systems showed that these systems can, similarly to computer navigation, reliably improve lower leg alignment, component positioning and soft tissues balancing. Furthermore, two studies comparing robotic-assisted with computer-navigated surgery reported superiority of robotic-assisted surgery in controlling these factors. Manually controlling all these surgical variables can be difficult for the orthopaedic surgeon. Findings in this study suggest that computer navigation or robotic assistance may help managing these multiple variables and could improve outcomes. Future studies assessing the role of soft tissue balancing in knee arthroplasty and long-term follow-up studies assessing the role of computer-navigated and robotic-assisted knee arthroplasty are needed.

Highly dexterous 2-module soft robot for intra-organ navigation in minimally invasive surgery.

PubMed

Abidi, Haider; Gerboni, Giada; Brancadoro, Margherita; Fras, Jan; Diodato, Alessandro; Cianchetti, Matteo; Wurdemann, Helge; Althoefer, Kaspar; Menciassi, Arianna

2018-02-01

For some surgical interventions, like the Total Mesorectal Excision (TME), traditional laparoscopes lack the flexibility to safely maneuver and reach difficult surgical targets. This paper answers this need through designing, fabricating and modelling a highly dexterous 2-module soft robot for minimally invasive surgery (MIS). A soft robotic approach is proposed that uses flexible fluidic actuators (FFAs) allowing highly dexterous and inherently safe navigation. Dexterity is provided by an optimized design of fluid chambers within the robot modules. Safe physical interaction is ensured by fabricating the entire structure by soft and compliant elastomers, resulting in a squeezable 2-module robot. An inner free lumen/chamber along the central axis serves as a guide of flexible endoscopic tools. A constant curvature based inverse kinematics model is also proposed, providing insight into the robot capabilities. Experimental tests in a surgical scenario using a cadaver model are reported, demonstrating the robot advantages over standard systems in a realistic MIS environment. Simulations and experiments show the efficacy of the proposed soft robot. Copyright © 2017 John Wiley & Sons, Ltd.

Fuzzy integral-based gaze control architecture incorporated with modified-univector field-based navigation for humanoid robots.

PubMed

Yoo, Jeong-Ki; Kim, Jong-Hwan

2012-02-01

When a humanoid robot moves in a dynamic environment, a simple process of planning and following a path may not guarantee competent performance for dynamic obstacle avoidance because the robot acquires limited information from the environment using a local vision sensor. Thus, it is essential to update its local map as frequently as possible to obtain more information through gaze control while walking. This paper proposes a fuzzy integral-based gaze control architecture incorporated with the modified-univector field-based navigation for humanoid robots. To determine the gaze direction, four criteria based on local map confidence, waypoint, self-localization, and obstacles, are defined along with their corresponding partial evaluation functions. Using the partial evaluation values and the degree of consideration for criteria, fuzzy integral is applied to each candidate gaze direction for global evaluation. For the effective dynamic obstacle avoidance, partial evaluation functions about self-localization error and surrounding obstacles are also used for generating virtual dynamic obstacle for the modified-univector field method which generates the path and velocity of robot toward the next waypoint. The proposed architecture is verified through the comparison with the conventional weighted sum-based approach with the simulations using a developed simulator for HanSaRam-IX (HSR-IX).

Multidisciplinary unmanned technology teammate (MUTT)

NASA Astrophysics Data System (ADS)

Uzunovic, Nenad; Schneider, Anne; Lacaze, Alberto; Murphy, Karl; Del Giorno, Mark

2013-01-01

The U.S. Army Tank Automotive Research, Development and Engineering Center (TARDEC) held an autonomous robot competition called CANINE in June 2012. The goal of the competition was to develop innovative and natural control methods for robots. This paper describes the winning technology, including the vision system, the operator interaction, and the autonomous mobility. The rules stated only gestures or voice commands could be used for control. The robots would learn a new object at the start of each phase, find the object after it was thrown into a field, and return the object to the operator. Each of the six phases became more difficult, including clutter of the same color or shape as the object, moving and stationary obstacles, and finding the operator who moved from the starting location to a new location. The Robotic Research Team integrated techniques in computer vision, speech recognition, object manipulation, and autonomous navigation. A multi-filter computer vision solution reliably detected the objects while rejecting objects of similar color or shape, even while the robot was in motion. A speech-based interface with short commands provided close to natural communication of complicated commands from the operator to the robot. An innovative gripper design allowed for efficient object pickup. A robust autonomous mobility and navigation solution for ground robotic platforms provided fast and reliable obstacle avoidance and course navigation. The research approach focused on winning the competition while remaining cognizant and relevant to real world applications.

Flexible robotics with electromagnetic tracking improves safety and efficiency during in vitro endovascular navigation.

PubMed

Schwein, Adeline; Kramer, Ben; Chinnadurai, Ponraj; Walker, Sean; O'Malley, Marcia; Lumsden, Alan; Bismuth, Jean

2017-02-01

One limitation of the use of robotic catheters is the lack of real-time three-dimensional (3D) localization and position updating: they are still navigated based on two-dimensional (2D) X-ray fluoroscopic projection images. Our goal was to evaluate whether incorporating an electromagnetic (EM) sensor on a robotic catheter tip could improve endovascular navigation. Six users were tasked to navigate using a robotic catheter with incorporated EM sensors in an aortic aneurysm phantom. All users cannulated two anatomic targets (left renal artery and posterior "gate") using four visualization modes: (1) standard fluoroscopy mode (control), (2) 2D fluoroscopy mode showing real-time virtual catheter orientation from EM tracking, (3) 3D model of the phantom with anteroposterior and endoluminal view, and (4) 3D model with anteroposterior and lateral view. Standard X-ray fluoroscopy was always available. Cannulation and fluoroscopy times were noted for every mode. 3D positions of the EM tip sensor were recorded at 4 Hz to establish kinematic metrics. The EM sensor-incorporated catheter navigated as expected according to all users. The success rate for cannulation was 100%. For the posterior gate target, mean cannulation times in minutes:seconds were 8:12, 4:19, 4:29, and 3:09, respectively, for modes 1, 2, 3 and 4 (P = .013), and mean fluoroscopy times were 274, 20, 29, and 2 seconds, respectively (P = .001). 3D path lengths, spectral arc length, root mean dimensionless jerk, and number of submovements were significantly improved when EM tracking was used (P < .05), showing higher quality of catheter movement with EM navigation. The EM tracked robotic catheter allowed better real-time 3D orientation, facilitating navigation, with a reduction in cannulation and fluoroscopy times and improvement of motion consistency and efficiency. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Robotic platform for traveling on vertical piping network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nance, Thomas A; Vrettos, Nick J; Krementz, Daniel

This invention relates generally to robotic systems and is specifically designed for a robotic system that can navigate vertical pipes within a waste tank or similar environment. The robotic system allows a process for sampling, cleaning, inspecting and removing waste around vertical pipes by supplying a robotic platform that uses the vertical pipes to support and navigate the platform above waste material contained in the tank.

Obstacle negotiation control for a mobile robot suspended on overhead ground wires by optoelectronic sensors

NASA Astrophysics Data System (ADS)

Zheng, Li; Yi, Ruan

2009-11-01

Power line inspection and maintenance already benefit from developments in mobile robotics. This paper presents mobile robots capable of crossing obstacles on overhead ground wires. A teleoperated robot realizes inspection and maintenance tasks on power transmission line equipment. The inspection robot is driven by 11 motor with two arms, two wheels and two claws. The inspection robot is designed to realize the function of observation, grasp, walk, rolling, turn, rise, and decline. This paper is oriented toward 100% reliable obstacle detection and identification, and sensor fusion to increase the autonomy level. An embedded computer based on PC/104 bus is chosen as the core of control system. Visible light camera and thermal infrared Camera are both installed in a programmable pan-and-tilt camera (PPTC) unit. High-quality visual feedback rapidly becomes crucial for human-in-the-loop control and effective teleoperation. The communication system between the robot and the ground station is based on Mesh wireless networks by 700 MHz bands. An expert system programmed with Visual C++ is developed to implement the automatic control. Optoelectronic laser sensors and laser range scanner were installed in robot for obstacle-navigation control to grasp the overhead ground wires. A novel prototype with careful considerations on mobility was designed to inspect the 500KV power transmission lines. Results of experiments demonstrate that the robot can be applied to execute the navigation and inspection tasks.

Solving Navigational Uncertainty Using Grid Cells on Robots

PubMed Central

Milford, Michael J.; Wiles, Janet; Wyeth, Gordon F.

2010-01-01

To successfully navigate their habitats, many mammals use a combination of two mechanisms, path integration and calibration using landmarks, which together enable them to estimate their location and orientation, or pose. In large natural environments, both these mechanisms are characterized by uncertainty: the path integration process is subject to the accumulation of error, while landmark calibration is limited by perceptual ambiguity. It remains unclear how animals form coherent spatial representations in the presence of such uncertainty. Navigation research using robots has determined that uncertainty can be effectively addressed by maintaining multiple probabilistic estimates of a robot's pose. Here we show how conjunctive grid cells in dorsocaudal medial entorhinal cortex (dMEC) may maintain multiple estimates of pose using a brain-based robot navigation system known as RatSLAM. Based both on rodent spatially-responsive cells and functional engineering principles, the cells at the core of the RatSLAM computational model have similar characteristics to rodent grid cells, which we demonstrate by replicating the seminal Moser experiments. We apply the RatSLAM model to a new experimental paradigm designed to examine the responses of a robot or animal in the presence of perceptual ambiguity. Our computational approach enables us to observe short-term population coding of multiple location hypotheses, a phenomenon which would not be easily observable in rodent recordings. We present behavioral and neural evidence demonstrating that the conjunctive grid cells maintain and propagate multiple estimates of pose, enabling the correct pose estimate to be resolved over time even without uniquely identifying cues. While recent research has focused on the grid-like firing characteristics, accuracy and representational capacity of grid cells, our results identify a possible critical and unique role for conjunctive grid cells in filtering sensory uncertainty. We anticipate our study to be a starting point for animal experiments that test navigation in perceptually ambiguous environments. PMID:21085643

Perception-action map learning in controlled multiscroll systems applied to robot navigation.

PubMed

Arena, Paolo; De Fiore, Sebastiano; Fortuna, Luigi; Patané, Luca

2008-12-01

In this paper a new technique for action-oriented perception in robots is presented. The paper starts from exploiting the successful implementation of the basic idea that perceptual states can be embedded into chaotic attractors whose dynamical evolution can be associated with sensorial stimuli. In this way, it can be possible to encode, into the chaotic dynamics, environment-dependent patterns. These have to be suitably linked to an action, executed by the robot, to fulfill an assigned mission. This task is addressed here: the action-oriented perception loop is closed by introducing a simple unsupervised learning stage, implemented via a bio-inspired structure based on the motor map paradigm. In this way, perceptual meanings, useful for solving a given task, can be autonomously learned, based on the environment-dependent patterns embedded into the controlled chaotic dynamics. The presented framework has been tested on a simulated robot and the performance have been successfully compared with other traditional navigation control paradigms. Moreover an implementation of the proposed architecture on a Field Programmable Gate Array is briefly outlined and preliminary experimental results on a roving robot are also reported.

Learning Long-Range Vision for an Offroad Robot

DTIC Science & Technology

2008-09-01

robot to perceive and navigate in an unstructured natural world is a difficult task. Without learning, navigation systems are short-range and extremely...unsupervised or weakly supervised learning methods are necessary for training general feature representations for natural scenes. The process was...the world looked dark, and Legos when I was weary. iii ABSTRACT Teaching a robot to perceive and navigate in an unstructured natural world is a

Spatial abstraction for autonomous robot navigation.

PubMed

Epstein, Susan L; Aroor, Anoop; Evanusa, Matthew; Sklar, Elizabeth I; Parsons, Simon

2015-09-01

Optimal navigation for a simulated robot relies on a detailed map and explicit path planning, an approach problematic for real-world robots that are subject to noise and error. This paper reports on autonomous robots that rely on local spatial perception, learning, and commonsense rationales instead. Despite realistic actuator error, learned spatial abstractions form a model that supports effective travel.

Navigation and Robotics in Spinal Surgery: Where Are We Now?

PubMed

Overley, Samuel C; Cho, Samuel K; Mehta, Ankit I; Arnold, Paul M

2017-03-01

Spine surgery has experienced much technological innovation over the past several decades. The field has seen advancements in operative techniques, implants and biologics, and equipment such as computer-assisted navigation and surgical robotics. With the arrival of real-time image guidance and navigation capabilities along with the computing ability to process and reconstruct these data into an interactive three-dimensional spinal "map", so too have the applications of surgical robotic technology. While spinal robotics and navigation represent promising potential for improving modern spinal surgery, it remains paramount to demonstrate its superiority as compared to traditional techniques prior to assimilation of its use amongst surgeons.The applications for intraoperative navigation and image-guided robotics have expanded to surgical resection of spinal column and intradural tumors, revision procedures on arthrodesed spines, and deformity cases with distorted anatomy. Additionally, these platforms may mitigate much of the harmful radiation exposure in minimally invasive surgery to which the patient, surgeon, and ancillary operating room staff are subjected.Spine surgery relies upon meticulous fine motor skills to manipulate neural elements and a steady hand while doing so, often exploiting small working corridors utilizing exposures that minimize collateral damage. Additionally, the procedures may be long and arduous, predisposing the surgeon to both mental and physical fatigue. In light of these characteristics, spine surgery may actually be an ideal candidate for the integration of navigation and robotic-assisted procedures.With this paper, we aim to critically evaluate the current literature and explore the options available for intraoperative navigation and robotic-assisted spine surgery. Copyright © 2016 by the Congress of Neurological Surgeons.

Reasoning on the Self-Organizing Incremental Associative Memory for Online Robot Path Planning

NASA Astrophysics Data System (ADS)

Kawewong, Aram; Honda, Yutaro; Tsuboyama, Manabu; Hasegawa, Osamu

Robot path-planning is one of the important issues in robotic navigation. This paper presents a novel robot path-planning approach based on the associative memory using Self-Organizing Incremental Neural Networks (SOINN). By the proposed method, an environment is first autonomously divided into a set of path-fragments by junctions. Each fragment is represented by a sequence of preliminarily generated common patterns (CPs). In an online manner, a robot regards the current path as the associative path-fragments, each connected by junctions. The reasoning technique is additionally proposed for decision making at each junction to speed up the exploration time. Distinct from other methods, our method does not ignore the important information about the regions between junctions (path-fragments). The resultant number of path-fragments is also less than other method. Evaluation is done via Webots physical 3D-simulated and real robot experiments, where only distance sensors are available. Results show that our method can represent the environment effectively; it enables the robot to solve the goal-oriented navigation problem in only one episode, which is actually less than that necessary for most of the Reinforcement Learning (RL) based methods. The running time is proved finite and scales well with the environment. The resultant number of path-fragments matches well to the environment.

Soft computing-based terrain visual sensing and data fusion for unmanned ground robotic systems

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir

2006-05-01

In this paper, we have primarily discussed technical challenges and navigational skill requirements of mobile robots for traversability path planning in natural terrain environments similar to Mars surface terrains. We have described different methods for detection of salient terrain features based on imaging texture analysis techniques. We have also presented three competing techniques for terrain traversability assessment of mobile robots navigating in unstructured natural terrain environments. These three techniques include: a rule-based terrain classifier, a neural network-based terrain classifier, and a fuzzy-logic terrain classifier. Each proposed terrain classifier divides a region of natural terrain into finite sub-terrain regions and classifies terrain condition exclusively within each sub-terrain region based on terrain visual clues. The Kalman Filtering technique is applied for aggregative fusion of sub-terrain assessment results. The last two terrain classifiers are shown to have remarkable capability for terrain traversability assessment of natural terrains. We have conducted a comparative performance evaluation of all three terrain classifiers and presented the results in this paper.

Development of a two wheeled self balancing robot with speech recognition and navigation algorithm

NASA Astrophysics Data System (ADS)

Rahman, Md. Muhaimin; Ashik-E-Rasul, Haq, Nowab. Md. Aminul; Hassan, Mehedi; Hasib, Irfan Mohammad Al; Hassan, K. M. Rafidh

2016-07-01

This paper is aimed to discuss modeling, construction and development of navigation algorithm of a two wheeled self balancing mobile robot in an enclosure. In this paper, we have discussed the design of two of the main controller algorithms, namely PID algorithms, on the robot model. Simulation is performed in the SIMULINK environment. The controller is developed primarily for self-balancing of the robot and also it's positioning. As for the navigation in an enclosure, template matching algorithm is proposed for precise measurement of the robot position. The navigation system needs to be calibrated before navigation process starts. Almost all of the earlier template matching algorithms that can be found in the open literature can only trace the robot. But the proposed algorithm here can also locate the position of other objects in an enclosure, like furniture, tables etc. This will enable the robot to know the exact location of every stationary object in the enclosure. Moreover, some additional features, such as Speech Recognition and Object Detection, are added. For Object Detection, the single board Computer Raspberry Pi is used. The system is programmed to analyze images captured via the camera, which are then processed through background subtraction, followed by active noise reduction.

Autonomous navigation method for substation inspection robot based on travelling deviation

NASA Astrophysics Data System (ADS)

Yang, Guoqing; Xu, Wei; Li, Jian; Fu, Chongguang; Zhou, Hao; Zhang, Chuanyou; Shao, Guangting

2017-06-01

A new method of edge detection is proposed in substation environment, which can realize the autonomous navigation of the substation inspection robot. First of all, the road image and information are obtained by using an image acquisition device. Secondly, the noise in the region of interest which is selected in the road image, is removed with the digital image processing algorithm, the road edge is extracted by Canny operator, and the road boundaries are extracted by Hough transform. Finally, the distance between the robot and the left and the right boundaries is calculated, and the travelling distance is obtained. The robot's walking route is controlled according to the travel deviation and the preset threshold. Experimental results show that the proposed method can detect the road area in real time, and the algorithm has high accuracy and stable performance.

Design of a laser navigation system for the inspection robot used in substation

NASA Astrophysics Data System (ADS)

Zhu, Jing; Sun, Yanhe; Sun, Deli

2017-01-01

Aimed at the deficiency of the magnetic guide and RFID parking system used by substation inspection robot now, a laser navigation system is designed, and the system structure, the method of map building and positioning are all introduced. The system performance is tested in a 500kV substation, and the result show that the repetitive precision of navigation system is precise enough to help the robot fulfill inspection tasks.

Landmark-based robust navigation for tactical UGV control in GPS-denied communication-degraded environments

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.

Electromagnetic tracking of flexible robotic catheters enables "assisted navigation" and brings automation to endovascular navigation in an in vitro study.

PubMed

Schwein, Adeline; Kramer, Benjamin; Chinnadurai, Ponraj; Virmani, Neha; Walker, Sean; O'Malley, Marcia; Lumsden, Alan B; Bismuth, Jean

2018-04-01

Combining three-dimensional (3D) catheter control with electromagnetic (EM) tracking-based navigation significantly reduced fluoroscopy time and improved robotic catheter movement quality in a previous in vitro pilot study. The aim of this study was to expound on previous results and to expand the value of EM tracking with a novel feature, assistednavigation, allowing automatic catheter orientation and semiautomatic vessel cannulation. Eighteen users navigated a robotic catheter in an aortic aneurysm phantom using an EM guidewire and a modified 9F robotic catheter with EM sensors at the tip of both leader and sheath. All users cannulated two targets, the left renal artery and posterior gate, using four visualization modes: (1) Standard fluoroscopy (control). (2) 2D biplane fluoroscopy showing real-time virtual catheter localization and orientation from EM tracking. (3) 2D biplane fluoroscopy with novel EM assisted navigation allowing the user to define the target vessel. The robotic catheter orients itself automatically toward the target; the user then only needs to advance the guidewire following this predefined optimized path to catheterize the vessel. Then, while advancing the catheter over the wire, the assisted navigation automatically modifies catheter bending and rotation in order to ensure smooth progression, avoiding loss of wire access. (4) Virtual 3D representation of the phantom showing real-time virtual catheter localization and orientation. Standard fluoroscopy was always available; cannulation and fluoroscopy times were noted for every mode and target cannulation. Quality of catheter movement was assessed by measuring the number of submovements of the catheter using the 3D coordinates of the EM sensors. A t-test was used to compare the standard fluoroscopy mode against EM tracking modes. EM tracking significantly reduced the mean fluoroscopy time (P < .001) and the number of submovements (P < .02) for both cannulation tasks. For the posterior gate, mean cannulation time was also significantly reduced when using EM tracking (P < .001). The use of novel EM assisted navigation feature (mode 3) showed further reduced cannulation time for the posterior gate (P = .002) and improved quality of catheter movement for the left renal artery cannulation (P = .021). These results confirmed the findings of a prior study that highlighted the value of combining 3D robotic catheter control and 3D navigation to improve safety and efficiency of endovascular procedures. The novel EM assisted navigation feature augments the robotic master/slave concept with automated catheter orientation toward the target and shows promising results in reducing procedure time and improving catheter motion quality. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Control of free-flying space robot manipulator systems

NASA Technical Reports Server (NTRS)

Cannon, Robert H., Jr.

1977-01-01

To accelerate the development of multi-armed, free-flying satellite manipulators, a fixed-base cooperative manipulation facility is being developed. The work performed on multiple arm cooperation on a free-flying robot is summarized. Research is also summarized on global navigation and control of free-flying space robots. The Locomotion Enhancement via Arm Pushoff (LEAP) approach is described and progress to date is presented.

Determining navigability of terrain using point cloud data.

PubMed

Cockrell, Stephanie; Lee, Gregory; Newman, Wyatt

2013-06-01

This paper presents an algorithm to identify features of the navigation surface in front of a wheeled robot. Recent advances in mobile robotics have brought about the development of smart wheelchairs to assist disabled people, allowing them to be more independent. These robots have a human occupant and operate in real environments where they must be able to detect hazards like holes, stairs, or obstacles. Furthermore, to ensure safe navigation, wheelchairs often need to locate and navigate on ramps. The algorithm is implemented on data from a Kinect and can effectively identify these features, increasing occupant safety and allowing for a smoother ride.

Visual terrain mapping for traversable path planning of mobile robots

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir; Amrani, Rachida; Tunstel, Edward W.

2004-10-01

In this paper, we have primarily discussed technical challenges and navigational skill requirements of mobile robots for traversability path planning in natural terrain environments similar to Mars surface terrains. We have described different methods for detection of salient terrain features based on imaging texture analysis techniques. We have also presented three competing techniques for terrain traversability assessment of mobile robots navigating in unstructured natural terrain environments. These three techniques include: a rule-based terrain classifier, a neural network-based terrain classifier, and a fuzzy-logic terrain classifier. Each proposed terrain classifier divides a region of natural terrain into finite sub-terrain regions and classifies terrain condition exclusively within each sub-terrain region based on terrain visual clues. The Kalman Filtering technique is applied for aggregative fusion of sub-terrain assessment results. The last two terrain classifiers are shown to have remarkable capability for terrain traversability assessment of natural terrains. We have conducted a comparative performance evaluation of all three terrain classifiers and presented the results in this paper.

Reinforcement learning algorithms for robotic navigation in dynamic environments.

PubMed

Yen, Gary G; Hickey, Travis W

2004-04-01

The purpose of this study was to examine improvements to reinforcement learning (RL) algorithms in order to successfully interact within dynamic environments. The scope of the research was that of RL algorithms as applied to robotic navigation. Proposed improvements include: addition of a forgetting mechanism, use of feature based state inputs, and hierarchical structuring of an RL agent. Simulations were performed to evaluate the individual merits and flaws of each proposal, to compare proposed methods to prior established methods, and to compare proposed methods to theoretically optimal solutions. Incorporation of a forgetting mechanism did considerably improve the learning times of RL agents in a dynamic environment. However, direct implementation of a feature-based RL agent did not result in any performance enhancements, as pure feature-based navigation results in a lack of positional awareness, and the inability of the agent to determine the location of the goal state. Inclusion of a hierarchical structure in an RL agent resulted in significantly improved performance, specifically when one layer of the hierarchy included a feature-based agent for obstacle avoidance, and a standard RL agent for global navigation. In summary, the inclusion of a forgetting mechanism, and the use of a hierarchically structured RL agent offer substantially increased performance when compared to traditional RL agents navigating in a dynamic environment.

Control of free-flying space robot manipulator systems

NASA Technical Reports Server (NTRS)

Cannon, Robert H., Jr.

1988-01-01

The focus of the work is to develop and perform a set of research projects using laboratory models of satellite robots. These devices use air cushion technology to simulate in two dimensions the drag-free, zero-g conditions of space. Five research areas are examined: cooperative manipulation on a fixed base; cooperative manipulation on a free-floating base; global navigation and control of a free-floating robot; an alternative transport mode call Locomotion Enhancement via Arm Push-Off (LEAP), and adaptive control of LEAP.

Robotically assisted velocity-sensitive triggered focused ultrasound surgery

NASA Astrophysics Data System (ADS)

Maier, Florian; Brunner, Alexander; Jenne, Jürgen W.; Krafft, Axel J.; Semmler, Wolfhard; Bock, Michael

2012-11-01

Magnetic Resonance (MR) guided Focused Ultrasound Surgery (FUS) of abdominal organs is challenging due to breathing motion and limited patient access in the MR environment. In this work, an experimental robotically assisted FUS setup was combined with a MR-based navigator technique to realize motion-compensated sonications and online temperature imaging. Experiments were carried out in a static phantom, during periodic manual motion of the phantom without triggering, and with triggering to evaluate the triggering method. In contrast to the non-triggered sonication, the results of the triggered sonication show a confined symmetric temperature distribution. In conclusion, the velocity sensitive navigator can be employed for triggered FUS to compensate for periodic motion. Combined with the robotic FUS setup, flexible treatment of abdominal targets might be realized.

Visual identification and similarity measures used for on-line motion planning of autonomous robots in unknown environments

NASA Astrophysics Data System (ADS)

Martínez, Fredy; Martínez, Fernando; Jacinto, Edwar

2017-02-01

In this paper we propose an on-line motion planning strategy for autonomous robots in dynamic and locally observable environments. In this approach, we first visually identify geometric shapes in the environment by filtering images. Then, an ART-2 network is used to establish the similarity between patterns. The proposed algorithm allows that a robot establish its relative location in the environment, and define its navigation path based on images of the environment and its similarity to reference images. This is an efficient and minimalist method that uses the similarity of landmark view patterns to navigate to the desired destination. Laboratory tests on real prototypes demonstrate the performance of the algorithm.

Event-Based Control Strategy for Mobile Robots in Wireless Environments.

PubMed

Socas, Rafael; Dormido, Sebastián; Dormido, Raquel; Fabregas, Ernesto

2015-12-02

In this paper, a new event-based control strategy for mobile robots is presented. It has been designed to work in wireless environments where a centralized controller has to interchange information with the robots over an RF (radio frequency) interface. The event-based architectures have been developed for differential wheeled robots, although they can be applied to other kinds of robots in a simple way. The solution has been checked over classical navigation algorithms, like wall following and obstacle avoidance, using scenarios with a unique or multiple robots. A comparison between the proposed architectures and the classical discrete-time strategy is also carried out. The experimental results shows that the proposed solution has a higher efficiency in communication resource usage than the classical discrete-time strategy with the same accuracy.

Event-Based Control Strategy for Mobile Robots in Wireless Environments

PubMed Central

Socas, Rafael; Dormido, Sebastián; Dormido, Raquel; Fabregas, Ernesto

2015-01-01

In this paper, a new event-based control strategy for mobile robots is presented. It has been designed to work in wireless environments where a centralized controller has to interchange information with the robots over an RF (radio frequency) interface. The event-based architectures have been developed for differential wheeled robots, although they can be applied to other kinds of robots in a simple way. The solution has been checked over classical navigation algorithms, like wall following and obstacle avoidance, using scenarios with a unique or multiple robots. A comparison between the proposed architectures and the classical discrete-time strategy is also carried out. The experimental results shows that the proposed solution has a higher efficiency in communication resource usage than the classical discrete-time strategy with the same accuracy. PMID:26633412

Multidisciplinary approach for developing a new robotic system for domiciliary assistance to elderly people.

PubMed

Cavallo, F; Aquilano, M; Bonaccorsi, M; Mannari, I; Carrozza, M C; Dario, P

2011-01-01

This paper aims to show the effectiveness of a (inter / multi)disciplinary team, based on the technology developers, elderly care organizations, and designers, in developing the ASTRO robotic system for domiciliary assistance to elderly people. The main issues presented in this work concern the improvement of robot's behavior by means of a smart sensor network able to share information with the robot for localization and navigation, and the design of the robot's appearance and functionalities by means of a substantial analysis of users' requirements and attitude to robotic technology to improve acceptability and usability.

Autonomous mobile robot teams

NASA Technical Reports Server (NTRS)

Agah, Arvin; Bekey, George A.

1994-01-01

This paper describes autonomous mobile robot teams performing tasks in unstructured environments. The behavior and the intelligence of the group is distributed, and the system does not include a central command base or leader. The novel concept of the Tropism-Based Cognitive Architecture is introduced, which is used by the robots in order to produce behavior transforming their sensory information to proper action. The results of a number of simulation experiments are presented. These experiments include worlds where the robot teams must locate, decompose, and gather objects, and defend themselves against hostile predators, while navigating around stationary and mobile obstacles.

Technological evaluation of gesture and speech interfaces for enabling dismounted soldier-robot dialogue

NASA Astrophysics Data System (ADS)

Kattoju, Ravi Kiran; Barber, Daniel J.; Abich, Julian; Harris, Jonathan

2016-05-01

With increasing necessity for intuitive Soldier-robot communication in military operations and advancements in interactive technologies, autonomous robots have transitioned from assistance tools to functional and operational teammates able to service an array of military operations. Despite improvements in gesture and speech recognition technologies, their effectiveness in supporting Soldier-robot communication is still uncertain. The purpose of the present study was to evaluate the performance of gesture and speech interface technologies to facilitate Soldier-robot communication during a spatial-navigation task with an autonomous robot. Gesture and speech semantically based spatial-navigation commands leveraged existing lexicons for visual and verbal communication from the U.S Army field manual for visual signaling and a previously established Squad Level Vocabulary (SLV). Speech commands were recorded by a Lapel microphone and Microsoft Kinect, and classified by commercial off-the-shelf automatic speech recognition (ASR) software. Visual signals were captured and classified using a custom wireless gesture glove and software. Participants in the experiment commanded a robot to complete a simulated ISR mission in a scaled down urban scenario by delivering a sequence of gesture and speech commands, both individually and simultaneously, to the robot. Performance and reliability of gesture and speech hardware interfaces and recognition tools were analyzed and reported. Analysis of experimental results demonstrated the employed gesture technology has significant potential for enabling bidirectional Soldier-robot team dialogue based on the high classification accuracy and minimal training required to perform gesture commands.

Cognitive memory and mapping in a brain-like system for robotic navigation.

PubMed

Tang, Huajin; Huang, Weiwei; Narayanamoorthy, Aditya; Yan, Rui

2017-03-01

Electrophysiological studies in animals may provide a great insight into developing brain-like models of spatial cognition for robots. These studies suggest that the spatial ability of animals requires proper functioning of the hippocampus and the entorhinal cortex (EC). The involvement of the hippocampus in spatial cognition has been extensively studied, both in animal as well as in theoretical studies, such as in the brain-based models by Edelman and colleagues. In this work, we extend these earlier models, with a particular focus on the spatial coding properties of the EC and how it functions as an interface between the hippocampus and the neocortex, as proposed by previous work. By realizing the cognitive memory and mapping functions of the hippocampus and the EC, respectively, we develop a neurobiologically-inspired system to enable a mobile robot to perform task-based navigation in a maze environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Learning Probabilistic Features for Robotic Navigation Using Laser Sensors

PubMed Central

Aznar, Fidel; Pujol, Francisco A.; Pujol, Mar; Rizo, Ramón; Pujol, María-José

2014-01-01

SLAM is a popular task used by robots and autonomous vehicles to build a map of an unknown environment and, at the same time, to determine their location within the map. This paper describes a SLAM-based, probabilistic robotic system able to learn the essential features of different parts of its environment. Some previous SLAM implementations had computational complexities ranging from O(Nlog(N)) to O(N 2), where N is the number of map features. Unlike these methods, our approach reduces the computational complexity to O(N) by using a model to fuse the information from the sensors after applying the Bayesian paradigm. Once the training process is completed, the robot identifies and locates those areas that potentially match the sections that have been previously learned. After the training, the robot navigates and extracts a three-dimensional map of the environment using a single laser sensor. Thus, it perceives different sections of its world. In addition, in order to make our system able to be used in a low-cost robot, low-complexity algorithms that can be easily implemented on embedded processors or microcontrollers are used. PMID:25415377

Learning probabilistic features for robotic navigation using laser sensors.

PubMed

Aznar, Fidel; Pujol, Francisco A; Pujol, Mar; Rizo, Ramón; Pujol, María-José

2014-01-01

SLAM is a popular task used by robots and autonomous vehicles to build a map of an unknown environment and, at the same time, to determine their location within the map. This paper describes a SLAM-based, probabilistic robotic system able to learn the essential features of different parts of its environment. Some previous SLAM implementations had computational complexities ranging from O(Nlog(N)) to O(N(2)), where N is the number of map features. Unlike these methods, our approach reduces the computational complexity to O(N) by using a model to fuse the information from the sensors after applying the Bayesian paradigm. Once the training process is completed, the robot identifies and locates those areas that potentially match the sections that have been previously learned. After the training, the robot navigates and extracts a three-dimensional map of the environment using a single laser sensor. Thus, it perceives different sections of its world. In addition, in order to make our system able to be used in a low-cost robot, low-complexity algorithms that can be easily implemented on embedded processors or microcontrollers are used.

Design and implementation of magnetically maneuverable capsule endoscope system with direction reference for image navigation.

PubMed

Sun, Zhen-Jun; Ye, Bo; Sun, Yi; Zhang, Hong-Hai; Liu, Sheng

2014-07-01

This article describes a novel magnetically maneuverable capsule endoscope system with direction reference for image navigation. This direction reference was employed by utilizing a specific magnet configuration between a pair of external permanent magnets and a magnetic shell coated on the external capsule endoscope surface. A pair of customized Cartesian robots, each with only 4 degrees of freedom, was built to hold the external permanent magnets as their end-effectors. These robots, together with their external permanent magnets, were placed on two opposite sides of a "patient bed." Because of the optimized configuration based on magnetic analysis between the external permanent magnets and the magnetic shell, a simplified control strategy was proposed, and only two parameters, yaw step angle and moving step, were necessary for the employed robotic system. Step-by-step experiments demonstrated that the proposed system is capable of magnetically maneuvering the capsule endoscope while providing direction reference for image navigation. © IMechE 2014.

Determining Locations by Use of Networks of Passive Beacons

NASA Technical Reports Server (NTRS)

Okino, Clayton; Gray, Andrew; Jennings, Esther

2009-01-01

Networks of passive radio beacons spanning moderate-sized terrain areas have been proposed to aid navigation of small robotic aircraft that would be used to explore Saturn s moon Titan. Such networks could also be used on Earth to aid navigation of robotic aircraft, land vehicles, or vessels engaged in exploration or reconnaissance in situations or locations (e.g., underwater locations) in which Global Positioning System (GPS) signals are unreliable or unavailable. Prior to use, it would be necessary to pre-position the beacons at known locations that would be determined by use of one or more precise independent global navigation system(s). Thereafter, while navigating over the area spanned by a given network of passive beacons, an exploratory robot would use the beacons to determine its position precisely relative to the known beacon positions (see figure). If it were necessary for the robot to explore multiple, separated terrain areas spanned by different networks of beacons, the robot could use a long-haul, relatively coarse global navigation system for the lower-precision position determination needed during transit between such areas. The proposed method of precise determination of position of an exploratory robot relative to the positions of passive radio beacons is based partly on the principles of radar and partly on the principles of radio-frequency identification (RFID) tags. The robot would transmit radar-like signals that would be modified and reflected by the passive beacons. The distance to each beacon would be determined from the roundtrip propagation time and/or round-trip phase shift of the signal returning from that beacon. Signals returned from different beacons could be distinguished by means of their RFID characteristics. Alternatively or in addition, the antenna of each beacon could be designed to radiate in a unique pattern that could be identified by the navigation system. Also, alternatively or in addition, sets of identical beacons could be deployed in unique configurations such that the navigation system could identify their unique combinations of radio-frequency reflections as an alternative to leveraging the uniqueness of the RFID tags. The degree of dimensional accuracy would depend not only on the locations of the beacons but also on the number of beacon signals received, the number of samples of each signal, the motion of the robot, and the time intervals between samples. At one extreme, a single sample of the return signal from a single beacon could be used to determine the distance from that beacon and hence to determine that the robot is located somewhere on a sphere, the radius of which equals that distance and the center of which lies at the beacon. In a less extreme example, the three-dimensional position of the robot could be determined with fair precision from a single sample of the signal from each of three beacons. In intermediate cases, position estimates could be refined and/or position ambiguities could be resolved by use of supplementary readings of an altimeter and other instruments aboard the robot.

Calibration Of An Omnidirectional Vision Navigation System Using An Industrial Robot

NASA Astrophysics Data System (ADS)

Oh, Sung J.; Hall, Ernest L.

1989-09-01

The characteristics of an omnidirectional vision navigation system were studied to determine position accuracy for the navigation and path control of a mobile robot. Experiments for calibration and other parameters were performed using an industrial robot to conduct repetitive motions. The accuracy and repeatability of the experimental setup and the alignment between the robot and the sensor provided errors of less than 1 pixel on each axis. Linearity between zenith angle and image location was tested at four different locations. Angular error of less than 1° and radial error of less than 1 pixel were observed at moderate speed variations. The experimental information and the test of coordinated operation of the equipment provide understanding of characteristics as well as insight into the evaluation and improvement of the prototype dynamic omnivision system. The calibration of the sensor is important since the accuracy of navigation influences the accuracy of robot motion. This sensor system is currently being developed for a robot lawn mower; however, wider applications are obvious. The significance of this work is that it adds to the knowledge of the omnivision sensor.

Experiments on robot-assisted navigated drilling and milling of bones for pedicle screw placement.

PubMed

Ortmaier, T; Weiss, H; Döbele, S; Schreiber, U

2006-12-01

This article presents experimental results for robot-assisted navigated drilling and milling for pedicle screw placement. The preliminary study was carried out in order to gain first insights into positioning accuracies and machining forces during hands-on robotic spine surgery. Additionally, the results formed the basis for the development of a new robot for surgery. A simplified anatomical model is used to derive the accuracy requirements. The experimental set-up consists of a navigation system and an impedance-controlled light-weight robot holding the surgical instrument. The navigation system is used to position the surgical instrument and to compensate for pose errors during machining. Holes are drilled in artificial bone and bovine spine. A quantitative comparison of the drill-hole diameters was achieved using a computer. The interaction forces and pose errors are discussed with respect to the chosen machining technology and control parameters. Within the technological boundaries of the experimental set-up, it is shown that the accuracy requirements can be met and that milling is superior to drilling. It is expected that robot assisted navigated surgery helps to improve the reliability of surgical procedures. Further experiments are necessary to take the whole workflow into account. Copyright 2006 John Wiley & Sons, Ltd.

Navigating a Mobile Robot Across Terrain Using Fuzzy Logic

NASA Technical Reports Server (NTRS)

Seraji, Homayoun; Howard, Ayanna; Bon, Bruce

2003-01-01

A strategy for autonomous navigation of a robotic vehicle across hazardous terrain involves the use of a measure of traversability of terrain within a fuzzy-logic conceptual framework. This navigation strategy requires no a priori information about the environment. Fuzzy logic was selected as a basic element of this strategy because it provides a formal methodology for representing and implementing a human driver s heuristic knowledge and operational experience. Within a fuzzy-logic framework, the attributes of human reasoning and decision- making can be formulated by simple IF (antecedent), THEN (consequent) rules coupled with easily understandable and natural linguistic representations. The linguistic values in the rule antecedents convey the imprecision associated with measurements taken by sensors onboard a mobile robot, while the linguistic values in the rule consequents represent the vagueness inherent in the reasoning processes to generate the control actions. The operational strategies of the human expert driver can be transferred, via fuzzy logic, to a robot-navigation strategy in the form of a set of simple conditional statements composed of linguistic variables. These linguistic variables are defined by fuzzy sets in accordance with user-defined membership functions. The main advantages of a fuzzy navigation strategy lie in the ability to extract heuristic rules from human experience and to obviate the need for an analytical model of the robot navigation process.

Vision-based mobile robot navigation through deep convolutional neural networks and end-to-end learning

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

On Navigation Sensor Error Correction

NASA Astrophysics Data System (ADS)

Larin, V. B.

2016-01-01

The navigation problem for the simplest wheeled robotic vehicle is solved by just measuring kinematical parameters, doing without accelerometers and angular-rate sensors. It is supposed that the steerable-wheel angle sensor has a bias that must be corrected. The navigation parameters are corrected using the GPS. The approach proposed regards the wheeled robot as a system with nonholonomic constraints. The performance of such a navigation system is demonstrated by way of an example

From self-assessment to frustration, a small step toward autonomy in robotic navigation

PubMed Central

Jauffret, Adrien; Cuperlier, Nicolas; Tarroux, Philippe; Gaussier, Philippe

2013-01-01

Autonomy and self-improvement capabilities are still challenging in the fields of robotics and machine learning. Allowing a robot to autonomously navigate in wide and unknown environments not only requires a repertoire of robust strategies to cope with miscellaneous situations, but also needs mechanisms of self-assessment for guiding learning and for monitoring strategies. Monitoring strategies requires feedbacks on the behavior's quality, from a given fitness system in order to take correct decisions. In this work, we focus on how a second-order controller can be used to (1) manage behaviors according to the situation and (2) seek for human interactions to improve skills. Following an incremental and constructivist approach, we present a generic neural architecture, based on an on-line novelty detection algorithm that may be able to self-evaluate any sensory-motor strategies. This architecture learns contingencies between sensations and actions, giving the expected sensation from the previous perception. Prediction error, coming from surprising events, provides a measure of the quality of the underlying sensory-motor contingencies. We show how a simple second-order controller (emotional system) based on the prediction progress allows the system to regulate its behavior to solve complex navigation tasks and also succeeds in asking for help if it detects dead-lock situations. We propose that this model could be a key structure toward self-assessment and autonomy. We made several experiments that can account for such properties for two different strategies (road following and place cells based navigation) in different situations. PMID:24115931

A Fully Sensorized Cooperative Robotic System for Surgical Interventions

PubMed Central

Tovar-Arriaga, Saúl; Vargas, José Emilio; Ramos, Juan M.; Aceves, Marco A.; Gorrostieta, Efren; Kalender, Willi A.

2012-01-01

In this research a fully sensorized cooperative robot system for manipulation of needles is presented. The setup consists of a DLR/KUKA Light Weight Robot III especially designed for safe human/robot interaction, a FD-CT robot-driven angiographic C-arm system, and a navigation camera. Also, new control strategies for robot manipulation in the clinical environment are introduced. A method for fast calibration of the involved components and the preliminary accuracy tests of the whole possible errors chain are presented. Calibration of the robot with the navigation system has a residual error of 0.81 mm (rms) with a standard deviation of ±0.41 mm. The accuracy of the robotic system while targeting fixed points at different positions within the workspace is of 1.2 mm (rms) with a standard deviation of ±0.4 mm. After calibration, and due to close loop control, the absolute positioning accuracy was reduced to the navigation camera accuracy which is of 0.35 mm (rms). The implemented control allows the robot to compensate for small patient movements. PMID:23012551

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.

Thorough exploration of complex environments with a space-based potential field

NASA Astrophysics Data System (ADS)

Kenealy, Alina; Primiano, Nicholas; Keyes, Alex; Lyons, Damian M.

2015-01-01

Robotic exploration, for the purposes of search and rescue or explosive device detection, can be improved by using a team of multiple robots. Potential field navigation methods offer natural and efficient distributed exploration algorithms in which team members are mutually repelled to spread out and cover the area efficiently. However, they also suffer from field minima issues. Liu and Lyons proposed a Space-Based Potential Field (SBPF) algorithm that disperses robots efficiently and also ensures they are driven in a distributed fashion to cover complex geometry. In this paper, the approach is modified to handle two problems with the original SBPF method: fast exploration of enclosed spaces, and fast navigation of convex obstacles. Firstly, a "gate-sensing" function was implemented. The function draws the robot to narrow openings, such as doors or corridors that it might otherwise pass by, to ensure every room can be explored. Secondly, an improved obstacle field conveyor belt function was developed which allows the robot to avoid walls and barriers while using their surface as a motion guide to avoid being trapped. Simulation results, where the modified SPBF program controls the MobileSim Pioneer 3-AT simulator program, are presented for a selection of maps that capture difficult to explore geometries. Physical robot results are also presented, where a team of Pioneer 3-AT robots is controlled by the modified SBPF program. Data collected prior to the improvements, new simulation results, and robot experiments are presented as evidence of performance improvements.

ODYSSEUS autonomous walking robot: The leg/arm design

NASA Technical Reports Server (NTRS)

Bourbakis, N. G.; Maas, M.; Tascillo, A.; Vandewinckel, C.

1994-01-01

ODYSSEUS is an autonomous walking robot, which makes use of three wheels and three legs for its movement in the free navigation space. More specifically, it makes use of its autonomous wheels to move around in an environment where the surface is smooth and not uneven. However, in the case that there are small height obstacles, stairs, or small height unevenness in the navigation environment, the robot makes use of both wheels and legs to travel efficiently. In this paper we present the detailed hardware design and the simulated behavior of the extended leg/arm part of the robot, since it plays a very significant role in the robot actions (movements, selection of objects, etc.). In particular, the leg/arm consists of three major parts: The first part is a pipe attached to the robot base with a flexible 3-D joint. This pipe has a rotated bar as an extended part, which terminates in a 3-D flexible joint. The second part of the leg/arm is also a pipe similar to the first. The extended bar of the second part ends at a 2-D joint. The last part of the leg/arm is a clip-hand. It is used for selecting several small weight and size objects, and when it is in a 'closed' mode, it is used as a supporting part of the robot leg. The entire leg/arm part is controlled and synchronized by a microcontroller (68CH11) attached to the robot base.

Development of autonomous grasping and navigating robot

NASA Astrophysics Data System (ADS)

Kudoh, Hiroyuki; Fujimoto, Keisuke; Nakayama, Yasuichi

2015-01-01

The ability to find and grasp target items in an unknown environment is important for working robots. We developed an autonomous navigating and grasping robot. The operations are locating a requested item, moving to where the item is placed, finding the item on a shelf or table, and picking the item up from the shelf or the table. To achieve these operations, we designed the robot with three functions: an autonomous navigating function that generates a map and a route in an unknown environment, an item position recognizing function, and a grasping function. We tested this robot in an unknown environment. It achieved a series of operations: moving to a destination, recognizing the positions of items on a shelf, picking up an item, placing it on a cart with its hand, and returning to the starting location. The results of this experiment show the applicability of reducing the workforce with robots.

Autonomous Navigation by a Mobile Robot

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance; Aghazarian, Hrand

2005-01-01

ROAMAN is a computer program for autonomous navigation of a mobile robot on a long (as much as hundreds of meters) traversal of terrain. Developed for use aboard a robotic vehicle (rover) exploring the surface of a remote planet, ROAMAN could also be adapted to similar use on terrestrial mobile robots. ROAMAN implements a combination of algorithms for (1) long-range path planning based on images acquired by mast-mounted, wide-baseline stereoscopic cameras, and (2) local path planning based on images acquired by body-mounted, narrow-baseline stereoscopic cameras. The long-range path-planning algorithm autonomously generates a series of waypoints that are passed to the local path-planning algorithm, which plans obstacle-avoiding legs between the waypoints. Both the long- and short-range algorithms use an occupancy-grid representation in computations to detect obstacles and plan paths. Maps that are maintained by the long- and short-range portions of the software are not shared because substantial localization errors can accumulate during any long traverse. ROAMAN is not guaranteed to generate an optimal shortest path, but does maintain the safety of the rover.

Insect-Inspired Optical-Flow Navigation Sensors

NASA Technical Reports Server (NTRS)

Thakoor, Sarita; Morookian, John M.; Chahl, Javan; Soccol, Dean; Hines, Butler; Zornetzer, Steven

2005-01-01

Integrated circuits that exploit optical flow to sense motions of computer mice on or near surfaces ( optical mouse chips ) are used as navigation sensors in a class of small flying robots now undergoing development for potential use in such applications as exploration, search, and surveillance. The basic principles of these robots were described briefly in Insect-Inspired Flight Control for Small Flying Robots (NPO-30545), NASA Tech Briefs, Vol. 29, No. 1 (January 2005), page 61. To recapitulate from the cited prior article: The concept of optical flow can be defined, loosely, as the use of texture in images as a source of motion cues. The flight-control and navigation systems of these robots are inspired largely by the designs and functions of the vision systems and brains of insects, which have been demonstrated to utilize optical flow (as detected by their eyes and brains) resulting from their own motions in the environment. Optical flow has been shown to be very effective as a means of avoiding obstacles and controlling speeds and altitudes in robotic navigation. Prior systems used in experiments on navigating by means of optical flow have involved the use of panoramic optics, high-resolution image sensors, and programmable imagedata- processing computers.

The navigation system of the JPL robot

NASA Technical Reports Server (NTRS)

Thompson, A. M.

1977-01-01

The control structure of the JPL research robot and the operations of the navigation subsystem are discussed. The robot functions as a network of interacting concurrent processes distributed among several computers and coordinated by a central executive. The results of scene analysis are used to create a segmented terrain model in which surface regions are classified by traversibility. The model is used by a path planning algorithm, PATH, which uses tree search methods to find the optimal path to a goal. In PATH, the search space is defined dynamically as a consequence of node testing. Maze-solving and the use of an associative data base for context dependent node generation are also discussed. Execution of a planned path is accomplished by a feedback guidance process with automatic error recovery.

Experiments in teleoperator and autonomous control of space robotic vehicles

NASA Technical Reports Server (NTRS)

Alexander, Harold L.

1991-01-01

A program of research embracing teleoperator and automatic navigational control of freely flying satellite robots is presented. Current research goals include: (1) developing visual operator interfaces for improved vehicle teleoperation; (2) determining the effects of different visual interface system designs on operator performance; and (3) achieving autonomous vision-based vehicle navigation and control. This research program combines virtual-environment teleoperation studies and neutral-buoyancy experiments using a space-robot simulator vehicle currently under development. Visual-interface design options under investigation include monoscopic versus stereoscopic displays and cameras, helmet-mounted versus panel-mounted display monitors, head-tracking versus fixed or manually steerable remote cameras, and the provision of vehicle-fixed visual cues, or markers, in the remote scene for improved sensing of vehicle position, orientation, and motion.

Automatic Operation For A Robot Lawn Mower

NASA Astrophysics Data System (ADS)

Huang, Y. Y.; Cao, Z. L.; Oh, S. J.; Kattan, E. U.; Hall, E. L.

1987-02-01

A domestic mobile robot, lawn mower, which performs the automatic operation mode, has been built up in the Center of Robotics Research, University of Cincinnati. The robot lawn mower automatically completes its work with the region filling operation, a new kind of path planning for mobile robots. Some strategies for region filling of path planning have been developed for a partly-known or a unknown environment. Also, an advanced omnidirectional navigation system and a multisensor-based control system are used in the automatic operation. Research on the robot lawn mower, especially on the region filling of path planning, is significant in industrial and agricultural applications.

Kinematic analysis and simulation of a substation inspection robot guided by magnetic sensor

NASA Astrophysics Data System (ADS)

Xiao, Peng; Luan, Yiqing; Wang, Haipeng; Li, Li; Li, Jianxiang

2017-01-01

In order to improve the performance of the magnetic navigation system used by substation inspection robot, the kinematic characteristics is analyzed based on a simplified magnetic guiding system model, and then the simulation process is executed to verify the reasonability of the whole analysis procedure. Finally, some suggestions are extracted out, which will be helpful to guide the design of the inspection robot system in the future.

Experiments in autonomous robotics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamel, W.R.

1987-01-01

The Center for Engineering Systems Advanced Research (CESAR) is performing basic research in autonomous robotics for energy-related applications in hazardous environments. The CESAR research agenda includes a strong experimental component to assure practical evaluation of new concepts and theories. An evolutionary sequence of mobile research robots has been planned to support research in robot navigation, world sensing, and object manipulation. A number of experiments have been performed in studying robot navigation and path planning with planar sonar sensing. Future experiments will address more complex tasks involving three-dimensional sensing, dexterous manipulation, and human-scale operations.

Enhancing fuzzy robot navigation systems by mimicking human visual perception of natural terrain traversibility

NASA Technical Reports Server (NTRS)

Tunstel, E.; Howard, A.; Edwards, D.; Carlson, A.

2001-01-01

This paper presents a technique for learning to assess terrain traversability for outdoor mobile robot navigation using human-embedded logic and real-time perception of terrain features extracted from image data.

Mobile robots traversability awareness based on terrain visual sensory data fusion

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir

2007-04-01

In this paper, we have presented methods that significantly improve the robot awareness of its terrain traversability conditions. The terrain traversability awareness is achieved by association of terrain image appearances from different poses and fusion of extracted information from multimodality imaging and range sensor data for localization and clustering environment landmarks. Initially, we describe methods for extraction of salient features of the terrain for the purpose of landmarks registration from two or more images taken from different via points along the trajectory path of the robot. The method of image registration is applied as a means of overlaying (two or more) of the same terrain scene at different viewpoints. The registration geometrically aligns salient landmarks of two images (the reference and sensed images). A Similarity matching techniques is proposed for matching the terrain salient landmarks. Secondly, we present three terrain classifier models based on rule-based, supervised neural network, and fuzzy logic for classification of terrain condition under uncertainty and mapping the robot's terrain perception to apt traversability measures. This paper addresses the technical challenges and navigational skill requirements of mobile robots for traversability path planning in natural terrain environments similar to Mars surface terrains. We have described different methods for detection of salient terrain features based on imaging texture analysis techniques. We have also presented three competing techniques for terrain traversability assessment of mobile robots navigating in unstructured natural terrain environments. These three techniques include: a rule-based terrain classifier, a neural network-based terrain classifier, and a fuzzy-logic terrain classifier. Each proposed terrain classifier divides a region of natural terrain into finite sub-terrain regions and classifies terrain condition exclusively within each sub-terrain region based on terrain spatial and textural cues.

Modular Countermine Payload for Small Robots

DOE Office of Scientific and Technical Information (OSTI.GOV)

Herman Herman; Doug Few; Roelof Versteeg

2010-04-01

Payloads for small robotic platforms have historically been designed and implemented as platform and task specific solutions. A consequence of this approach is that payloads cannot be deployed on different robotic platforms without substantial re-engineering efforts. To address this issue, we developed a modular countermine payload that is designed from the ground-up to be platform agnostic. The payload consists of the multi-mission payload controller unit (PCU) coupled with the configurable mission specific threat detection, navigation and marking payloads. The multi-mission PCU has all the common electronics to control and interface to all the payloads. It also contains the embedded processormore » that can be used to run the navigational and control software. The PCU has a very flexible robot interface which can be configured to interface to various robot platforms. The threat detection payload consists of a two axis sweeping arm and the detector. The navigation payload consists of several perception sensors that are used for terrain mapping, obstacle detection and navigation. Finally, the marking payload consists of a dual-color paint marking system. Through the multi-mission PCU, all these payloads are packaged in a platform agnostic way to allow deployment on multiple robotic platforms, including Talon and Packbot.« less

Modular countermine payload for small robots

NASA Astrophysics Data System (ADS)

Herman, Herman; Few, Doug; Versteeg, Roelof; Valois, Jean-Sebastien; McMahill, Jeff; Licitra, Michael; Henciak, Edward

2010-04-01

Payloads for small robotic platforms have historically been designed and implemented as platform and task specific solutions. A consequence of this approach is that payloads cannot be deployed on different robotic platforms without substantial re-engineering efforts. To address this issue, we developed a modular countermine payload that is designed from the ground-up to be platform agnostic. The payload consists of the multi-mission payload controller unit (PCU) coupled with the configurable mission specific threat detection, navigation and marking payloads. The multi-mission PCU has all the common electronics to control and interface to all the payloads. It also contains the embedded processor that can be used to run the navigational and control software. The PCU has a very flexible robot interface which can be configured to interface to various robot platforms. The threat detection payload consists of a two axis sweeping arm and the detector. The navigation payload consists of several perception sensors that are used for terrain mapping, obstacle detection and navigation. Finally, the marking payload consists of a dual-color paint marking system. Through the multimission PCU, all these payloads are packaged in a platform agnostic way to allow deployment on multiple robotic platforms, including Talon and Packbot.

Electromagnetic navigational bronchoscopy and robotic-assisted thoracic surgery.

PubMed

Christie, Sara

2014-06-01

With the use of electromagnetic navigational bronchoscopy and robotics, lung lesions can be diagnosed and resected during one surgical procedure. Global positioning system technology allows surgeons to identify and mark a thoracic tumor, and then robotics technology allows them to perform minimally invasive resection and cancer staging procedures. Nurses on the perioperative robotics team must consider the logistics of providing safe and competent care when performing combined procedures during one surgical encounter. Instrumentation, OR organization and room setup, and patient positioning are important factors to consider to complete the procedure systematically and efficiently. This revolutionary concept of combining navigational bronchoscopy with robotics requires a team of dedicated nurses to facilitate the sequence of events essential for providing optimal patient outcomes in highly advanced surgical procedures. Copyright © 2014 AORN, Inc. Published by Elsevier Inc. All rights reserved.

Low computation vision-based navigation for a Martian rover

NASA Technical Reports Server (NTRS)

Gavin, Andrew S.; Brooks, Rodney A.

1994-01-01

Construction and design details of the Mobot Vision System, a small, self-contained, mobile vision system, are presented. This system uses the view from the top of a small, roving, robotic vehicle to supply data that is processed in real-time to safely navigate the surface of Mars. A simple, low-computation algorithm for constructing a 3-D navigational map of the Martian environment to be used by the rover is discussed.

Embodied cognition for autonomous interactive robots.

PubMed

Hoffman, Guy

2012-10-01

In the past, notions of embodiment have been applied to robotics mainly in the realm of very simple robots, and supporting low-level mechanisms such as dynamics and navigation. In contrast, most human-like, interactive, and socially adept robotic systems turn away from embodiment and use amodal, symbolic, and modular approaches to cognition and interaction. At the same time, recent research in Embodied Cognition (EC) is spanning an increasing number of complex cognitive processes, including language, nonverbal communication, learning, and social behavior. This article suggests adopting a modern EC approach for autonomous robots interacting with humans. In particular, we present three core principles from EC that may be applicable to such robots: (a) modal perceptual representation, (b) action/perception and action/cognition integration, and (c) a simulation-based model of top-down perceptual biasing. We describe a computational framework based on these principles, and its implementation on two physical robots. This could provide a new paradigm for embodied human-robot interaction based on recent psychological and neurological findings. Copyright © 2012 Cognitive Science Society, Inc.

Embedded mobile farm robot for identification of diseased plants

NASA Astrophysics Data System (ADS)

Sadistap, S. S.; Botre, B. A.; Pandit, Harshavardhan; Chandrasekhar; Rao, Adesh

2013-07-01

This paper presents the development of a mobile robot used in farms for identification of diseased plants. It puts forth two of the major aspects of robotics namely automated navigation and image processing. The robot navigates on the basis of the GPS (Global Positioning System) location and data obtained from IR (Infrared) sensors to avoid any obstacles in its path. It uses an image processing algorithm to differentiate between diseased and non-diseased plants. A robotic platform consisting of an ARM9 processor, motor drivers, robot mechanical assembly, camera and infrared sensors has been used. Mini2440 microcontroller has been used wherein Embedded linux OS (Operating System) is implemented.

Evolving earth-based and in-situ satellite network architectures for Mars communications and navigation support

NASA Technical Reports Server (NTRS)

Hastrup, Rolf; Weinberg, Aaron; Mcomber, Robert

1991-01-01

Results of on-going studies to develop navigation/telecommunications network concepts to support future robotic and human missions to Mars are presented. The performance and connectivity improvements provided by the relay network will permit use of simpler, lower performance, and less costly telecom subsystems for the in-situ mission exploration elements. Orbiting relay satellites can serve as effective navigation aids by supporting earth-based tracking as well as providing Mars-centered radiometric data for mission elements approaching, in orbit, or on the surface of Mars. The relay satellite orbits may be selected to optimize navigation aid support and communication coverage for specific mission sets.

Evolving earth-based and in-situ satellite network architectures for Mars communications and navigation support

NASA Astrophysics Data System (ADS)

Hastrup, Rolf; Weinberg, Aaron; McOmber, Robert

1991-09-01

Results of on-going studies to develop navigation/telecommunications network concepts to support future robotic and human missions to Mars are presented. The performance and connectivity improvements provided by the relay network will permit use of simpler, lower performance, and less costly telecom subsystems for the in-situ mission exploration elements. Orbiting relay satellites can serve as effective navigation aids by supporting earth-based tracking as well as providing Mars-centered radiometric data for mission elements approaching, in orbit, or on the surface of Mars. The relay satellite orbits may be selected to optimize navigation aid support and communication coverage for specific mission sets.

UAV-guided navigation for ground robot tele-operation in a military reconnaissance environment.

PubMed

Chen, Jessie Y C

2010-08-01

A military reconnaissance environment was simulated to examine the performance of ground robotics operators who were instructed to utilise streaming video from an unmanned aerial vehicle (UAV) to navigate his/her ground robot to the locations of the targets. The effects of participants' spatial ability on their performance and workload were also investigated. Results showed that participants' overall performance (speed and accuracy) was better when she/he had access to images from larger UAVs with fixed orientations, compared with other UAV conditions (baseline- no UAV, micro air vehicle and UAV with orbiting views). Participants experienced the highest workload when the UAV was orbiting. Those individuals with higher spatial ability performed significantly better and reported less workload than those with lower spatial ability. The results of the current study will further understanding of ground robot operators' target search performance based on streaming video from UAVs. The results will also facilitate the implementation of ground/air robots in military environments and will be useful to the future military system design and training community.

Vision-Based Real-Time Traversable Region Detection for Mobile Robot in the Outdoors.

PubMed

Deng, Fucheng; Zhu, Xiaorui; He, Chao

2017-09-13

Environment perception is essential for autonomous mobile robots in human-robot coexisting outdoor environments. One of the important tasks for such intelligent robots is to autonomously detect the traversable region in an unstructured 3D real world. The main drawback of most existing methods is that of high computational complexity. Hence, this paper proposes a binocular vision-based, real-time solution for detecting traversable region in the outdoors. In the proposed method, an appearance model based on multivariate Gaussian is quickly constructed from a sample region in the left image adaptively determined by the vanishing point and dominant borders. Then, a fast, self-supervised segmentation scheme is proposed to classify the traversable and non-traversable regions. The proposed method is evaluated on public datasets as well as a real mobile robot. Implementation on the mobile robot has shown its ability in the real-time navigation applications.

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.

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.

Adaptive Tracking Control for Robots With an Interneural Computing Scheme.

PubMed

Tsai, Feng-Sheng; Hsu, Sheng-Yi; Shih, Mau-Hsiang

2018-04-01

Adaptive tracking control of mobile robots requires the ability to follow a trajectory generated by a moving target. The conventional analysis of adaptive tracking uses energy minimization to study the convergence and robustness of the tracking error when the mobile robot follows a desired trajectory. However, in the case that the moving target generates trajectories with uncertainties, a common Lyapunov-like function for energy minimization may be extremely difficult to determine. Here, to solve the adaptive tracking problem with uncertainties, we wish to implement an interneural computing scheme in the design of a mobile robot for behavior-based navigation. The behavior-based navigation adopts an adaptive plan of behavior patterns learning from the uncertainties of the environment. The characteristic feature of the interneural computing scheme is the use of neural path pruning with rewards and punishment interacting with the environment. On this basis, the mobile robot can be exploited to change its coupling weights in paths of neural connections systematically, which can then inhibit or enhance the effect of flow elimination in the dynamics of the evolutionary neural network. Such dynamical flow translation ultimately leads to robust sensory-to-motor transformations adapting to the uncertainties of the environment. A simulation result shows that the mobile robot with the interneural computing scheme can perform fault-tolerant behavior of tracking by maintaining suitable behavior patterns at high frequency levels.

Robotic digital subtraction angiography systems within the hybrid operating room.

PubMed

Murayama, Yuichi; Irie, Koreaki; Saguchi, Takayuki; Ishibashi, Toshihiro; Ebara, Masaki; Nagashima, Hiroyasu; Isoshima, Akira; Arakawa, Hideki; Takao, Hiroyuki; Ohashi, Hiroki; Joki, Tatsuhiro; Kato, Masataka; Tani, Satoshi; Ikeuchi, Satoshi; Abe, Toshiaki

2011-05-01

Fully equipped high-end digital subtraction angiography (DSA) within the operating room (OR) environment has emerged as a new trend in the fields of neurosurgery and vascular surgery. To describe initial clinical experience with a robotic DSA system in the hybrid OR. A newly designed robotic DSA system (Artis zeego; Siemens AG, Forchheim, Germany) was installed in the hybrid OR. The system consists of a multiaxis robotic C arm and surgical OR table. In addition to conventional neuroendovascular procedures, the system was used as an intraoperative imaging tool for various neurosurgical procedures such as aneurysm clipping and spine instrumentation. Five hundred one neurosurgical procedures were successfully conducted in the hybrid OR with the robotic DSA. During surgical procedures such as aneurysm clipping and arteriovenous fistula treatment, intraoperative 2-/3-dimensional angiography and C-arm-based computed tomographic images (DynaCT) were easily performed without moving the OR table. Newly developed virtual navigation software (syngo iGuide; Siemens AG) can be used in frameless navigation and in access to deep-seated intracranial lesions or needle placement. This newly developed robotic DSA system provides safe and precise treatment in the fields of endovascular treatment and neurosurgery.

New Control Paradigms for Resources Saving: An Approach for Mobile Robots Navigation.

PubMed

Socas, Rafael; Dormido, Raquel; Dormido, Sebastián

2018-01-18

In this work, an event-based control scheme is presented. The proposed system has been developed to solve control problems appearing in the field of Networked Control Systems (NCS). Several models and methodologies have been proposed to measure different resources consumptions. The use of bandwidth, computational load and energy resources have been investigated. This analysis shows how the parameters of the system impacts on the resources efficiency. Moreover, the proposed system has been compared with its equivalent discrete-time solution. In the experiments, an application of NCS for mobile robots navigation has been set up and its resource usage efficiency has been analysed.

New Control Paradigms for Resources Saving: An Approach for Mobile Robots Navigation

PubMed Central

2018-01-01

In this work, an event-based control scheme is presented. The proposed system has been developed to solve control problems appearing in the field of Networked Control Systems (NCS). Several models and methodologies have been proposed to measure different resources consumptions. The use of bandwidth, computational load and energy resources have been investigated. This analysis shows how the parameters of the system impacts on the resources efficiency. Moreover, the proposed system has been compared with its equivalent discrete-time solution. In the experiments, an application of NCS for mobile robots navigation has been set up and its resource usage efficiency has been analysed. PMID:29346321

Visual homing with a pan-tilt based stereo camera

NASA Astrophysics Data System (ADS)

Nirmal, Paramesh; Lyons, Damian M.

2013-01-01

Visual homing is a navigation method based on comparing a stored image of the goal location and the current image (current view) to determine how to navigate to the goal location. It is theorized that insects, such as ants and bees, employ visual homing methods to return to their nest. Visual homing has been applied to autonomous robot platforms using two main approaches: holistic and feature-based. Both methods aim at determining distance and direction to the goal location. Navigational algorithms using Scale Invariant Feature Transforms (SIFT) have gained great popularity in the recent years due to the robustness of the feature operator. Churchill and Vardy have developed a visual homing method using scale change information (Homing in Scale Space, HiSS) from SIFT. HiSS uses SIFT feature scale change information to determine distance between the robot and the goal location. Since the scale component is discrete with a small range of values, the result is a rough measurement with limited accuracy. We have developed a method that uses stereo data, resulting in better homing performance. Our approach utilizes a pan-tilt based stereo camera, which is used to build composite wide-field images. We use the wide-field images combined with stereo-data obtained from the stereo camera to extend the keypoint vector described in to include a new parameter, depth (z). Using this info, our algorithm determines the distance and orientation from the robot to the goal location. We compare our method with HiSS in a set of indoor trials using a Pioneer 3-AT robot equipped with a BumbleBee2 stereo camera. We evaluate the performance of both methods using a set of performance measures described in this paper.

Google glass-based remote control of a mobile robot

NASA Astrophysics Data System (ADS)

Yu, Song; Wen, Xi; Li, Wei; Chen, Genshe

2016-05-01

In this paper, we present an approach to remote control of a mobile robot via a Google Glass with the multi-function and compact size. This wearable device provides a new human-machine interface (HMI) to control a robot without need for a regular computer monitor because the Google Glass micro projector is able to display live videos around robot environments. In doing it, we first develop a protocol to establish WI-FI connection between Google Glass and a robot and then implement five types of robot behaviors: Moving Forward, Turning Left, Turning Right, Taking Pause, and Moving Backward, which are controlled by sliding and clicking the touchpad located on the right side of the temple. In order to demonstrate the effectiveness of the proposed Google Glass-based remote control system, we navigate a virtual Surveyor robot to pass a maze. Experimental results demonstrate that the proposed control system achieves the desired performance.

Navigation system for robot-assisted intra-articular lower-limb fracture surgery.

PubMed

Dagnino, Giulio; Georgilas, Ioannis; Köhler, Paul; Morad, Samir; Atkins, Roger; Dogramadzi, Sanja

2016-10-01

In the surgical treatment for lower-leg intra-articular fractures, the fragments have to be positioned and aligned to reconstruct the fractured bone as precisely as possible, to allow the joint to function correctly again. Standard procedures use 2D radiographs to estimate the desired reduction position of bone fragments. However, optimal correction in a 3D space requires 3D imaging. This paper introduces a new navigation system that uses pre-operative planning based on 3D CT data and intra-operative 3D guidance to virtually reduce lower-limb intra-articular fractures. Physical reduction in the fractures is then performed by our robotic system based on the virtual reduction. 3D models of bone fragments are segmented from CT scan. Fragments are pre-operatively visualized on the screen and virtually manipulated by the surgeon through a dedicated GUI to achieve the virtual reduction in the fracture. Intra-operatively, the actual position of the bone fragments is provided by an optical tracker enabling real-time 3D guidance. The motion commands for the robot connected to the bone fragment are generated, and the fracture physically reduced based on the surgeon's virtual reduction. To test the system, four femur models were fractured to obtain four different distal femur fracture types. Each one of them was subsequently reduced 20 times by a surgeon using our system. The navigation system allowed an orthopaedic surgeon to virtually reduce the fracture with a maximum residual positioning error of [Formula: see text] (translational) and [Formula: see text] (rotational). Correspondent physical reductions resulted in an accuracy of 1.03 ± 0.2 mm and [Formula: see text], when the robot reduced the fracture. Experimental outcome demonstrates the accuracy and effectiveness of the proposed navigation system, presenting a fracture reduction accuracy of about 1 mm and [Formula: see text], and meeting the clinical requirements for distal femur fracture reduction procedures.

A development of intelligent entertainment robot for home life

NASA Astrophysics Data System (ADS)

Kim, Cheoltaek; Lee, Ju-Jang

2005-12-01

The purpose of this paper was to present the study and design idea for entertainment robot with educational purpose (IRFEE). The robot has been designed for home life considering dependability and interaction. The developed robot has three objectives - 1. Develop autonomous robot, 2. Design robot considering mobility and robustness, 3. Develop robot interface and software considering entertainment and education functionalities. The autonomous navigation was implemented by active vision based SLAM and modified EPF algorithm. The two differential wheels, the pan-tilt were designed mobility and robustness and the exterior was designed considering esthetic element and minimizing interference. The speech and tracking algorithm provided the good interface with human. The image transfer and Internet site connection is needed for service of remote connection and educational purpose.

A Concise Guide to Feature Histograms with Applications to LIDAR-Based Spacecraft Relative Navigation

NASA Astrophysics Data System (ADS)

Rhodes, Andrew P.; Christian, John A.; Evans, Thomas

2017-12-01

With the availability and popularity of 3D sensors, it is advantageous to re-examine the use of point cloud descriptors for the purpose of pose estimation and spacecraft relative navigation. One popular descriptor is the oriented unique repeatable clustered viewpoint feature histogram (OUR-CVFH), which is most often utilized in personal and industrial robotics to simultaneously recognize and navigate relative to an object. Recent research into using the OUR-CVFH descriptor for spacecraft navigation has produced favorable results. Since OUR-CVFH is the most recent innovation in a large family of feature histogram point cloud descriptors, discussions of parameter settings and insights into its functionality are spread among various publications and online resources. This paper organizes the history of feature histogram point cloud descriptors for a straightforward explanation of their evolution. This article compiles all the requisite information needed to implement OUR-CVFH into one location, as well as providing useful suggestions on how to tune the generation parameters. This work is beneficial for anyone interested in using this histogram descriptor for object recognition or navigation - may it be personal robotics or spacecraft navigation.

Navigable points estimation for mobile robots using binary image skeletonization

NASA Astrophysics Data System (ADS)

Martinez S., Fernando; Jacinto G., Edwar; Montiel A., Holman

2017-02-01

This paper describes the use of image skeletonization for the estimation of all the navigable points, inside a scene of mobile robots navigation. Those points are used for computing a valid navigation path, using standard methods. The main idea is to find the middle and the extreme points of the obstacles in the scene, taking into account the robot size, and create a map of navigable points, in order to reduce the amount of information for the planning algorithm. Those points are located by means of the skeletonization of a binary image of the obstacles and the scene background, along with some other digital image processing algorithms. The proposed algorithm automatically gives a variable number of navigable points per obstacle, depending on the complexity of its shape. As well as, the way how the algorithm can change some of their parameters in order to change the final number of the resultant key points is shown. The results shown here were obtained applying different kinds of digital image processing algorithms on static scenes.

Immune systems are not just for making you feel better: they are for controlling autonomous robots

NASA Astrophysics Data System (ADS)

Rosenblum, Mark

2005-05-01

The typical algorithm for robot autonomous navigation in off-road complex environments involves building a 3D map of the robot's surrounding environment using a 3D sensing modality such as stereo vision or active laser scanning, and generating an instantaneous plan to navigate around hazards. Although there has been steady progress using these methods, these systems suffer from several limitations that cannot be overcome with 3D sensing and planning alone. Geometric sensing alone has no ability to distinguish between compressible and non-compressible materials. As a result, these systems have difficulty in heavily vegetated environments and require sensitivity adjustments across different terrain types. On the planning side, these systems have no ability to learn from their mistakes and avoid problematic environmental situations on subsequent encounters. We have implemented an adaptive terrain classification system based on the Artificial Immune System (AIS) computational model, which is loosely based on the biological immune system, that combines various forms of imaging sensor inputs to produce a "feature labeled" image of the scene categorizing areas as benign or detrimental for autonomous robot navigation. Because of the qualities of the AIS computation model, the resulting system will be able to learn and adapt on its own through interaction with the environment by modifying its interpretation of the sensor data. The feature labeled results from the AIS analysis are inserted into a map and can then be used by a planner to generate a safe route to a goal point. The coupling of diverse visual cues with the malleable AIS computational model will lead to autonomous robotic ground vehicles that require less human intervention for deployment in novel environments and more robust operation as a result of the system's ability to improve its performance through interaction with the environment.

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.

The Design and Implementation of a Semi-Autonomous Surf-Zone Robot Using Advanced Sensors and a Common Robot Operating System

DTIC Science & Technology

2011-06-01

effective way- point navigation algorithm that interfaced with a Java based graphical user interface (GUI), written by Uzun, for a robot named Bender [2...the angular acceleration, θ̈, or angular rate, θ̇. When considering a joint driven by an electric motor, the inertia and friction can be divided into...interactive simulations that can receive input from user controls, scripts , and other applications, such as Excel and MATLAB. One drawback is that the

Autonomous Navigation, Dynamic Path and Work Flow Planning in Multi-Agent Robotic Swarms Project

NASA Technical Reports Server (NTRS)

Falker, John; Zeitlin, Nancy; Leucht, Kurt; Stolleis, Karl

2015-01-01

Kennedy Space Center has teamed up with the Biological Computation Lab at the University of New Mexico to create a swarm of small, low-cost, autonomous robots, called Swarmies, to be used as a ground-based research platform for in-situ resource utilization missions. The behavior of the robot swarm mimics the central-place foraging strategy of ants to find and collect resources in an unknown environment and return those resources to a central site.

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.

Behavior coordination of mobile robotics using supervisory control of fuzzy discrete event systems.

PubMed

Jayasiri, Awantha; Mann, George K I; Gosine, Raymond G

2011-10-01

In order to incorporate the uncertainty and impreciseness present in real-world event-driven asynchronous systems, fuzzy discrete event systems (DESs) (FDESs) have been proposed as an extension to crisp DESs. In this paper, first, we propose an extension to the supervisory control theory of FDES by redefining fuzzy controllable and uncontrollable events. The proposed supervisor is capable of enabling feasible uncontrollable and controllable events with different possibilities. Then, the extended supervisory control framework of FDES is employed to model and control several navigational tasks of a mobile robot using the behavior-based approach. The robot has limited sensory capabilities, and the navigations have been performed in several unmodeled environments. The reactive and deliberative behaviors of the mobile robotic system are weighted through fuzzy uncontrollable and controllable events, respectively. By employing the proposed supervisory controller, a command-fusion-type behavior coordination is achieved. The observability of fuzzy events is incorporated to represent the sensory imprecision. As a systematic analysis of the system, a fuzzy-state-based controllability measure is introduced. The approach is implemented in both simulation and real time. A performance evaluation is performed to quantitatively estimate the validity of the proposed approach over its counterparts.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rao, N.S.V.; Kareti, S.; Shi, Weimin

A formal framework for navigating a robot in a geometric terrain by an unknown set of obstacles is considered. Here the terrain model is not a priori known, but the robot is equipped with a sensor system (vision or touch) employed for the purpose of navigation. The focus is restricted to the non-heuristic algorithms which can be theoretically shown to be correct within a given framework of models for the robot, terrain and sensor system. These formulations, although abstract and simplified compared to real-life scenarios, provide foundations for practical systems by highlighting the underlying critical issues. First, the authors considermore » the algorithms that are shown to navigate correctly without much consideration given to the performance parameters such as distance traversed, etc. Second, they consider non-heuristic algorithms that guarantee bounds on the distance traversed or the ratio of the distance traversed to the shortest path length (computed if the terrain model is known). Then they consider the navigation of robots with very limited computational capabilities such as finite automata, etc.« less

A design strategy for autonomous systems

NASA Technical Reports Server (NTRS)

Forster, Pete

1989-01-01

Some solutions to crucial issues regarding the competent performance of an autonomously operating robot are identified; namely, that of handling multiple and variable data sources containing overlapping information and maintaining coherent operation while responding adequately to changes in the environment. Support for the ideas developed for the construction of such behavior are extracted from speculations in the study of cognitive psychology, an understanding of the behavior of controlled mechanisms, and the development of behavior-based robots in a few robot research laboratories. The validity of these ideas is supported by some simple simulation experiments in the field of mobile robot navigation and guidance.

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.

An Analysis of Navigation Algorithms for Smartphones Using J2ME

NASA Astrophysics Data System (ADS)

Santos, André C.; Tarrataca, Luís; Cardoso, João M. P.

Embedded systems are considered one of the most potential areas for future innovations. Two embedded fields that will most certainly take a primary role in future innovations are mobile robotics and mobile computing. Mobile robots and smartphones are growing in number and functionalities, becoming a presence in our daily life. In this paper, we study the current feasibility of a smartphone to execute navigation algorithms. As a test case, we use a smartphone to control an autonomous mobile robot. We tested three navigation problems: Mapping, Localization and Path Planning. For each of these problems, an algorithm has been chosen, developed in J2ME, and tested on the field. Results show the current mobile Java capacity for executing computationally demanding algorithms and reveal the real possibility of using smartphones for autonomous navigation.

Navigation of a care and welfare robot

NASA Astrophysics Data System (ADS)

Yukawa, Toshihiro; Hosoya, Osamu; Saito, Naoki; Okano, Hideharu

2005-12-01

In this paper, we propose the development of a robot that can perform nursing tasks in a hospital. In a narrow environment such as a sickroom or a hallway, the robot must be able to move freely in arbitrary directions. Therefore, the robot needs to have high controllability and the capability to make precise movements. Our robot can recognize a line by using cameras, and can be controlled in the reference directions by means of comparison with original cell map information; furthermore, it moves safely on the basis of an original center-line established permanently in the building. Correspondence between the robot and a centralized control center enables the robot's autonomous movement in the hospital. Through a navigation system using cell map information, the robot is able to perform nursing tasks smoothly by changing the camera angle.

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.

A learning-based semi-autonomous controller for robotic exploration of unknown disaster scenes while searching for victims.

PubMed

Doroodgar, Barzin; Liu, Yugang; Nejat, Goldie

2014-12-01

Semi-autonomous control schemes can address the limitations of both teleoperation and fully autonomous robotic control of rescue robots in disaster environments by allowing a human operator to cooperate and share such tasks with a rescue robot as navigation, exploration, and victim identification. In this paper, we present a unique hierarchical reinforcement learning-based semi-autonomous control architecture for rescue robots operating in cluttered and unknown urban search and rescue (USAR) environments. The aim of the controller is to enable a rescue robot to continuously learn from its own experiences in an environment in order to improve its overall performance in exploration of unknown disaster scenes. A direction-based exploration technique is integrated in the controller to expand the search area of the robot via the classification of regions and the rubble piles within these regions. Both simulations and physical experiments in USAR-like environments verify the robustness of the proposed HRL-based semi-autonomous controller to unknown cluttered scenes with different sizes and varying types of configurations.

Mapping of unknown industrial plant using ROS-based navigation mobile robot

NASA Astrophysics Data System (ADS)

Priyandoko, G.; Ming, T. Y.; Achmad, M. S. H.

2017-10-01

This research examines how humans work with teleoperated unmanned mobile robot inspection in industrial plant area resulting 2D/3D map for further critical evaluation. This experiment focuses on two parts, the way human-robot doing remote interactions using robust method and the way robot perceives the environment surround as a 2D/3D perspective map. ROS (robot operating system) as a tool was utilized in the development and implementation during the research which comes up with robust data communication method in the form of messages and topics. RGBD SLAM performs the visual mapping function to construct 2D/3D map using Kinect sensor. The results showed that the mobile robot-based teleoperated system are successful to extend human perspective in term of remote surveillance in large area of industrial plant. It was concluded that the proposed work is robust solution for large mapping within an unknown construction building.

Laser-Camera Vision Sensing for Spacecraft Mobile Robot Navigation

NASA Technical Reports Server (NTRS)

Maluf, David A.; Khalil, Ahmad S.; Dorais, Gregory A.; Gawdiak, Yuri

2002-01-01

The advent of spacecraft mobile robots-free-flyng sensor platforms and communications devices intended to accompany astronauts or remotely operate on space missions both inside and outside of a spacecraft-has demanded the development of a simple and effective navigation schema. One such system under exploration involves the use of a laser-camera arrangement to predict relative positioning of the mobile robot. By projecting laser beams from the robot, a 3D reference frame can be introduced. Thus, as the robot shifts in position, the position reference frame produced by the laser images is correspondingly altered. Using normalization and camera registration techniques presented in this paper, the relative translation and rotation of the robot in 3D are determined from these reference frame transformations.

Robotics in invasive cardiac electrophysiology.

PubMed

Shurrab, Mohammed; Schilling, Richard; Gang, Eli; Khan, Ejaz M; Crystal, Eugene

2014-07-01

Robotic systems allow for mapping and ablation of different arrhythmia substrates replacing hand maneuvering of intracardiac catheters with machine steering. Currently there are four commercially available robotic systems. Niobe magnetic navigation system (Stereotaxis Inc., St Louis, MO) and Sensei robotic navigation system (Hansen Medical Inc., Mountain View, CA) have an established platform with at least 10 years of clinical studies looking at their efficacy and safety. AMIGO Remote Catheter System (Catheter Robotics, Inc., Mount Olive, NJ) and Catheter Guidance Control and Imaging (Magnetecs, Inglewood, CA) are in the earlier phases of implementations with ongoing feasibility and some limited clinical studies. This review discusses the advantages and limitations related to each existing system and highlights the ideal futuristic robotic system that may include the most promising features of the current ones.

Hand gesture guided robot-assisted surgery based on a direct augmented reality interface.

PubMed

Wen, Rong; Tay, Wei-Liang; Nguyen, Binh P; Chng, Chin-Boon; Chui, Chee-Kong

2014-09-01

Radiofrequency (RF) ablation is a good alternative to hepatic resection for treatment of liver tumors. However, accurate needle insertion requires precise hand-eye coordination and is also affected by the difficulty of RF needle navigation. This paper proposes a cooperative surgical robot system, guided by hand gestures and supported by an augmented reality (AR)-based surgical field, for robot-assisted percutaneous treatment. It establishes a robot-assisted natural AR guidance mechanism that incorporates the advantages of the following three aspects: AR visual guidance information, surgeon's experiences and accuracy of robotic surgery. A projector-based AR environment is directly overlaid on a patient to display preoperative and intraoperative information, while a mobile surgical robot system implements specified RF needle insertion plans. Natural hand gestures are used as an intuitive and robust method to interact with both the AR system and surgical robot. The proposed system was evaluated on a mannequin model. Experimental results demonstrated that hand gesture guidance was able to effectively guide the surgical robot, and the robot-assisted implementation was found to improve the accuracy of needle insertion. This human-robot cooperative mechanism is a promising approach for precise transcutaneous ablation therapy. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Current status of endovascular catheter robotics.

PubMed

Lumsden, Alan B; Bismuth, Jean

2018-06-01

In this review, we will detail the evolution of endovascular therapy as the basis for the development of catheter-based robotics. In parallel, we will outline the evolution of robotics in the surgical space and how the convergence of technology and the entrepreneurs who push this evolution have led to the development of endovascular robots. The current state-of-the-art and future directions and potential are summarized for the reader. Information in this review has been drawn primarily from our personal clinical and preclinical experience in use of catheter robotics, coupled with some ground-breaking work reported from a few other major centers who have embraced the technology's capabilities and opportunities. Several case studies demonstrating the unique capabilities of a precisely controlled catheter are presented. Most of the preclinical work was performed in the advanced imaging and navigation laboratory. In this unique facility, the interface of advanced imaging techniques and robotic guidance is being explored. Although this procedure employs a very high-tech approach to navigation inside the endovascular space, we have conveyed the kind of opportunities that this technology affords to integrate 3D imaging and 3D control. Further, we present the opportunity of semi-autonomous motion of these devices to a target. For the interventionist, enhanced precision can be achieved in a nearly radiation-free environment.

Proceedings of the 1989 CESAR/CEA (Center for Engineering Systems Advanced Research/Commissariat a l'Energie Atomique) workshop on autonomous mobile robots (May 30--June 1, 1989)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harber, K.S.; Pin, F.G.

1990-03-01

The US DOE Center for Engineering Systems Advanced Research (CESAR) at the Oak Ridge National Laboratory (ORNL) and the Commissariat a l'Energie Atomique's (CEA) Office de Robotique et Productique within the Directorat a la Valorization are working toward a long-term cooperative agreement and relationship in the area of Intelligent Systems Research (ISR). This report presents the proceedings of the first CESAR/CEA Workshop on Autonomous Mobile Robots which took place at ORNL on May 30, 31 and June 1, 1989. The purpose of the workshop was to present and discuss methodologies and algorithms under development at the two facilities in themore » area of perception and navigation for autonomous mobile robots in unstructured environments. Experimental demonstration of the algorithms and comparison of some of their features were proposed to take place within the framework of a previously mutually agreed-upon demonstration scenario or base-case.'' The base-case scenario described in detail in Appendix A, involved autonomous navigation by the robot in an a priori unknown environment with dynamic obstacles, in order to reach a predetermined goal. From the intermediate goal location, the robot had to search for and locate a control panel, move toward it, and dock in front of the panel face. The CESAR demonstration was successfully accomplished using the HERMIES-IIB robot while subsets of the CEA demonstration performed using the ARES robot simulation and animation system were presented. The first session of the workshop focused on these experimental demonstrations and on the needs and considerations for establishing benchmarks'' for testing autonomous robot control algorithms.« less

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.

Open core control software for surgical robots.

PubMed

Arata, Jumpei; Kozuka, Hiroaki; Kim, Hyung Wook; Takesue, Naoyuki; Vladimirov, B; Sakaguchi, Masamichi; Tokuda, Junichi; Hata, Nobuhiko; Chinzei, Kiyoyuki; Fujimoto, Hideo

2010-05-01

In these days, patients and doctors in operation room are surrounded by many medical devices as resulting from recent advancement of medical technology. However, these cutting-edge medical devices are working independently and not collaborating with each other, even though the collaborations between these devices such as navigation systems and medical imaging devices are becoming very important for accomplishing complex surgical tasks (such as a tumor removal procedure while checking the tumor location in neurosurgery). On the other hand, several surgical robots have been commercialized, and are becoming common. However, these surgical robots are not open for collaborations with external medical devices in these days. A cutting-edge "intelligent surgical robot" will be possible in collaborating with surgical robots, various kinds of sensors, navigation system and so on. On the other hand, most of the academic software developments for surgical robots are "home-made" in their research institutions and not open to the public. Therefore, open source control software for surgical robots can be beneficial in this field. From these perspectives, we developed Open Core Control software for surgical robots to overcome these challenges. In general, control softwares have hardware dependencies based on actuators, sensors and various kinds of internal devices. Therefore, these control softwares cannot be used on different types of robots without modifications. However, the structure of the Open Core Control software can be reused for various types of robots by abstracting hardware dependent parts. In addition, network connectivity is crucial for collaboration between advanced medical devices. The OpenIGTLink is adopted in Interface class which plays a role to communicate with external medical devices. At the same time, it is essential to maintain the stable operation within the asynchronous data transactions through network. In the Open Core Control software, several techniques for this purpose were introduced. Virtual fixture is well known technique as a "force guide" for supporting operators to perform precise manipulation by using a master-slave robot. The virtual fixture for precise and safety surgery was implemented on the system to demonstrate an idea of high-level collaboration between a surgical robot and a navigation system. The extension of virtual fixture is not a part of the Open Core Control system, however, the function such as virtual fixture cannot be realized without a tight collaboration between cutting-edge medical devices. By using the virtual fixture, operators can pre-define an accessible area on the navigation system, and the area information can be transferred to the robot. In this manner, the surgical console generates the reflection force when the operator tries to get out from the pre-defined accessible area during surgery. The Open Core Control software was implemented on a surgical master-slave robot and stable operation was observed in a motion test. The tip of the surgical robot was displayed on a navigation system by connecting the surgical robot with a 3D position sensor through the OpenIGTLink. The accessible area was pre-defined before the operation, and the virtual fixture was displayed as a "force guide" on the surgical console. In addition, the system showed stable performance in a duration test with network disturbance. In this paper, a design of the Open Core Control software for surgical robots and the implementation of virtual fixture were described. The Open Core Control software was implemented on a surgical robot system and showed stable performance in high-level collaboration works. The Open Core Control software is developed to be a widely used platform of surgical robots. Safety issues are essential for control software of these complex medical devices. It is important to follow the global specifications such as a FDA requirement "General Principles of Software Validation" or IEC62304. For following these regulations, it is important to develop a self-test environment. Therefore, a test environment is now under development to test various interference in operation room such as a noise of electric knife by considering safety and test environment regulations such as ISO13849 and IEC60508. The Open Core Control software is currently being developed software in open-source manner and available on the Internet. A communization of software interface is becoming a major trend in this field. Based on this perspective, the Open Core Control software can be expected to bring contributions in this field.

Localization of Non-Linearly Modeled Autonomous Mobile Robots Using Out-of-Sequence Measurements

PubMed Central

Besada-Portas, Eva; Lopez-Orozco, Jose A.; Lanillos, Pablo; de la Cruz, Jesus M.

2012-01-01

This paper presents a state of the art of the estimation algorithms dealing with Out-of-Sequence (OOS) measurements for non-linearly modeled systems. The state of the art includes a critical analysis of the algorithm properties that takes into account the applicability of these techniques to autonomous mobile robot navigation based on the fusion of the measurements provided, delayed and OOS, by multiple sensors. Besides, it shows a representative example of the use of one of the most computationally efficient approaches in the localization module of the control software of a real robot (which has non-linear dynamics, and linear and non-linear sensors) and compares its performance against other approaches. The simulated results obtained with the selected OOS algorithm shows the computational requirements that each sensor of the robot imposes to it. The real experiments show how the inclusion of the selected OOS algorithm in the control software lets the robot successfully navigate in spite of receiving many OOS measurements. Finally, the comparison highlights that not only is the selected OOS algorithm among the best performing ones of the comparison, but it also has the lowest computational and memory cost. PMID:22736962

Localization of non-linearly modeled autonomous mobile robots using out-of-sequence measurements.

PubMed

Besada-Portas, Eva; Lopez-Orozco, Jose A; Lanillos, Pablo; de la Cruz, Jesus M

2012-01-01

This paper presents a state of the art of the estimation algorithms dealing with Out-of-Sequence (OOS) measurements for non-linearly modeled systems. The state of the art includes a critical analysis of the algorithm properties that takes into account the applicability of these techniques to autonomous mobile robot navigation based on the fusion of the measurements provided, delayed and OOS, by multiple sensors. Besides, it shows a representative example of the use of one of the most computationally efficient approaches in the localization module of the control software of a real robot (which has non-linear dynamics, and linear and non-linear sensors) and compares its performance against other approaches. The simulated results obtained with the selected OOS algorithm shows the computational requirements that each sensor of the robot imposes to it. The real experiments show how the inclusion of the selected OOS algorithm in the control software lets the robot successfully navigate in spite of receiving many OOS measurements. Finally, the comparison highlights that not only is the selected OOS algorithm among the best performing ones of the comparison, but it also has the lowest computational and memory cost.

Humanoid Mobile Manipulation Using Controller Refinement

NASA Technical Reports Server (NTRS)

Platt, Robert; Burridge, Robert; Diftler, Myron; Graf, Jodi; Goza, Mike; Huber, Eric; Brock, Oliver

2006-01-01

An important class of mobile manipulation problems are move-to-grasp problems where a mobile robot must navigate to and pick up an object. One of the distinguishing features of this class of tasks is its coarse-to-fine structure. Near the beginning of the task, the robot can only sense the target object coarsely or indirectly and make gross motion toward the object. However, after the robot has located and approached the object, the robot must finely control its grasping contacts using precise visual and haptic feedback. This paper proposes that move-to-grasp problems are naturally solved by a sequence of controllers that iteratively refines what ultimately becomes the final solution. This paper introduces the notion of a refining sequence of controllers and characterizes this type of solution. The approach is demonstrated in a move-to-grasp task where Robonaut, the NASA/JSC dexterous humanoid, is mounted on a mobile base and navigates to and picks up a geological sample box. In a series of tests, it is shown that a refining sequence of controllers decreases variance in robot configuration relative to the sample box until a successful grasp has been achieved.

Humanoid Mobile Manipulation Using Controller Refinement

NASA Technical Reports Server (NTRS)

Platt, Robert; Burridge, Robert; Diftler, Myron; Graf, Jodi; Goza, Mike; Huber, Eric

2006-01-01

An important class of mobile manipulation problems are move-to-grasp problems where a mobile robot must navigate to and pick up an object. One of the distinguishing features of this class of tasks is its coarse-to-fine structure. Near the beginning of the task, the robot can only sense the target object coarsely or indirectly and make gross motion toward the object. However, after the robot has located and approached the object, the robot must finely control its grasping contacts using precise visual and haptic feedback. In this paper, it is proposed that move-to-grasp problems are naturally solved by a sequence of controllers that iteratively refines what ultimately becomes the final solution. This paper introduces the notion of a refining sequence of controllers and characterizes this type of solution. The approach is demonstrated in a move-to-grasp task where Robonaut, the NASA/JSC dexterous humanoid, is mounted on a mobile base and navigates to and picks up a geological sample box. In a series of tests, it is shown that a refining sequence of controllers decreases variance in robot configuration relative to the sample box until a successful grasp has been achieved.

Improving mobile robot localization: grid-based approach

NASA Astrophysics Data System (ADS)

Yan, Junchi

2012-02-01

Autonomous mobile robots have been widely studied not only as advanced facilities for industrial and daily life automation, but also as a testbed in robotics competitions for extending the frontier of current artificial intelligence. In many of such contests, the robot is supposed to navigate on the ground with a grid layout. Based on this observation, we present a localization error correction method by exploring the geometric feature of the tile patterns. On top of the classical inertia-based positioning, our approach employs three fiber-optic sensors that are assembled under the bottom of the robot, presenting an equilateral triangle layout. The sensor apparatus, together with the proposed supporting algorithm, are designed to detect a line's direction (vertical or horizontal) by monitoring the grid crossing events. As a result, the line coordinate information can be fused to rectify the cumulative localization deviation from inertia positioning. The proposed method is analyzed theoretically in terms of its error bound and also has been implemented and tested on a customary developed two-wheel autonomous mobile robot.

Sandia National Laboratories proof-of-concept robotic security vehicle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harrington, J.J.; Jones, D.P.; Klarer, P.R.

1989-01-01

Several years ago Sandia National Laboratories developed a prototype interior robot that could navigate autonomously inside a large complex building to air and test interior intrusion detection systems. Recently the Department of Energy Office of Safeguards and Security has supported the development of a vehicle that will perform limited security functions autonomously in a structured exterior environment. The goal of the first phase of this project was to demonstrate the feasibility of an exterior robotic vehicle for security applications by using converted interior robot technology, if applicable. An existing teleoperational test bed vehicle with remote driving controls was modified andmore » integrated with a newly developed command driving station and navigation system hardware and software to form the Robotic Security Vehicle (RSV) system. The RSV, also called the Sandia Mobile Autonomous Navigator (SANDMAN), has been successfully used to demonstrate that teleoperated security vehicles which can perform limited autonomous functions are viable and have the potential to decrease security manpower requirements and improve system capabilities. 2 refs., 3 figs.« less

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.

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot.

PubMed

Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments. We firstly tested our approach on a physical simulation environment and then applied it to our real biomechanical walking robot AMOSII with 19 DOFs to adaptively avoid obstacles and navigate in the real world.

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot

PubMed Central

Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments. We firstly tested our approach on a physical simulation environment and then applied it to our real biomechanical walking robot AMOSII with 19 DOFs to adaptively avoid obstacles and navigate in the real world. PMID:26528176

Assessment of Navigation Using a Hybrid Cognitive/Metric World Model

DTIC Science & Technology

2015-01-01

The robot failed to avoid the stairs of the church. Table A-26 Assessment of vignette 1, path 6b, by researcher TBS Navigate left of the...NOTES 14. ABSTRACT One goal of the US Army Research Laboratory’s Robotic Collaborative Technology Alliance is to develop a cognitive architecture...that would allow a robot to operate on both the semantic and metric levels. As such, both symbolic and metric information would be interpreted within

DEMONSTRATION OF AUTONOMOUS AIR MONITORING THROUGH ROBOTICS

EPA Science Inventory

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...

Research into Kinect/Inertial Measurement Units Based on Indoor Robots.

PubMed

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.

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.

Indoor Positioning System Using Magnetic Field Map Navigation and an Encoder System

PubMed Central

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.

PubMed

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.

Stanford Aerospace Research Laboratory research overview

NASA Technical Reports Server (NTRS)

Ballhaus, W. L.; Alder, L. J.; Chen, V. W.; Dickson, W. C.; Ullman, M. A.

1993-01-01

Over the last ten years, the Stanford Aerospace Robotics Laboratory (ARL) has developed a hardware facility in which a number of space robotics issues have been, and continue to be, addressed. This paper reviews two of the current ARL research areas: navigation and control of free flying space robots, and modelling and control of extremely flexible space structures. The ARL has designed and built several semi-autonomous free-flying robots that perform numerous tasks in a zero-gravity, drag-free, two-dimensional environment. It is envisioned that future generations of these robots will be part of a human-robot team, in which the robots will operate under the task-level commands of astronauts. To make this possible, the ARL has developed a graphical user interface (GUI) with an intuitive object-level motion-direction capability. Using this interface, the ARL has demonstrated autonomous navigation, intercept and capture of moving and spinning objects, object transport, multiple-robot cooperative manipulation, and simple assemblies from both free-flying and fixed bases. The ARL has also built a number of experimental test beds on which the modelling and control of flexible manipulators has been studied. Early ARL experiments in this arena demonstrated for the first time the capability to control the end-point position of both single-link and multi-link flexible manipulators using end-point sensing. Building on these accomplishments, the ARL has been able to control payloads with unknown dynamics at the end of a flexible manipulator, and to achieve high-performance control of a multi-link flexible manipulator.

A 2.5D Map-Based Mobile Robot Localization via Cooperation of Aerial and Ground Robots

PubMed Central

Nam, Tae Hyeon; Shim, Jae Hong; Cho, Young Im

2017-01-01

Recently, there has been increasing interest in studying the task coordination of aerial and ground robots. When a robot begins navigation in an unknown area, it has no information about the surrounding environment. Accordingly, for robots to perform tasks based on location information, they need a simultaneous localization and mapping (SLAM) process that uses sensor information to draw a map of the environment, while simultaneously estimating the current location of the robot on the map. This paper aims to present a localization method based in cooperation between aerial and ground robots in an indoor environment. The proposed method allows a ground robot to reach accurate destination by using a 2.5D elevation map built by a low-cost RGB-D (Red Green and Blue-Depth) sensor and 2D Laser sensor attached onto an aerial robot. A 2.5D elevation map is formed by projecting height information of an obstacle using depth information obtained by the RGB-D sensor onto a grid map, which is generated by using the 2D Laser sensor and scan matching. Experimental results demonstrate the effectiveness of the proposed method for its accuracy in location recognition and computing speed. PMID:29186843

A 2.5D Map-Based Mobile Robot Localization via Cooperation of Aerial and Ground Robots.

PubMed

Nam, Tae Hyeon; Shim, Jae Hong; Cho, Young Im

2017-11-25

Recently, there has been increasing interest in studying the task coordination of aerial and ground robots. When a robot begins navigation in an unknown area, it has no information about the surrounding environment. Accordingly, for robots to perform tasks based on location information, they need a simultaneous localization and mapping (SLAM) process that uses sensor information to draw a map of the environment, while simultaneously estimating the current location of the robot on the map. This paper aims to present a localization method based in cooperation between aerial and ground robots in an indoor environment. The proposed method allows a ground robot to reach accurate destination by using a 2.5D elevation map built by a low-cost RGB-D (Red Green and Blue-Depth) sensor and 2D Laser sensor attached onto an aerial robot. A 2.5D elevation map is formed by projecting height information of an obstacle using depth information obtained by the RGB-D sensor onto a grid map, which is generated by using the 2D Laser sensor and scan matching. Experimental results demonstrate the effectiveness of the proposed method for its accuracy in location recognition and computing speed.

Methods and Apparatus for Autonomous Robotic Control

NASA Technical Reports Server (NTRS)

Gorshechnikov, Anatoly (Inventor); Livitz, Gennady (Inventor); Versace, Massimiliano (Inventor); Palma, Jesse (Inventor)

2017-01-01

Sensory processing of visual, auditory, and other sensor information (e.g., visual imagery, LIDAR, RADAR) is conventionally based on "stovepiped," or isolated processing, with little interactions between modules. Biological systems, on the other hand, fuse multi-sensory information to identify nearby objects of interest more quickly, more efficiently, and with higher signal-to-noise ratios. Similarly, examples of the OpenSense technology disclosed herein use neurally inspired processing to identify and locate objects in a robot's environment. This enables the robot to navigate its environment more quickly and with lower computational and power requirements.

Tandem robot control system and method for controlling mobile robots in tandem

DOEpatents

Hayward, David R.; Buttz, James H.; Shirey, David L.

2002-01-01

A control system for controlling mobile robots provides a way to control mobile robots, connected in tandem with coupling devices, to navigate across difficult terrain or in closed spaces. The mobile robots can be controlled cooperatively as a coupled system in linked mode or controlled individually as separate robots.

Real-time simulation for intra-operative navigation in robotic surgery. Using a mass spring system for a basic study of organ deformation.

PubMed

Kawamura, Kazuya; Kobayashi, Yo; Fujie, Masakatsu G

2007-01-01

Medical technology has advanced with the introduction of robot technology, making previous medical treatments that were very difficult far more possible. However, operation of a surgical robot demands substantial training and continual practice on the part of the surgeon because it requires difficult techniques that are different from those of traditional surgical procedures. We focused on a simulation technology based on the physical characteristics of organs. In this research, we proposed the development of surgical simulation, based on a physical model, for intra-operative navigation by a surgeon. In this paper, we describe the design of our system, in particular our organ deformation calculator. The proposed simulation system consists of an organ deformation calculator and virtual slave manipulators. We obtained adequate experimental results of a target node at a nearby point of interaction, because this point ensures better accuracy for our simulation model. The next research step would be to focus on a surgical environment in which internal organ models would be integrated into a slave simulation system.

Progress in Insect-Inspired Optical Navigation Sensors

NASA Technical Reports Server (NTRS)

Thakoor, Sarita; Chahl, Javaan; Zometzer, Steve

2005-01-01

Progress has been made in continuing efforts to develop optical flight-control and navigation sensors for miniature robotic aircraft. The designs of these sensors are inspired by the designs and functions of the vision systems and brains of insects. Two types of sensors of particular interest are polarization compasses and ocellar horizon sensors. The basic principle of polarization compasses was described (but without using the term "polarization compass") in "Insect-Inspired Flight Control for Small Flying Robots" (NPO-30545), NASA Tech Briefs, Vol. 29, No. 1 (January 2005), page 61. To recapitulate: Bees use sky polarization patterns in ultraviolet (UV) light, caused by Rayleigh scattering of sunlight by atmospheric gas molecules, as direction references relative to the apparent position of the Sun. A robotic direction-finding technique based on this concept would be more robust in comparison with a technique based on the direction to the visible Sun because the UV polarization pattern is distributed across the entire sky and, hence, is redundant and can be extrapolated from a small region of clear sky in an elsewhere cloudy sky that hides the Sun.

Crew/Robot Coordinated Planetary EVA Operations at a Lunar Base Analog Site

NASA Technical Reports Server (NTRS)

Diftler, M. A.; Ambrose, R. O.; Bluethmann, W. J.; Delgado, F. J.; Herrera, E.; Kosmo, J. J.; Janoiko, B. A.; Wilcox, B. H.; Townsend, J. A.; Matthews, J. B.;

Visual Navigation Constructing and Utilizing Simple Maps of an Indoor Environment

DTIC Science & Technology

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

Conference on Space and Military Applications of Automation and Robotics

NASA Technical Reports Server (NTRS)

1988-01-01

Topics addressed include: robotics; deployment strategies; artificial intelligence; expert systems; sensors and image processing; robotic systems; guidance, navigation, and control; aerospace and missile system manufacturing; and telerobotics.

Mobile robot trajectory tracking using noisy RSS measurements: an RFID approach.

PubMed

Miah, M Suruz; Gueaieb, Wail

2014-03-01

Most RF beacons-based mobile robot navigation techniques rely on approximating line-of-sight (LOS) distances between the beacons and the robot. This is mostly performed using the robot's received signal strength (RSS) measurements from the beacons. However, accurate mapping between the RSS measurements and the LOS distance is almost impossible to achieve in reverberant environments. This paper presents a partially-observed feedback controller for a wheeled mobile robot where the feedback signal is in the form of noisy RSS measurements emitted from radio frequency identification (RFID) tags. The proposed controller requires neither an accurate mapping between the LOS distance and the RSS measurements, nor the linearization of the robot model. The controller performance is demonstrated through numerical simulations and real-time experiments. ©2013 Published by ISA. All rights reserved.

RCTA capstone assessment

NASA Astrophysics Data System (ADS)

Lennon, Craig; Bodt, Barry; Childers, Marshal; Dean, Robert; Oh, Jean; DiBerardino, Chip; Keegan, Terence

2015-05-01

The Army Research Laboratory's Robotics Collaborative Technology Alliance (RCTA) is a program intended to change robots from tools that soldiers use into teammates with which soldiers can work. This requires the integration of fundamental and applied research in perception, artificial intelligence, and human-robot interaction. In October of 2014, the RCTA assessed progress towards integrating this research. This assessment was designed to evaluate the robot's performance when it used new capabilities to perform selected aspects of a mission. The assessed capabilities included the ability of the robot to: navigate semantically outdoors with respect to structures and landmarks, identify doors in the facades of buildings, and identify and track persons emerging from those doors. We present details of the mission-based vignettes that constituted the assessment, and evaluations of the robot's performance in these vignettes.

Autonomous assistance navigation for robotic wheelchairs in confined spaces.

PubMed

Cheein, Fernando Auat; Carelli, Ricardo; De la Cruz, Celso; Muller, Sandra; Bastos Filho, Teodiano F

2010-01-01

In this work, a visual interface for the assistance of a robotic wheelchair's navigation is presented. The visual interface is developed for the navigation in confined spaces such as narrows corridors or corridor-ends. The interface performs two navigation modus: non-autonomous and autonomous. The non-autonomous driving of the robotic wheelchair is made by means of a hand-joystick. The joystick directs the motion of the vehicle within the environment. The autonomous driving is performed when the user of the wheelchair has to turn (90, 90 or 180 degrees) within the environment. The turning strategy is performed by a maneuverability algorithm compatible with the kinematics of the wheelchair and by the SLAM (Simultaneous Localization and Mapping) algorithm. The SLAM algorithm provides the interface with the information concerning the environment disposition and the pose -position and orientation-of the wheelchair within the environment. Experimental and statistical results of the interface are also shown in this work.

Integrating Terrain Maps Into a Reactive Navigation Strategy

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Werger, Barry; Seraji, Homayoun

2006-01-01

An improved method of processing information for autonomous navigation of a robotic vehicle across rough terrain involves the integration of terrain maps into a reactive navigation strategy. Somewhat more precisely, the method involves the incorporation, into navigation logic, of data equivalent to regional traversability maps. The terrain characteristic is mapped using a fuzzy-logic representation of the difficulty of traversing the terrain. The method is robust in that it integrates a global path-planning strategy with sensor-based regional and local navigation strategies to ensure a high probability of success in reaching a destination and avoiding obstacles along the way. The sensor-based strategies use cameras aboard the vehicle to observe the regional terrain, defined as the area of the terrain that covers the immediate vicinity near the vehicle to a specified distance a few meters away.

Long Range Navigation for Mars Rovers Using Sensor-Based Path Planning and Visual Localisation

NASA Technical Reports Server (NTRS)

Laubach, Sharon L.; Olson, Clark F.; Burdick, Joel W.; Hayati, Samad

1999-01-01

The Mars Pathfinder mission illustrated the benefits of including a mobile robotic explorer on a planetary mission. However, for future Mars rover missions, significantly increased autonomy in navigation is required in order to meet demanding mission criteria. To address these requirements, we have developed new path planning and localisation capabilities that allow a rover to navigate robustly to a distant landmark. These algorithms have been implemented on the JPL Rocky 7 prototype microrover and have been tested extensively in the JPL MarsYard, as well as in natural terrain.

An assisted navigation training framework based on judgment theory using sparse and discrete human-machine interfaces.

PubMed

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.

Real-time optical flow estimation on a GPU for a skied-steered mobile robot

NASA Astrophysics Data System (ADS)

Kniaz, V. V.

2016-04-01

Accurate egomotion estimation is required for mobile robot navigation. Often the egomotion is estimated using optical flow algorithms. For an accurate estimation of optical flow most of modern algorithms require high memory resources and processor speed. However simple single-board computers that control the motion of the robot usually do not provide such resources. On the other hand, most of modern single-board computers are equipped with an embedded GPU that could be used in parallel with a CPU to improve the performance of the optical flow estimation algorithm. This paper presents a new Z-flow algorithm for efficient computation of an optical flow using an embedded GPU. The algorithm is based on the phase correlation optical flow estimation and provide a real-time performance on a low cost embedded GPU. The layered optical flow model is used. Layer segmentation is performed using graph-cut algorithm with a time derivative based energy function. Such approach makes the algorithm both fast and robust in low light and low texture conditions. The algorithm implementation for a Raspberry Pi Model B computer is discussed. For evaluation of the algorithm the computer was mounted on a Hercules mobile skied-steered robot equipped with a monocular camera. The evaluation was performed using a hardware-in-the-loop simulation and experiments with Hercules mobile robot. Also the algorithm was evaluated using KITTY Optical Flow 2015 dataset. The resulting endpoint error of the optical flow calculated with the developed algorithm was low enough for navigation of the robot along the desired trajectory.

[Principles of MR-guided interventions, surgery, navigation, and robotics].

PubMed

Melzer, A

2010-08-01

The application of magnetic resonance imaging (MRI) as an imaging technique in interventional and surgical techniques provides a new dimension of soft tissue-oriented precise procedures without exposure to ionizing radiation and nephrotoxic allergenic, iodine-containing contrast agents. The technical capabilities of MRI in combination with interventional devices and systems, navigation, and robotics are discussed.

A neural network-based exploratory learning and motor planning system for co-robots

PubMed Central

Galbraith, Byron V.; Guenther, Frank H.; Versace, Massimiliano

2015-01-01

Collaborative robots, or co-robots, are semi-autonomous robotic agents designed to work alongside humans in shared workspaces. To be effective, co-robots require the ability to respond and adapt to dynamic scenarios encountered in natural environments. One way to achieve this is through exploratory learning, or “learning by doing,” an unsupervised method in which co-robots are able to build an internal model for motor planning and coordination based on real-time sensory inputs. In this paper, we present an adaptive neural network-based system for co-robot control that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. To validate this system we used the 11-degrees-of-freedom RoPro Calliope mobile robot. Through motor babbling of its wheels and arm, the Calliope learned how to relate visual and proprioceptive information to achieve hand-eye-body coordination. By continually evaluating sensory inputs and externally provided goal directives, the Calliope was then able to autonomously select the appropriate wheel and joint velocities needed to perform its assigned task, such as following a moving target or retrieving an indicated object. PMID:26257640

A neural network-based exploratory learning and motor planning system for co-robots.

PubMed

Galbraith, Byron V; Guenther, Frank H; Versace, Massimiliano

2015-01-01

Collaborative robots, or co-robots, are semi-autonomous robotic agents designed to work alongside humans in shared workspaces. To be effective, co-robots require the ability to respond and adapt to dynamic scenarios encountered in natural environments. One way to achieve this is through exploratory learning, or "learning by doing," an unsupervised method in which co-robots are able to build an internal model for motor planning and coordination based on real-time sensory inputs. In this paper, we present an adaptive neural network-based system for co-robot control that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. To validate this system we used the 11-degrees-of-freedom RoPro Calliope mobile robot. Through motor babbling of its wheels and arm, the Calliope learned how to relate visual and proprioceptive information to achieve hand-eye-body coordination. By continually evaluating sensory inputs and externally provided goal directives, the Calliope was then able to autonomously select the appropriate wheel and joint velocities needed to perform its assigned task, such as following a moving target or retrieving an indicated object.

Endocavity Ultrasound Probe Manipulators

PubMed Central

Stoianovici, Dan; Kim, Chunwoo; Schäfer, Felix; Huang, Chien-Ming; Zuo, Yihe; Petrisor, Doru; Han, Misop

2014-01-01

We developed two similar structure manipulators for medical endocavity ultrasound probes with 3 and 4 degrees of freedom (DoF). These robots allow scanning with ultrasound for 3-D imaging and enable robot-assisted image-guided procedures. Both robots use remote center of motion kinematics, characteristic of medical robots. The 4-DoF robot provides unrestricted manipulation of the endocavity probe. With the 3-DoF robot the insertion motion of the probe must be adjusted manually, but the device is simpler and may also be used to manipulate external-body probes. The robots enabled a novel surgical approach of using intraoperative image-based navigation during robot-assisted laparoscopic prostatectomy (RALP), performed with concurrent use of two robotic systems (Tandem, T-RALP). Thus far, a clinical trial for evaluation of safety and feasibility has been performed successfully on 46 patients. This paper describes the architecture and design of the robots, the two prototypes, control features related to safety, preclinical experiments, and the T-RALP procedure. PMID:24795525

Evaluation of the ROSA™ Spine robot for minimally invasive surgical procedures.

PubMed

Lefranc, M; Peltier, J

2016-10-01

The ROSA® robot (Medtech, Montpellier, France) is a new medical device designed to assist the surgeon during minimally invasive spine procedures. The device comprises a patient-side cart (bearing the robotic arm and a workstation) and an optical navigation camera. The ROSA® Spine robot enables accurate pedicle screw placement. Thanks to its robotic arm and navigation abilities, the robot monitors movements of the spine throughout the entire surgical procedure and thus enables accurate, safe arthrodesis for the treatment of degenerative lumbar disc diseases, exactly as planned by the surgeon. Development perspectives include (i) assistance at all levels of the spine, (ii) improved planning abilities (virtualization of the entire surgical procedure) and (iii) use for almost any percutaneous spinal procedures not limited in screw positioning such as percutaneous endoscopic lumbar discectomy, intracorporeal implant positioning, over te top laminectomy or radiofrequency ablation.

Learning classifier systems for single and multiple mobile robots in unstructured environments

NASA Astrophysics Data System (ADS)

Bay, John S.

1995-12-01

The learning classifier system (LCS) is a learning production system that generates behavioral rules via an underlying discovery mechanism. The LCS architecture operates similarly to a blackboard architecture; i.e., by posted-message communications. But in the LCS, the message board is wiped clean at every time interval, thereby requiring no persistent shared resource. In this paper, we adapt the LCS to the problem of mobile robot navigation in completely unstructured environments. We consider the model of the robot itself, including its sensor and actuator structures, to be part of this environment, in addition to the world-model that includes a goal and obstacles at unknown locations. This requires a robot to learn its own I/O characteristics in addition to solving its navigation problem, but results in a learning controller that is equally applicable, unaltered, in robots with a wide variety of kinematic structures and sensing capabilities. We show the effectiveness of this LCS-based controller through both simulation and experimental trials with a small robot. We then propose a new architecture, the Distributed Learning Classifier System (DLCS), which generalizes the message-passing behavior of the LCS from internal messages within a single agent to broadcast massages among multiple agents. This communications mode requires little bandwidth and is easily implemented with inexpensive, off-the-shelf hardware. The DLCS is shown to have potential application as a learning controller for multiple intelligent agents.

Robust human machine interface based on head movements applied to assistive robotics.

PubMed

Perez, Elisa; López, Natalia; Orosco, Eugenio; Soria, Carlos; Mut, Vicente; Freire-Bastos, Teodiano

2013-01-01

This paper presents an interface that uses two different sensing techniques and combines both results through a fusion process to obtain the minimum-variance estimator of the orientation of the user's head. Sensing techniques of the interface are based on an inertial sensor and artificial vision. The orientation of the user's head is used to steer the navigation of a robotic wheelchair. Also, a control algorithm for assistive technology system is presented. The system is evaluated by four individuals with severe motors disability and a quantitative index was developed, in order to objectively evaluate the performance. The results obtained are promising since most users could perform the proposed tasks with the robotic wheelchair.

Robust Human Machine Interface Based on Head Movements Applied to Assistive Robotics

PubMed Central

Perez, Elisa; López, Natalia; Orosco, Eugenio; Soria, Carlos; Mut, Vicente; Freire-Bastos, Teodiano

2013-01-01

This paper presents an interface that uses two different sensing techniques and combines both results through a fusion process to obtain the minimum-variance estimator of the orientation of the user's head. Sensing techniques of the interface are based on an inertial sensor and artificial vision. The orientation of the user's head is used to steer the navigation of a robotic wheelchair. Also, a control algorithm for assistive technology system is presented. The system is evaluated by four individuals with severe motors disability and a quantitative index was developed, in order to objectively evaluate the performance. The results obtained are promising since most users could perform the proposed tasks with the robotic wheelchair. PMID:24453877

Adding navigation, artificial audition and vital sign monitoring capabilities to a telepresence mobile robot for remote home care applications.

PubMed

Laniel, Sebastien; Letourneau, Dominic; Labbe, Mathieu; Grondin, Francois; Polgar, Janice; Michaud, Francois

2017-07-01

A telepresence mobile robot is a remote-controlled, wheeled device with wireless internet connectivity for bidirectional audio, video and data transmission. In health care, a telepresence robot could be used to have a clinician or a caregiver assist seniors in their homes without having to travel to these locations. Many mobile telepresence robotic platforms have recently been introduced on the market, bringing mobility to telecommunication and vital sign monitoring at reasonable costs. What is missing for making them effective remote telepresence systems for home care assistance are capabilities specifically needed to assist the remote operator in controlling the robot and perceiving the environment through the robot's sensors or, in other words, minimizing cognitive load and maximizing situation awareness. This paper describes our approach adding navigation, artificial audition and vital sign monitoring capabilities to a commercially available telepresence mobile robot. This requires the use of a robot control architecture to integrate the autonomous and teleoperation capabilities of the platform.

A 3D terrain reconstruction method of stereo vision based quadruped robot navigation system

NASA Astrophysics Data System (ADS)

Ge, Zhuo; Zhu, Ying; Liang, Guanhao

2017-01-01

To provide 3D environment information for the quadruped robot autonomous navigation system during walking through rough terrain, based on the stereo vision, a novel 3D terrain reconstruction method is presented. In order to solve the problem that images collected by stereo sensors have large regions with similar grayscale and the problem that image matching is poor at real-time performance, watershed algorithm and fuzzy c-means clustering algorithm are combined for contour extraction. Aiming at the problem of error matching, duel constraint with region matching and pixel matching is established for matching optimization. Using the stereo matching edge pixel pairs, the 3D coordinate algorithm is estimated according to the binocular stereo vision imaging model. Experimental results show that the proposed method can yield high stereo matching ratio and reconstruct 3D scene quickly and efficiently.

Performance Evaluation of a Pose Estimation Method based on the SwissRanger SR4000

DTIC Science & Technology

2012-08-01

however, not suitable for navigating a small robot. Commercially available Flash LIDAR now has sufficient accuracy for robotic application. A...Flash LIDAR simultaneously produces intensity and range images of the scene at a video frame rate. It has the following advantages over stereovision...fully dense depth data across its field-of-view. The commercially available Flash LIDAR includes the SwissRanger [17] and TigerEye 3D [18

ROBOSIGHT: Robotic Vision System For Inspection And Manipulation

NASA Astrophysics Data System (ADS)

Trivedi, Mohan M.; Chen, ChuXin; Marapane, Suresh

1989-02-01

Vision is an important sensory modality that can be used for deriving information critical to the proper, efficient, flexible, and safe operation of an intelligent robot. Vision systems are uti-lized for developing higher level interpretation of the nature of a robotic workspace using images acquired by cameras mounted on a robot. Such information can be useful for tasks such as object recognition, object location, object inspection, obstacle avoidance and navigation. In this paper we describe efforts directed towards developing a vision system useful for performing various robotic inspection and manipulation tasks. The system utilizes gray scale images and can be viewed as a model-based system. It includes general purpose image analysis modules as well as special purpose, task dependent object status recognition modules. Experiments are described to verify the robust performance of the integrated system using a robotic testbed.

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.

Real-Time Hazard Detection and Avoidance Demonstration for a Planetary Lander

NASA Technical Reports Server (NTRS)

Epp, Chirold D.; Robertson, Edward A.; Carson, John M., III

2014-01-01

The Autonomous Landing Hazard Avoidance Technology (ALHAT) Project is chartered to develop and mature to a Technology Readiness Level (TRL) of six an autonomous system combining guidance, navigation and control with terrain sensing and recognition functions for crewed, cargo, and robotic planetary landing vehicles. In addition to precision landing close to a pre-mission defined landing location, the ALHAT System must be capable of autonomously identifying and avoiding surface hazards in real-time to enable a safe landing under any lighting conditions. This paper provides an overview of the recent results of the ALHAT closed loop hazard detection and avoidance flight demonstrations on the Morpheus Vertical Testbed (VTB) at the Kennedy Space Center, including results and lessons learned. This effort is also described in the context of a technology path in support of future crewed and robotic planetary exploration missions based upon the core sensing functions of the ALHAT system: Terrain Relative Navigation (TRN), Hazard Detection and Avoidance (HDA), and Hazard Relative Navigation (HRN).

Navigating the pathway to robotic competency in general thoracic surgery.

PubMed

Seder, Christopher W; Cassivi, Stephen D; Wigle, Dennis A

2013-01-01

Although robotic technology has addressed many of the limitations of traditional videoscopic surgery, robotic surgery has not gained widespread acceptance in the general thoracic community. We report our initial robotic surgery experience and propose a structured, competency-based pathway for the development of robotic skills. Between December 2008 and February 2012, a total of 79 robot-assisted pulmonary, mediastinal, benign esophageal, or diaphragmatic procedures were performed. Data on patient characteristics and perioperative outcomes were retrospectively collected and analyzed. During the study period, one surgeon and three residents participated in a triphasic, competency-based pathway designed to teach robotic skills. The pathway consisted of individual preclinical learning followed by mentored preclinical exercises and progressive clinical responsibility. The robot-assisted procedures performed included lung resection (n = 38), mediastinal mass resection (n = 19), hiatal or paraesophageal hernia repair (n = 12), and Heller myotomy (n = 7), among others (n = 3). There were no perioperative mortalities, with a 20% complication rate and a 3% readmission rate. Conversion to a thoracoscopic or open approach was required in eight pulmonary resections to facilitate dissection (six) or to control hemorrhage (two). Fewer major perioperative complications were observed in the later half of the experience. All residents who participated in the thoracic surgery robotic pathway perform robot-assisted procedures as part of their clinical practice. Robot-assisted thoracic surgery can be safely learned when skill acquisition is guided by a structured, competency-based pathway.

Autonomous Collision-Free Navigation of Microvehicles in Complex and Dynamically Changing Environments.

PubMed

Li, Tianlong; Chang, Xiaocong; Wu, Zhiguang; Li, Jinxing; Shao, Guangbin; Deng, Xinghong; Qiu, Jianbin; Guo, Bin; Zhang, Guangyu; He, Qiang; Li, Longqiu; Wang, Joseph

2017-09-26

Self-propelled micro- and nanoscale robots represent a rapidly emerging and fascinating robotics research area. However, designing autonomous and adaptive control systems for operating micro/nanorobotics in complex and dynamically changing environments, which is a highly demanding feature, is still an unmet challenge. Here we describe a smart microvehicle for precise autonomous navigation in complicated environments and traffic scenarios. The fully autonomous navigation system of the smart microvehicle is composed of a microscope-coupled CCD camera, an artificial intelligence planner, and a magnetic field generator. The microscope-coupled CCD camera provides real-time localization of the chemically powered Janus microsphere vehicle and environmental detection for path planning to generate optimal collision-free routes, while the moving direction of the microrobot toward a reference position is determined by the external electromagnetic torque. Real-time object detection offers adaptive path planning in response to dynamically changing environments. We demonstrate that the autonomous navigation system can guide the vehicle movement in complex patterns, in the presence of dynamically changing obstacles, and in complex biological environments. Such a navigation system for micro/nanoscale vehicles, relying on vision-based close-loop control and path planning, is highly promising for their autonomous operation in complex dynamic settings and unpredictable scenarios expected in a variety of realistic nanoscale scenarios.

Navigation through unknown and dynamic open spaces using topological notions

NASA Astrophysics Data System (ADS)

Miguel-Tomé, Sergio

2018-04-01

Until now, most algorithms used for navigation have had the purpose of directing system towards one point in space. However, humans communicate tasks by specifying spatial relations among elements or places. In addition, the environments in which humans develop their activities are extremely dynamic. The only option that allows for successful navigation in dynamic and unknown environments is making real-time decisions. Therefore, robots capable of collaborating closely with human beings must be able to make decisions based on the local information registered by the sensors and interpret and express spatial relations. Furthermore, when one person is asked to perform a task in an environment, this task is communicated given a category of goals so the person does not need to be supervised. Thus, two problems appear when one wants to create multifunctional robots: how to navigate in dynamic and unknown environments using spatial relations and how to accomplish this without supervision. In this article, a new architecture to address the two cited problems is presented, called the topological qualitative navigation architecture. In previous works, a qualitative heuristic called the heuristic of topological qualitative semantics (HTQS) has been developed to establish and identify spatial relations. However, that heuristic only allows for establishing one spatial relation with a specific object. In contrast, navigation requires a temporal sequence of goals with different objects. The new architecture attains continuous generation of goals and resolves them using HTQS. Thus, the new architecture achieves autonomous navigation in dynamic or unknown open environments.

Two-Armed, Mobile, Sensate Research Robot

NASA Technical Reports Server (NTRS)

Engelberger, J. F.; Roberts, W. Nelson; Ryan, David J.; Silverthorne, Andrew

2004-01-01

The Anthropomorphic Robotic Testbed (ART) is an experimental prototype of a partly anthropomorphic, humanoid-size, mobile robot. The basic ART design concept provides for a combination of two-armed coordination, tactility, stereoscopic vision, mobility with navigation and avoidance of obstacles, and natural-language communication, so that the ART could emulate humans in many activities. The ART could be developed into a variety of highly capable robotic assistants for general or specific applications. There is especially great potential for the development of ART-based robots as substitutes for live-in health-care aides for home-bound persons who are aged, infirm, or physically handicapped; these robots could greatly reduce the cost of home health care and extend the term of independent living. The ART is a fully autonomous and untethered system. It includes a mobile base on which is mounted an extensible torso topped by a head, shoulders, and two arms. All subsystems of the ART are powered by a rechargeable, removable battery pack. The mobile base is a differentially- driven, nonholonomic vehicle capable of a speed >1 m/s and can handle a payload >100 kg. The base can be controlled manually, in forward/backward and/or simultaneous rotational motion, by use of a joystick. Alternatively, the motion of the base can be controlled autonomously by an onboard navigational computer. By retraction or extension of the torso, the head height of the ART can be adjusted from 5 ft (1.5 m) to 6 1/2 ft (2 m), so that the arms can reach either the floor or high shelves, or some ceilings. The arms are symmetrical. Each arm (including the wrist) has a total of six rotary axes like those of the human shoulder, elbow, and wrist joints. The arms are actuated by electric motors in combination with brakes and gas-spring assists on the shoulder and elbow joints. The arms are operated under closed-loop digital control. A receptacle for an end effector is mounted on the tip of the wrist and contains a force-and-torque sensor that provides feedback for force (compliance) control of the arm. The end effector could be a tool or a robot hand, depending on the application.

Navigation system for autonomous mapper robots

NASA Astrophysics Data System (ADS)

Halbach, Marc; Baudoin, Yvan

1993-05-01

This paper describes the conception and realization of a fast, robust, and general navigation system for a mobile (wheeled or legged) robot. A database, representing a high level map of the environment is generated and continuously updated. The first part describes the legged target vehicle and the hexapod robot being developed. The second section deals with spatial and temporal sensor fusion for dynamic environment modeling within an obstacle/free space probabilistic classification grid. Ultrasonic sensors are used, others are suspected to be integrated, and a-priori knowledge is treated. US sensors are controlled by the path planning module. The third part concerns path planning and a simulation of a wheeled robot is also presented.

Visual environment recognition for robot path planning using template matched filters

NASA Astrophysics Data System (ADS)

Orozco-Rosas, Ulises; Picos, Kenia; Díaz-Ramírez, Víctor H.; Montiel, Oscar; Sepúlveda, Roberto

2017-08-01

A visual approach in environment recognition for robot navigation is proposed. This work includes a template matching filtering technique to detect obstacles and feasible paths using a single camera to sense a cluttered environment. In this problem statement, a robot can move from the start to the goal by choosing a single path between multiple possible ways. In order to generate an efficient and safe path for mobile robot navigation, the proposal employs a pseudo-bacterial potential field algorithm to derive optimal potential field functions using evolutionary computation. Simulation results are evaluated in synthetic and real scenes in terms of accuracy of environment recognition and efficiency of path planning computation.

Using sensor habituation in mobile robots to reduce oscillatory movements in narrow corridors.

PubMed

Chang, Carolina

2005-11-01

Habituation is a form of nonassociative learning observed in a variety of species of animals. Arguably, it is the simplest form of learning. Nonetheless, the ability to habituate to certain stimuli implies plastic neural systems and adaptive behaviors. This paper describes how computational models of habituation can be applied to real robots. In particular, we discuss the problem of the oscillatory movements observed when a Khepera robot navigates through narrow hallways using a biologically inspired neurocontroller. Results show that habituation to the proximity of the walls can lead to smoother navigation. Habituation to sensory stimulation to the sides of the robot does not interfere with the robot's ability to turn at dead ends and to avoid obstacles outside the hallway. This paper shows that simple biological mechanisms of learning can be adapted to achieve better performance in real mobile robots.

A two-class self-paced BCI to control a robot in four directions.

PubMed

Ron-Angevin, Ricardo; Velasco-Alvarez, Francisco; Sancha-Ros, Salvador; da Silva-Sauer, Leandro

2011-01-01

In this work, an electroencephalographic analysis-based, self-paced (asynchronous) brain-computer interface (BCI) is proposed to control a mobile robot using four different navigation commands: turn right, turn left, move forward and move back. In order to reduce the probability of misclassification, the BCI is to be controlled with only two mental tasks (relaxed state versus imagination of right hand movements), using an audio-cued interface. Four healthy subjects participated in the experiment. After two sessions controlling a simulated robot in a virtual environment (which allowed the user to become familiar with the interface), three subjects successfully moved the robot in a real environment. The obtained results show that the proposed interface enables control over the robot, even for subjects with low BCI performance. © 2011 IEEE

Planning in subsumption architectures

NASA Technical Reports Server (NTRS)

Chalfant, Eugene C.

1994-01-01

A subsumption planner using a parallel distributed computational paradigm based on the subsumption architecture for control of real-world capable robots is described. Virtual sensor state space is used as a planning tool to visualize the robot's anticipated effect on its environment. Decision sequences are generated based on the environmental situation expected at the time the robot must commit to a decision. Between decision points, the robot performs in a preprogrammed manner. A rudimentary, domain-specific partial world model contains enough information to extrapolate the end results of the rote behavior between decision points. A collective network of predictors operates in parallel with the reactive network forming a recurrrent network which generates plans as a hierarchy. Details of a plan segment are generated only when its execution is imminent. The use of the subsumption planner is demonstrated by a simple maze navigation problem.

Tracking Control of Mobile Robots Localized via Chained Fusion of Discrete and Continuous Epipolar Geometry, IMU and Odometry.

PubMed

Tick, David; Satici, Aykut C; Shen, Jinglin; Gans, Nicholas

2013-08-01

This paper presents a novel navigation and control system for autonomous mobile robots that includes path planning, localization, and control. A unique vision-based pose and velocity estimation scheme utilizing both the continuous and discrete forms of the Euclidean homography matrix is fused with inertial and optical encoder measurements to estimate the pose, orientation, and velocity of the robot and ensure accurate localization and control signals. A depth estimation system is integrated in order to overcome the loss of scale inherent in vision-based estimation. A path following control system is introduced that is capable of guiding the robot along a designated curve. Stability analysis is provided for the control system and experimental results are presented that prove the combined localization and control system performs with high accuracy.

Modeling and controlling a robotic convoy using guidance laws strategies.

PubMed

Belkhouche, Fethi; Belkhouche, Boumediene

2005-08-01

This paper deals with the problem of modeling and controlling a robotic convoy. Guidance laws techniques are used to provide a mathematical formulation of the problem. The guidance laws used for this purpose are the velocity pursuit, the deviated pursuit, and the proportional navigation. The velocity pursuit equations model the robot's path under various sensors based control laws. A systematic study of the tracking problem based on this technique is undertaken. These guidance laws are applied to derive decentralized control laws for the angular and linear velocities. For the angular velocity, the control law is directly derived from the guidance laws after considering the relative kinematics equations between successive robots. The second control law maintains the distance between successive robots constant by controlling the linear velocity. This control law is derived by considering the kinematics equations between successive robots under the considered guidance law. Properties of the method are discussed and proven. Simulation results confirm the validity of our approach, as well as the validity of the properties of the method. Index Terms-Guidance laws, relative kinematics equations, robotic convoy, tracking.

Solar Thermal Utility-Scale Joint Venture Program (USJVP) Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

MANCINI,THOMAS R.

2001-04-01

Several years ago Sandia National Laboratories developed a prototype interior robot [1] that could navigate autonomously inside a large complex building to aid and test interior intrusion detection systems. Recently the Department of Energy Office of Safeguards and Security has supported the development of a vehicle that will perform limited security functions autonomously in a structured exterior environment. The goal of the first phase of this project was to demonstrate the feasibility of an exterior robotic vehicle for security applications by using converted interior robot technology, if applicable. An existing teleoperational test bed vehicle with remote driving controls was modifiedmore » and integrated with a newly developed command driving station and navigation system hardware and software to form the Robotic Security Vehicle (RSV) system. The RSV, also called the Sandia Mobile Autonomous Navigator (SANDMAN), has been successfully used to demonstrate that teleoperated security vehicles which can perform limited autonomous functions are viable and have the potential to decrease security manpower requirements and improve system capabilities.« less

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.

Autonomous Robot Navigation in Human-Centered Environments Based on 3D Data Fusion

NASA Astrophysics Data System (ADS)

Steinhaus, Peter; Strand, Marcus; Dillmann, Rüdiger

2007-12-01

Efficient navigation of mobile platforms in dynamic human-centered environments is still an open research topic. We have already proposed an architecture (MEPHISTO) for a navigation system that is able to fulfill the main requirements of efficient navigation: fast and reliable sensor processing, extensive global world modeling, and distributed path planning. Our architecture uses a distributed system of sensor processing, world modeling, and path planning units. In this arcticle, we present implemented methods in the context of data fusion algorithms for 3D world modeling and real-time path planning. We also show results of the prototypic application of the system at the museum ZKM (center for art and media) in Karlsruhe.

A positional estimation technique for an autonomous land vehicle in an unstructured environment

NASA Technical Reports Server (NTRS)

Talluri, Raj; Aggarwal, J. K.

1990-01-01

This paper presents a solution to the positional estimation problem of an autonomous land vehicle navigating in an unstructured mountainous terrain. A Digital Elevation Map (DEM) of the area in which the robot is to navigate is assumed to be given. It is also assumed that the robot is equipped with a camera that can be panned and tilted, and a device to measure the elevation of the robot above the ground surface. No recognizable landmarks are assumed to be present in the environment in which the robot is to navigate. The solution presented makes use of the DEM information, and structures the problem as a heuristic search in the DEM for the possible robot location. The shape and position of the horizon line in the image plane and the known camera geometry of the perspective projection are used as parameters to search the DEM. Various heuristics drawn from the geometric constraints are used to prune the search space significantly. The algorithm is made robust to errors in the imaging process by accounting for the worst care errors. The approach is tested using DEM data of areas in Colorado and Texas. The method is suitable for use in outdoor mobile robots and planetary rovers.

Survey of computer vision technology for UVA navigation

NASA Astrophysics Data System (ADS)

Xie, Bo; Fan, Xiang; Li, Sijian

2017-11-01

Navigation based on computer version technology, which has the characteristics of strong independence, high precision and is not susceptible to electrical interference, has attracted more and more attention in the filed of UAV navigation research. Early navigation project based on computer version technology mainly applied to autonomous ground robot. In recent years, the visual navigation system is widely applied to unmanned machine, deep space detector and underwater robot. That further stimulate the research of integrated navigation algorithm based on computer version technology. In China, with many types of UAV development and two lunar exploration, the three phase of the project started, there has been significant progress in the study of visual navigation. The paper expounds the development of navigation based on computer version technology in the filed of UAV navigation research and draw a conclusion that visual navigation is mainly applied to three aspects as follows.(1) Acquisition of UAV navigation parameters. The parameters, including UAV attitude, position and velocity information could be got according to the relationship between the images from sensors and carrier's attitude, the relationship between instant matching images and the reference images and the relationship between carrier's velocity and characteristics of sequential images.(2) Autonomous obstacle avoidance. There are many ways to achieve obstacle avoidance in UAV navigation. The methods based on computer version technology ,including feature matching, template matching, image frames and so on, are mainly introduced. (3) The target tracking, positioning. Using the obtained images, UAV position is calculated by using optical flow method, MeanShift algorithm, CamShift algorithm, Kalman filtering and particle filter algotithm. The paper expounds three kinds of mainstream visual system. (1) High speed visual system. It uses parallel structure, with which image detection and processing are carried out at high speed. The system is applied to rapid response system. (2) The visual system of distributed network. There are several discrete image data acquisition sensor in different locations, which transmit image data to the node processor to increase the sampling rate. (3) The visual system combined with observer. The system combines image sensors with the external observers to make up for lack of visual equipment. To some degree, these systems overcome lacks of the early visual system, including low frequency, low processing efficiency and strong noise. In the end, the difficulties of navigation based on computer version technology in practical application are briefly discussed. (1) Due to the huge workload of image operation , the real-time performance of the system is poor. (2) Due to the large environmental impact , the anti-interference ability of the system is poor.(3) Due to the ability to work in a particular environment, the system has poor adaptability.

Symbiotic Navigation in Multi-Robot Systems with Remote Obstacle Knowledge Sharing

PubMed Central

Ravankar, Abhijeet; Ravankar, Ankit A.; Kobayashi, Yukinori; Emaru, Takanori

2017-01-01

Large scale operational areas often require multiple service robots for coverage and task parallelism. In such scenarios, each robot keeps its individual map of the environment and serves specific areas of the map at different times. We propose a knowledge sharing mechanism for multiple robots in which one robot can inform other robots about the changes in map, like path blockage, or new static obstacles, encountered at specific areas of the map. This symbiotic information sharing allows the robots to update remote areas of the map without having to explicitly navigate those areas, and plan efficient paths. A node representation of paths is presented for seamless sharing of blocked path information. The transience of obstacles is modeled to track obstacles which might have been removed. A lazy information update scheme is presented in which only relevant information affecting the current task is updated for efficiency. The advantages of the proposed method for path planning are discussed against traditional method with experimental results in both simulation and real environments. PMID:28678193

Terrain discovery and navigation of a multi-articulated linear robot using map-seeking circuits

NASA Astrophysics Data System (ADS)

Snider, Ross K.; Arathorn, David W.

2006-05-01

A significant challenge in robotics is providing a robot with the ability to sense its environment and then autonomously move while accommodating obstacles. The DARPA Grand Challenge, one of the most visible examples, set the goal of driving a vehicle autonomously for over a hundred miles avoiding obstacles along a predetermined path. Map-Seeking Circuits have shown their biomimetic capability in both vision and inverse kinematics and here we demonstrate their potential usefulness for intelligent exploration of unknown terrain using a multi-articulated linear robot. A robot that could handle any degree of terrain complexity would be useful for exploring inaccessible crowded spaces such as rubble piles in emergency situations, patrolling/intelligence gathering in tough terrain, tunnel exploration, and possibly even planetary exploration. Here we simulate autonomous exploratory navigation by an interaction of terrain discovery using the multi-articulated linear robot to build a local terrain map and exploitation of that growing terrain map to solve the propulsion problem of the robot.

Recent CESAR (Center for Engineering Systems Advanced Research) research activities in sensor based reasoning for autonomous machines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pin, F.G.; de Saussure, G.; Spelt, P.F.

1988-01-01

This paper describes recent research activities at the Center for Engineering Systems Advanced Research (CESAR) in the area of sensor based reasoning, with emphasis being given to their application and implementation on our HERMIES-IIB autonomous mobile vehicle. These activities, including navigation and exploration in a-priori unknown and dynamic environments, goal recognition, vision-guided manipulation and sensor-driven machine learning, are discussed within the framework of a scenario in which an autonomous robot is asked to navigate through an unknown dynamic environment, explore, find and dock at the panel, read and understand the status of the panel's meters and dials, learn the functioningmore » of a process control panel, and successfully manipulate the control devices of the panel to solve a maintenance emergency problems. A demonstration of the successful implementation of the algorithms on our HERMIES-IIB autonomous robot for resolution of this scenario is presented. Conclusions are drawn concerning the applicability of the methodologies to more general classes of problems and implications for future work on sensor-driven reasoning for autonomous robots are discussed. 8 refs., 3 figs.« less

NeuroRex: A Clinical Neural Interface Roadmap for EEG-based Brain Machine Interfaces to a Lower Body Robotic Exoskeleton*

PubMed Central

Contreras-Vidal, Jose L.; Grossman, Robert G.

2013-01-01

In this communication, a translational clinical brain-machine interface (BMI) roadmap for an EEG-based BMI to a robotic exoskeleton (NeuroRex) is presented. This multi-faceted project addresses important engineering and clinical challenges: It addresses the validation of an intelligent, self-balancing, robotic lower-body and trunk exoskeleton (Rex) augmented with EEG-based BMI capabilities to interpret user intent to assist a mobility-impaired person to walk independently. The goal is to improve the quality of life and health status of wheelchair-bounded persons by enabling standing and sitting, walking and backing, turning, ascending and descending stairs/curbs, and navigating sloping surfaces in a variety of conditions without the need for additional support or crutches. PMID:24110003

FLEXnav: a fuzzy logic expert dead-reckoning system for the Segway RMP

NASA Astrophysics Data System (ADS)

Ojeda, Lauro; Raju, Mukunda; Borenstein, Johann

2004-09-01

Most mobile robots use a combination of absolute and relative sensing techniques for position estimation. Relative positioning techniques are generally known as dead-reckoning. Many systems use odometry as their only dead-reckoning means. However, in recent years fiber optic gyroscopes have become more affordable and are being used on many platforms to supplement odometry, especially in indoor applications. Still, if the terrain is not level (i.e., rugged or rolling terrain), the tilt of the vehicle introduces errors into the conversion of gyro readings to vehicle heading. In order to overcome this problem vehicle tilt must be measured and factored into the heading computation. A unique new mobile robot is the Segway Robotics Mobility Platform (RMP). This functionally close relative of the innovative Segway Human Transporter (HT) stabilizes a statically unstable single-axle robot dynamically, based on the principle of the inverted pendulum. While this approach works very well for human transportation, it introduces as unique set of challenges to navigation equipment using an onboard gyro. This is due to the fact that in operation the Segway RMP constantly changes its forward tilt, to prevent dynamically falling over. This paper introduces our new Fuzzy Logic Expert rule-based navigation (FLEXnav) method for fusing data from multiple gyroscopes and accelerometers in order to estimate accurately the attitude (i.e., heading and tilt) of a mobile robot. The attitude information is then further fused with wheel encoder data to estimate the three-dimensional position of the mobile robot. We have further extended this approach to include the special conditions of operation on the Segway RMP. The paper presents experimental results of a Segway RMP equipped with our system and running over moderately rugged terrain.

Self-supervised learning as an enabling technology for future space exploration robots: ISS experiments on monocular distance learning

NASA Astrophysics Data System (ADS)

van Hecke, Kevin; de Croon, Guido C. H. E.; Hennes, Daniel; Setterfield, Timothy P.; Saenz-Otero, Alvar; Izzo, Dario

2017-11-01

Although machine learning holds an enormous promise for autonomous space robots, it is currently not employed because of the inherent uncertain outcome of learning processes. In this article we investigate a learning mechanism, Self-Supervised Learning (SSL), which is very reliable and hence an important candidate for real-world deployment even on safety-critical systems such as space robots. To demonstrate this reliability, we introduce a novel SSL setup that allows a stereo vision equipped robot to cope with the failure of one of its cameras. The setup learns to estimate average depth using a monocular image, by using the stereo vision depths from the past as trusted ground truth. We present preliminary results from an experiment on the International Space Station (ISS) performed with the MIT/NASA SPHERES VERTIGO satellite. The presented experiments were performed on October 8th, 2015 on board the ISS. The main goals were (1) data gathering, and (2) navigation based on stereo vision. First the astronaut Kimiya Yui moved the satellite around the Japanese Experiment Module to gather stereo vision data for learning. Subsequently, the satellite freely explored the space in the module based on its (trusted) stereo vision system and a pre-programmed exploration behavior, while simultaneously performing the self-supervised learning of monocular depth estimation on board. The two main goals were successfully achieved, representing the first online learning robotic experiments in space. These results lay the groundwork for a follow-up experiment in which the satellite will use the learned single-camera depth estimation for autonomous exploration in the ISS, and are an advancement towards future space robots that continuously improve their navigation capabilities over time, even in harsh and completely unknown space environments.

AUV SLAM and Experiments Using a Mechanical Scanning Forward-Looking Sonar

PubMed Central

He, Bo; Liang, Yan; Feng, Xiao; Nian, Rui; Yan, Tianhong; Li, Minghui; Zhang, Shujing

2012-01-01

Navigation technology is one of the most important challenges in the applications of autonomous underwater vehicles (AUVs) which navigate in the complex undersea environment. The ability of localizing a robot and accurately mapping its surroundings simultaneously, namely the simultaneous localization and mapping (SLAM) problem, is a key prerequisite of truly autonomous robots. In this paper, a modified-FastSLAM algorithm is proposed and used in the navigation for our C-Ranger research platform, an open-frame AUV. A mechanical scanning imaging sonar is chosen as the active sensor for the AUV. The modified-FastSLAM implements the update relying on the on-board sensors of C-Ranger. On the other hand, the algorithm employs the data association which combines the single particle maximum likelihood method with modified negative evidence method, and uses the rank-based resampling to overcome the particle depletion problem. In order to verify the feasibility of the proposed methods, both simulation experiments and sea trials for C-Ranger are conducted. The experimental results show the modified-FastSLAM employed for the navigation of the C-Ranger AUV is much more effective and accurate compared with the traditional methods. PMID:23012549

AUV SLAM and experiments using a mechanical scanning forward-looking sonar.

PubMed

He, Bo; Liang, Yan; Feng, Xiao; Nian, Rui; Yan, Tianhong; Li, Minghui; Zhang, Shujing

2012-01-01

Navigation technology is one of the most important challenges in the applications of autonomous underwater vehicles (AUVs) which navigate in the complex undersea environment. The ability of localizing a robot and accurately mapping its surroundings simultaneously, namely the simultaneous localization and mapping (SLAM) problem, is a key prerequisite of truly autonomous robots. In this paper, a modified-FastSLAM algorithm is proposed and used in the navigation for our C-Ranger research platform, an open-frame AUV. A mechanical scanning imaging sonar is chosen as the active sensor for the AUV. The modified-FastSLAM implements the update relying on the on-board sensors of C-Ranger. On the other hand, the algorithm employs the data association which combines the single particle maximum likelihood method with modified negative evidence method, and uses the rank-based resampling to overcome the particle depletion problem. In order to verify the feasibility of the proposed methods, both simulation experiments and sea trials for C-Ranger are conducted. The experimental results show the modified-FastSLAM employed for the navigation of the C-Ranger AUV is much more effective and accurate compared with the traditional methods.

Open core control software for surgical robots

PubMed Central

Kozuka, Hiroaki; Kim, Hyung Wook; Takesue, Naoyuki; Vladimirov, B.; Sakaguchi, Masamichi; Tokuda, Junichi; Hata, Nobuhiko; Chinzei, Kiyoyuki; Fujimoto, Hideo

2010-01-01

Object In these days, patients and doctors in operation room are surrounded by many medical devices as resulting from recent advancement of medical technology. However, these cutting-edge medical devices are working independently and not collaborating with each other, even though the collaborations between these devices such as navigation systems and medical imaging devices are becoming very important for accomplishing complex surgical tasks (such as a tumor removal procedure while checking the tumor location in neurosurgery). On the other hand, several surgical robots have been commercialized, and are becoming common. However, these surgical robots are not open for collaborations with external medical devices in these days. A cutting-edge “intelligent surgical robot” will be possible in collaborating with surgical robots, various kinds of sensors, navigation system and so on. On the other hand, most of the academic software developments for surgical robots are “home-made” in their research institutions and not open to the public. Therefore, open source control software for surgical robots can be beneficial in this field. From these perspectives, we developed Open Core Control software for surgical robots to overcome these challenges. Materials and methods In general, control softwares have hardware dependencies based on actuators, sensors and various kinds of internal devices. Therefore, these control softwares cannot be used on different types of robots without modifications. However, the structure of the Open Core Control software can be reused for various types of robots by abstracting hardware dependent parts. In addition, network connectivity is crucial for collaboration between advanced medical devices. The OpenIGTLink is adopted in Interface class which plays a role to communicate with external medical devices. At the same time, it is essential to maintain the stable operation within the asynchronous data transactions through network. In the Open Core Control software, several techniques for this purpose were introduced. Virtual fixture is well known technique as a “force guide” for supporting operators to perform precise manipulation by using a master–slave robot. The virtual fixture for precise and safety surgery was implemented on the system to demonstrate an idea of high-level collaboration between a surgical robot and a navigation system. The extension of virtual fixture is not a part of the Open Core Control system, however, the function such as virtual fixture cannot be realized without a tight collaboration between cutting-edge medical devices. By using the virtual fixture, operators can pre-define an accessible area on the navigation system, and the area information can be transferred to the robot. In this manner, the surgical console generates the reflection force when the operator tries to get out from the pre-defined accessible area during surgery. Results The Open Core Control software was implemented on a surgical master–slave robot and stable operation was observed in a motion test. The tip of the surgical robot was displayed on a navigation system by connecting the surgical robot with a 3D position sensor through the OpenIGTLink. The accessible area was pre-defined before the operation, and the virtual fixture was displayed as a “force guide” on the surgical console. In addition, the system showed stable performance in a duration test with network disturbance. Conclusion In this paper, a design of the Open Core Control software for surgical robots and the implementation of virtual fixture were described. The Open Core Control software was implemented on a surgical robot system and showed stable performance in high-level collaboration works. The Open Core Control software is developed to be a widely used platform of surgical robots. Safety issues are essential for control software of these complex medical devices. It is important to follow the global specifications such as a FDA requirement “General Principles of Software Validation” or IEC62304. For following these regulations, it is important to develop a self-test environment. Therefore, a test environment is now under development to test various interference in operation room such as a noise of electric knife by considering safety and test environment regulations such as ISO13849 and IEC60508. The Open Core Control software is currently being developed software in open-source manner and available on the Internet. A communization of software interface is becoming a major trend in this field. Based on this perspective, the Open Core Control software can be expected to bring contributions in this field. PMID:20033506

Magnetic resonance imaging compatible remote catheter navigation system with 3 degrees of freedom.

PubMed

Tavallaei, M A; Lavdas, M K; Gelman, D; Drangova, M

2016-08-01

To facilitate MRI-guided catheterization procedures, we present an MRI-compatible remote catheter navigation system that allows remote navigation of steerable catheters with 3 degrees of freedom. The system consists of a user interface (master), a robot (slave), and an ultrasonic motor control servomechanism. The interventionalist applies conventional motions (axial, radial and plunger manipulations) on an input catheter in the master unit; this user input is measured and used by the servomechanism to control a compact catheter manipulating robot, such that it replicates the interventionalist's input motion on the patient catheter. The performance of the system was evaluated in terms of MRI compatibility (SNR and artifact), feasibility of remote navigation under real-time MRI guidance, and motion replication accuracy. Real-time MRI experiments demonstrated that catheter was successfully navigated remotely to desired target references in all 3 degrees of freedom. The system had an absolute value error of [Formula: see text]1 mm in axial catheter motion replication over 30 mm of travel and [Formula: see text] for radial catheter motion replication over [Formula: see text]. The worst case SNR drop was observed to be [Formula: see text]3 %; the robot did not introduce any artifacts in the MR images. An MRI-compatible compact remote catheter navigation system has been developed that allows remote navigation of steerable catheters with 3 degrees of freedom. The proposed system allows for safe and accurate remote catheter navigation, within conventional closed-bore scanners, without degrading MR image quality.

Controlling robots in the home: Factors that affect the performance of novice robot operators.

PubMed

McGinn, Conor; Sena, Aran; Kelly, Kevin

2017-11-01

For robots to successfully integrate into everyday life, it is important that they can be effectively controlled by laypeople. However, the task of manually controlling mobile robots can be challenging due to demanding cognitive and sensorimotor requirements. This research explores the effect that the built environment has on the manual control of domestic service robots. In this study, a virtual reality simulation of a domestic robot control scenario was developed. The performance of fifty novice users was evaluated, and their subjective experiences recorded through questionnaires. Through quantitative and qualitative analysis, it was found that untrained operators frequently perform poorly at navigation-based robot control tasks. The study found that passing through doorways accounted for the largest number of collisions, and was consistently identified as a very difficult operation to perform. These findings suggest that homes and other human-orientated settings present significant challenges to robot control. Copyright © 2017 Elsevier Ltd. All rights reserved.

Wireless Cortical Brain-Machine Interface for Whole-Body Navigation in Primates

NASA Astrophysics Data System (ADS)

Rajangam, Sankaranarayani; Tseng, Po-He; Yin, Allen; Lehew, Gary; Schwarz, David; Lebedev, Mikhail A.; Nicolelis, Miguel A. L.

2016-03-01

Several groups have developed brain-machine-interfaces (BMIs) that allow primates to use cortical activity to control artificial limbs. Yet, it remains unknown whether cortical ensembles could represent the kinematics of whole-body navigation and be used to operate a BMI that moves a wheelchair continuously in space. Here we show that rhesus monkeys can learn to navigate a robotic wheelchair, using their cortical activity as the main control signal. Two monkeys were chronically implanted with multichannel microelectrode arrays that allowed wireless recordings from ensembles of premotor and sensorimotor cortical neurons. Initially, while monkeys remained seated in the robotic wheelchair, passive navigation was employed to train a linear decoder to extract 2D wheelchair kinematics from cortical activity. Next, monkeys employed the wireless BMI to translate their cortical activity into the robotic wheelchair’s translational and rotational velocities. Over time, monkeys improved their ability to navigate the wheelchair toward the location of a grape reward. The navigation was enacted by populations of cortical neurons tuned to whole-body displacement. During practice with the apparatus, we also noticed the presence of a cortical representation of the distance to reward location. These results demonstrate that intracranial BMIs could restore whole-body mobility to severely paralyzed patients in the future.

Markovian robots: Minimal navigation strategies for active particles

NASA Astrophysics Data System (ADS)

Nava, Luis Gómez; Großmann, Robert; Peruani, Fernando

2018-04-01

We explore minimal navigation strategies for active particles in complex, dynamical, external fields, introducing a class of autonomous, self-propelled particles which we call Markovian robots (MR). These machines are equipped with a navigation control system (NCS) that triggers random changes in the direction of self-propulsion of the robots. The internal state of the NCS is described by a Boolean variable that adopts two values. The temporal dynamics of this Boolean variable is dictated by a closed Markov chain—ensuring the absence of fixed points in the dynamics—with transition rates that may depend exclusively on the instantaneous, local value of the external field. Importantly, the NCS does not store past measurements of this value in continuous, internal variables. We show that despite the strong constraints, it is possible to conceive closed Markov chain motifs that lead to nontrivial motility behaviors of the MR in one, two, and three dimensions. By analytically reducing the complexity of the NCS dynamics, we obtain an effective description of the long-time motility behavior of the MR that allows us to identify the minimum requirements in the design of NCS motifs and transition rates to perform complex navigation tasks such as adaptive gradient following, detection of minima or maxima, or selection of a desired value in a dynamical, external field. We put these ideas in practice by assembling a robot that operates by the proposed minimalistic NCS to evaluate the robustness of MR, providing a proof of concept that is possible to navigate through complex information landscapes with such a simple NCS whose internal state can be stored in one bit. These ideas may prove useful for the engineering of miniaturized robots.

Optimal path planning for a mobile robot using cuckoo search algorithm

NASA Astrophysics Data System (ADS)

Mohanty, Prases K.; Parhi, Dayal R.

2016-03-01

The shortest/optimal path planning is essential for efficient operation of autonomous vehicles. In this article, a new nature-inspired meta-heuristic algorithm has been applied for mobile robot path planning in an unknown or partially known environment populated by a variety of static obstacles. This meta-heuristic algorithm is based on the levy flight behaviour and brood parasitic behaviour of cuckoos. A new objective function has been formulated between the robots and the target and obstacles, which satisfied the conditions of obstacle avoidance and target-seeking behaviour of robots present in the terrain. Depending upon the objective function value of each nest (cuckoo) in the swarm, the robot avoids obstacles and proceeds towards the target. The smooth optimal trajectory is framed with this algorithm when the robot reaches its goal. Some simulation and experimental results are presented at the end of the paper to show the effectiveness of the proposed navigational controller.

On-Board Perception System For Planetary Aerobot Balloon Navigation

NASA Technical Reports Server (NTRS)

Balaram, J.; Scheid, Robert E.; T. Salomon, Phil

1996-01-01

NASA's Jet Propulsion Laboratory is implementing the Planetary Aerobot Testbed to develop the technology needed to operate a robotic balloon aero-vehicle (Aerobot). This earth-based system would be the precursor for aerobots designed to explore Venus, Mars, Titan and other gaseous planetary bodies. The on-board perception system allows the aerobot to localize itself and navigate on a planet using information derived from a variety of celestial, inertial, ground-imaging, ranging, and radiometric sensors.

Evaluation of a completely robotized neurosurgical operating microscope.

PubMed

Kantelhardt, Sven R; Finke, Markus; Schweikard, Achim; Giese, Alf

2013-01-01

Operating microscopes are essential for most neurosurgical procedures. Modern robot-assisted controls offer new possibilities, combining the advantages of conventional and automated systems. We evaluated the prototype of a completely robotized operating microscope with an integrated optical coherence tomography module. A standard operating microscope was fitted with motors and control instruments, with the manual control mode and balance preserved. In the robot mode, the microscope was steered by a remote control that could be fixed to a surgical instrument. External encoders and accelerometers tracked microscope movements. The microscope was additionally fitted with an optical coherence tomography-scanning module. The robotized microscope was tested on model systems. It could be freely positioned, without forcing the surgeon to take the hands from the instruments or avert the eyes from the oculars. Positioning error was about 1 mm, and vibration faded in 1 second. Tracking of microscope movements, combined with an autofocus function, allowed determination of the focus position within the 3-dimensional space. This constituted a second loop of navigation independent from conventional infrared reflector-based techniques. In the robot mode, automated optical coherence tomography scanning of large surface areas was feasible. The prototype of a robotized optical coherence tomography-integrated operating microscope combines the advantages of a conventional manually controlled operating microscope with a remote-controlled positioning aid and a self-navigating microscope system that performs automated positioning tasks such as surface scans. This demonstrates that, in the future, operating microscopes may be used to acquire intraoperative spatial data, volume changes, and structural data of brain or brain tumor tissue.

Single-site access robot-assisted epicardial mapping with a snake robot: preparation and first clinical experience.

PubMed

Neuzil, Petr; Cerny, Stepan; Kralovec, Stepan; Svanidze, Oleg; Bohuslavek, Jan; Plasil, Petr; Jehlicka, Pavel; Holy, Frantisek; Petru, Jan; Kuenzler, Richard; Sediva, Lucie

2013-06-01

CardioARM, a highly flexible "snakelike" medical robotic system (Medrobotics, Raynham, MA), has been developed to allow physicians to view, access, and perform complex procedures intrapericardially on the beating heart through a single-access port. Transthoracic epicardial catheter mapping and ablation has emerged as a strategy to treat arrhythmias, particularly ventricular arrhythmias, originating from the epicardial surface. The aim of our investigation was to determine whether the CardioARM could be used to diagnose and treat ventricular tachycardia (VT) of epicardial origin. Animal and clinical studies of the CardioARM flexible robot were performed in hybrid surgical-electrophysiology settings. In a porcine model study, single-port pericardial access, navigation, mapping, and ablation were performed in nine animals. The device was then used in a small, single-center feasibility clinical study. Three patients, all with drug-refractory VT and multiple failed endocardial ablation attempts, underwent epicardial mapping with the flexible robot. In all nine animals, navigation, mapping, and ablation were successful without hemodynamic compromise. In the human study, all three patients demonstrated a favorable safety profile, with no major adverse events through a 30-day follow-up. Two cases achieved technical success, in which an electroanatomic map of the epicardial ventricle surface was created; in the third case, blood obscured visualization. These results, although based on a limited number of experimental animals and patients, show promise and suggest that further clinical investigation on the use of the flexible robot in patients requiring epicardial mapping of VT is warranted.

A Sustained Proximity Network for Multi-Mission Lunar Exploration

NASA Technical Reports Server (NTRS)

Soloff, Jason A.; Noreen, Gary; Deutsch, Leslie; Israel, David

2005-01-01

Tbe Vision for Space Exploration calls for an aggressive sequence of robotic missions beginning in 2008 to prepare for a human return to the Moon by 2020, with the goal of establishing a sustained human presence beyond low Earth orbit. A key enabler of exploration is reliable, available communication and navigation capabilities to support both human and robotic missions. An adaptable, sustainable communication and navigation architecture has been developed by Goddard Space Flight Center and the Jet Propulsion Laboratory to support human and robotic lunar exploration through the next two decades. A key component of the architecture is scalable deployment, with the infrastructure evolving as needs emerge, allowing NASA and its partner agencies to deploy an interoperable communication and navigation system in an evolutionary way, enabling cost effective, highly adaptable systems throughout the lunar exploration program.

Future View: Web Navigation based on Learning User's Browsing Strategy

NASA Astrophysics Data System (ADS)

Nagino, Norikatsu; Yamada, Seiji

In this paper, we propose a Future View system that assists user's usual Web browsing. The Future View will prefetch Web pages based on user's browsing strategies and present them to a user in order to assist Web browsing. To learn user's browsing strategy, the Future View uses two types of learning classifier systems: a content-based classifier system for contents change patterns and an action-based classifier system for user's action patterns. The results of learning is applied to crawling by Web robots, and the gathered Web pages are presented to a user through a Web browser interface. We experimentally show effectiveness of navigation using the Future View.

A GPU-accelerated cortical neural network model for visually guided robot navigation.

PubMed

Beyeler, Michael; Oros, Nicolas; Dutt, Nikil; Krichmar, Jeffrey L

2015-12-01

Humans and other terrestrial animals use vision to traverse novel cluttered environments with apparent ease. On one hand, although much is known about the behavioral dynamics of steering in humans, it remains unclear how relevant perceptual variables might be represented in the brain. On the other hand, although a wealth of data exists about the neural circuitry that is concerned with the perception of self-motion variables such as the current direction of travel, little research has been devoted to investigating how this neural circuitry may relate to active steering control. Here we present a cortical neural network model for visually guided navigation that has been embodied on a physical robot exploring a real-world environment. The model includes a rate based motion energy model for area V1, and a spiking neural network model for cortical area MT. The model generates a cortical representation of optic flow, determines the position of objects based on motion discontinuities, and combines these signals with the representation of a goal location to produce motor commands that successfully steer the robot around obstacles toward the goal. The model produces robot trajectories that closely match human behavioral data. This study demonstrates how neural signals in a model of cortical area MT might provide sufficient motion information to steer a physical robot on human-like paths around obstacles in a real-world environment, and exemplifies the importance of embodiment, as behavior is deeply coupled not only with the underlying model of brain function, but also with the anatomical constraints of the physical body it controls. Copyright © 2015 Elsevier Ltd. All rights reserved.

Merge Fuzzy Visual Servoing and GPS-Based Planning to Obtain a Proper Navigation Behavior for a Small Crop-Inspection Robot.

PubMed

Bengochea-Guevara, José M; Conesa-Muñoz, Jesus; Andújar, Dionisio; Ribeiro, Angela

2016-02-24

The concept of precision agriculture, which proposes farming management adapted to crop variability, has emerged in recent years. To effectively implement precision agriculture, data must be gathered from the field in an automated manner at minimal cost. In this study, a small autonomous field inspection vehicle was developed to minimise the impact of the scouting on the crop and soil compaction. The proposed approach integrates a camera with a GPS receiver to obtain a set of basic behaviours required of an autonomous mobile robot to inspect a crop field with full coverage. A path planner considered the field contour and the crop type to determine the best inspection route. An image-processing method capable of extracting the central crop row under uncontrolled lighting conditions in real time from images acquired with a reflex camera positioned on the front of the robot was developed. Two fuzzy controllers were also designed and developed to achieve vision-guided navigation. A method for detecting the end of a crop row using camera-acquired images was developed. In addition, manoeuvres necessary for the robot to change rows were established. These manoeuvres enabled the robot to autonomously cover the entire crop by following a previously established plan and without stepping on the crop row, which is an essential behaviour for covering crops such as maize without damaging them.

Merge Fuzzy Visual Servoing and GPS-Based Planning to Obtain a Proper Navigation Behavior for a Small Crop-Inspection Robot

PubMed Central

Bengochea-Guevara, José M.; Conesa-Muñoz, Jesus; Andújar, Dionisio; Ribeiro, Angela

2016-01-01

The concept of precision agriculture, which proposes farming management adapted to crop variability, has emerged in recent years. To effectively implement precision agriculture, data must be gathered from the field in an automated manner at minimal cost. In this study, a small autonomous field inspection vehicle was developed to minimise the impact of the scouting on the crop and soil compaction. The proposed approach integrates a camera with a GPS receiver to obtain a set of basic behaviours required of an autonomous mobile robot to inspect a crop field with full coverage. A path planner considered the field contour and the crop type to determine the best inspection route. An image-processing method capable of extracting the central crop row under uncontrolled lighting conditions in real time from images acquired with a reflex camera positioned on the front of the robot was developed. Two fuzzy controllers were also designed and developed to achieve vision-guided navigation. A method for detecting the end of a crop row using camera-acquired images was developed. In addition, manoeuvres necessary for the robot to change rows were established. These manoeuvres enabled the robot to autonomously cover the entire crop by following a previously established plan and without stepping on the crop row, which is an essential behaviour for covering crops such as maize without damaging them. PMID:26927102

Experiments with a small behaviour controlled planetary rover

NASA Technical Reports Server (NTRS)

Miller, David P.; Desai, Rajiv S.; Gat, Erann; Ivlev, Robert; Loch, John

1993-01-01

A series of experiments that were performed on the Rocky 3 robot is described. Rocky 3 is a small autonomous rover capable of navigating through rough outdoor terrain to a predesignated area, searching that area for soft soil, acquiring a soil sample, and depositing the sample in a container at its home base. The robot is programmed according to a reactive behavior control paradigm using the ALFA programming language. This style of programming produces robust autonomous performance while requiring significantly less computational resources than more traditional mobile robot control systems. The code for Rocky 3 runs on an eight bit processor and uses about ten k of memory.

Event detection and localization for small mobile robots using reservoir computing.

PubMed

Antonelo, E A; Schrauwen, B; Stroobandt, D

2008-08-01

Reservoir Computing (RC) techniques use a fixed (usually randomly created) recurrent neural network, or more generally any dynamic system, which operates at the edge of stability, where only a linear static readout output layer is trained by standard linear regression methods. In this work, RC is used for detecting complex events in autonomous robot navigation. This can be extended to robot localization tasks which are solely based on a few low-range, high-noise sensory data. The robot thus builds an implicit map of the environment (after learning) that is used for efficient localization by simply processing the input stream of distance sensors. These techniques are demonstrated in both a simple simulation environment and in the physically realistic Webots simulation of the commercially available e-puck robot, using several complex and even dynamic environments.

Coordinating teams of autonomous vehicles: an architectural perspective

NASA Astrophysics Data System (ADS)

Czichon, Cary; Peterson, Robert W.; Mettala, Erik G.; Vondrak, Ivo

2005-05-01

In defense-related robotics research, a mission level integration gap exists between mission tasks (tactical) performed by ground, sea, or air applications and elementary behaviors enacted by processing, communications, sensors, and weaponry resources (platform specific). The gap spans ensemble (heterogeneous team) behaviors, automatic MOE/MOP tracking, and tactical task modeling/simulation for virtual and mixed teams comprised of robotic and human combatants. This study surveys robotic system architectures, compares approaches for navigating problem/state spaces by autonomous systems, describes an architecture for an integrated, repository-based modeling, simulation, and execution environment, and outlines a multi-tiered scheme for robotic behavior components that is agent-based, platform-independent, and extendable via plug-ins. Tools for this integrated environment, along with a distributed agent framework for collaborative task performance are being developed by a U.S. Army funded SBIR project (RDECOM Contract N61339-04-C-0005).

Behavioral Mapless Navigation Using Rings

NASA Technical Reports Server (NTRS)

Monroe, Randall P.; Miller, Samuel A.; Bradley, Arthur T.

2012-01-01

This paper presents work on the development and implementation of a novel approach to robotic navigation. In this system, map-building and localization for obstacle avoidance are discarded in favor of moment-by-moment behavioral processing of the sonar sensor data. To accomplish this, we developed a network of behaviors that communicate through the passing of rings, data structures that are similar in form to the sonar data itself and express the decisions of each behavior. Through the use of these rings, behaviors can moderate each other, conflicting impulses can be mediated, and designers can easily connect modules to create complex emergent navigational techniques. We discuss the development of a number of these modules and their successful use as a navigation system in the Trinity omnidirectional robot.

SPHERES Vertigo

NASA Image and Video Library

2014-07-25

ISS040-E-079083 (25 July 2014) --- In the International Space Station?s Kibo laboratory, NASA astronaut Steve Swanson, Expedition 40 commander, enters data in a computer in preparation for a session with a trio of soccer-ball-sized robots known as the Synchronized Position Hold, Engage, Reorient, Experimental Satellites, or SPHERES. The free-flying robots were equipped with stereoscopic goggles called the Visual Estimation and Relative Tracking for Inspection of Generic Objects, or VERTIGO, to enable the SPHERES to perform relative navigation based on a 3D model of a target object.

SPHERES-Vertigo experiment

NASA Image and Video Library

2014-07-25

ISS040-E-080130 (25 July 2014) --- In the International Space Station?s Kibo laboratory, European Space Agency astronaut Alexander Gerst, Expedition 40 flight engineer, conducts a session with a trio of soccer-ball-sized robots known as the Synchronized Position Hold, Engage, Reorient, Experimental Satellites, or SPHERES. The free-flying robots were equipped with stereoscopic goggles called the Visual Estimation and Relative Tracking for Inspection of Generic Objects, or VERTIGO, to enable the SPHERES to perform relative navigation based on a 3D model of a target object.

Research in free-flying robots and flexible manipulators at the Stanford Aerospace Robotics Laboratory

NASA Technical Reports Server (NTRS)

Ballhaus, W. L.; Alder, L. J.; Chen, V. W.; Dickson, W. C.; Ullman, M. A.; Wilson, E.

1993-01-01

Over the last ten years, the Stanford Aerospace Robotics Laboratory (ARL) has developed a hardware facility in which a number of space robotics issues have been, and continue to be addressed. This paper reviews two of the current ARL research areas: navigation and control of free flying space robots, and modeling and control of extremely flexible space structures.

Obstacle Classification and 3D Measurement in Unstructured Environments Based on ToF Cameras

PubMed Central

Yu, Hongshan; Zhu, Jiang; Wang, Yaonan; Jia, Wenyan; Sun, Mingui; Tang, Yandong

2014-01-01

Inspired by the human 3D visual perception system, we present an obstacle detection and classification method based on the use of Time-of-Flight (ToF) cameras for robotic navigation in unstructured environments. The ToF camera provides 3D sensing by capturing an image along with per-pixel 3D space information. Based on this valuable feature and human knowledge of navigation, the proposed method first removes irrelevant regions which do not affect robot's movement from the scene. In the second step, regions of interest are detected and clustered as possible obstacles using both 3D information and intensity image obtained by the ToF camera. Consequently, a multiple relevance vector machine (RVM) classifier is designed to classify obstacles into four possible classes based on the terrain traversability and geometrical features of the obstacles. Finally, experimental results in various unstructured environments are presented to verify the robustness and performance of the proposed approach. We have found that, compared with the existing obstacle recognition methods, the new approach is more accurate and efficient. PMID:24945679

Sample Return Robot Centennial Challenge

NASA Image and Video Library

2012-06-16

NASA Deputy Administrator Lori Garver, left, listens as Worcester Polytechnic Institute (WPI) Robotics Resource Center Director and NASA-WPI Sample Return Robot Centennial Challenge Judge Ken Stafford points out how the robots navigate the playing field during the challenge on Saturday, June 16, 2012 in Worcester, Mass. Teams were challenged to build autonomous robots that can identify, collect and return samples. NASA needs autonomous robotic capability for future planetary exploration. Photo Credit: (NASA/Bill Ingalls)

Sample Return Robot Centennial Challenge

NASA Image and Video Library

2012-06-16

NASA Deputy Administrator Lori Garver, right, listens as Worcester Polytechnic Institute (WPI) Robotics Resource Center Director and NASA-WPI Sample Return Robot Centennial Challenge Judge Ken Stafford points out how the robots navigate the playing field during the challenge on Saturday, June 16, 2012 in Worcester, Mass. Teams were challenged to build autonomous robots that can identify, collect and return samples. NASA needs autonomous robotic capability for future planetary exploration. Photo Credit: (NASA/Bill Ingalls)

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.

A Case Study on a Capsule Robot in the Gastrointestinal Tract to Teach Robot Programming and Navigation

ERIC Educational Resources Information Center

Guo, Yi; Zhang, Shubo; Ritter, Arthur; Man, Hong

2014-01-01

Despite the increasing importance of robotics, there is a significant challenge involved in teaching this to undergraduate students in biomedical engineering (BME) and other related disciplines in which robotics techniques could be readily applied. This paper addresses this challenge through the development and pilot testing of a bio-microrobotics…

Under-vehicle autonomous inspection through undercarriage signatures

NASA Astrophysics Data System (ADS)

Schoenherr, Edward; Smuda, Bill

2005-05-01

Increased threats to gate security have caused recent need for improved vehicle inspection methods at security checkpoints in various fields of defense and security. A fast, reliable system of under-vehicle inspection that detects possibly harmful or unwanted materials hidden on vehicle undercarriages and notifies the user of the presence of these materials while allowing the user a safe standoff distance from the inspection site is desirable. An autonomous under-vehicle inspection system would provide for this. The proposed system would function as follows: A low-clearance tele-operated robotic platform would be equipped with sonar/laser range finding sensors as well as a video camera. As a vehicle to be inspected enters a checkpoint, the robot would autonomously navigate under the vehicle, using algorithms to detect tire locations for weigh points. During this navigation, data would be collected from the sonar/laser range finding hardware. This range data would be used to compile an impression of the vehicle undercarriage. Once this impression is complete, the system would compare it to a database of pre-scanned undercarriage impressions. Based on vehicle makes and models, any variance between the undercarriage being inspected and the impression compared against in the database would be marked as potentially threatening. If such variances exist, the robot would navigate to these locations and place the video camera in such a manner that the location in question can be viewed from a standoff position through a TV monitor. At this time, manual control of the robot navigation and camera control can be taken to imply further, more detailed inspection of the area/materials in question. After-market vehicle modifications would provide some difficulty, yet with enough pre-screening of such modifications, the system should still prove accurate. Also, impression scans that are taken in the field can be stored and tagged with a vehicles's license plate number, and future inspections of that vehicle can be compared to already screened and cleared impressions of the same vehicle in order to search for variance.

The Design and Development of an Omni-Directional Mobile Robot Oriented to an Intelligent Manufacturing System

PubMed Central

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

The Design and Development of an Omni-Directional Mobile Robot Oriented to an Intelligent Manufacturing System.

PubMed

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.

Vision-based semi-autonomous outdoor robot system to reduce soldier workload

NASA Astrophysics Data System (ADS)

Richardson, Al; Rodgers, Michael H.

2001-09-01

Sensors and computational capability have not reached the point to enable small robots to navigate autonomously in unconstrained outdoor environments at tactically useful speeds. This problem is greatly reduced, however, if a soldier can lead the robot through terrain that he knows it can traverse. An application of this concept is a small pack-mule robot that follows a foot soldier over outdoor terrain. The solder would be responsible to avoid situations beyond the robot's limitations when encountered. Having learned the route, the robot could autonomously retrace the path carrying supplies and munitions. This would greatly reduce the soldier's workload under normal conditions. This paper presents a description of a developmental robot sensor system using low-cost commercial 3D vision and inertial sensors to address this application. The robot moves at fast walking speed and requires only short-range perception to accomplish its task. 3D-feature information is recorded on a composite route map that the robot uses to negotiate its local environment and retrace the path taught by the soldier leader.

Depth estimation of features in video frames with improved feature matching technique using Kinect sensor

NASA Astrophysics Data System (ADS)

Sharma, Kajal; Moon, Inkyu; Kim, Sung Gaun

2012-10-01

Estimating depth has long been a major issue in the field of computer vision and robotics. The Kinect sensor's active sensing strategy provides high-frame-rate depth maps and can recognize user gestures and human pose. This paper presents a technique to estimate the depth of features extracted from video frames, along with an improved feature-matching method. In this paper, we used the Kinect camera developed by Microsoft, which captured color and depth images for further processing. Feature detection and selection is an important task for robot navigation. Many feature-matching techniques have been proposed earlier, and this paper proposes an improved feature matching between successive video frames with the use of neural network methodology in order to reduce the computation time of feature matching. The features extracted are invariant to image scale and rotation, and different experiments were conducted to evaluate the performance of feature matching between successive video frames. The extracted features are assigned distance based on the Kinect technology that can be used by the robot in order to determine the path of navigation, along with obstacle detection applications.

An overview on real-time control schemes for wheeled mobile robot

NASA Astrophysics Data System (ADS)

Radzak, M. S. A.; Ali, M. A. H.; Sha’amri, S.; Azwan, A. R.

2018-04-01

The purpose of this paper is to review real-time control motion algorithms for wheeled mobile robot (WMR) when navigating in environment such as road. Its need a good controller to avoid collision with any disturbance and maintain a track error at zero level. The controllers are used with other aiding sensors to measure the WMR’s velocities, posture, and interference to estimate the required torque to be applied on the wheels of mobile robot. Four main categories for wheeled mobile robot control systems have been found in literature which are namely: Kinematic based controller, Dynamic based controllers, artificial intelligence based control system, and Active Force control. A MATLAB/Simulink software is the main software to simulate and implement the control system. The real-time toolbox in MATLAB/SIMULINK are used to receive/send data from sensors/to actuator with presence of disturbances, however others software such C, C++ and visual basic are rare to be used.

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).

Soldier-Robot Team Communication: An Investigation of Exogenous Orienting Visual Display Cues and Robot Reporting Preferences

DTIC Science & Technology

2018-02-12

usability preference. Results under the second focus showed that the frequency with which participants expected status updates differed depending upon the...assistance requests for both navigational route and building selection depending on the type of exogenous visual cues displayed? 3) Is there a difference...in response time to visual reports for both navigational route and building selection depending on the type of exogenous visual cues displayed? 4

Goal-oriented robot navigation learning using a multi-scale space representation.

PubMed

Llofriu, M; Tejera, G; Contreras, M; Pelc, T; Fellous, J M; Weitzenfeld, A

2015-12-01

There has been extensive research in recent years on the multi-scale nature of hippocampal place cells and entorhinal grid cells encoding which led to many speculations on their role in spatial cognition. In this paper we focus on the multi-scale nature of place cells and how they contribute to faster learning during goal-oriented navigation when compared to a spatial cognition system composed of single scale place cells. The task consists of a circular arena with a fixed goal location, in which a robot is trained to find the shortest path to the goal after a number of learning trials. Synaptic connections are modified using a reinforcement learning paradigm adapted to the place cells multi-scale architecture. The model is evaluated in both simulation and physical robots. We find that larger scale and combined multi-scale representations favor goal-oriented navigation task learning. Copyright © 2015 Elsevier Ltd. All rights reserved.

Augmented reality and image overlay navigation with OsiriX in laparoscopic and robotic surgery: not only a matter of fashion.

PubMed

Volonté, Francesco; Pugin, François; Bucher, Pascal; Sugimoto, Maki; Ratib, Osman; Morel, Philippe

2011-07-01

New technologies can considerably improve preoperative planning, enhance the surgeon's skill and simplify the approach to complex procedures. Augmented reality techniques, robot assisted operations and computer assisted navigation tools will become increasingly important in surgery and in residents' education. We obtained 3D reconstructions from simple spiral computed tomography (CT) slides using OsiriX, an open source processing software package dedicated to DICOM images. These images were then projected on the patient's body with a beamer fixed to the operating table to enhance spatial perception during surgical intervention (augmented reality). Changing a window's deepness level allowed the surgeon to navigate through the patient's anatomy, highlighting regions of interest and marked pathologies. We used image overlay navigation for laparoscopic operations such cholecystectomy, abdominal exploration, distal pancreas resection and robotic liver resection. Augmented reality techniques will transform the behaviour of surgeons, making surgical interventions easier, faster and probably safer. These new techniques will also renew methods of surgical teaching, facilitating transmission of knowledge and skill to young surgeons.

Virtual modeling of robot-assisted manipulations in abdominal surgery.

PubMed

Berelavichus, Stanislav V; Karmazanovsky, Grigory G; Shirokov, Vadim S; Kubyshkin, Valeriy A; Kriger, Andrey G; Kondratyev, Evgeny V; Zakharova, Olga P

2012-06-27

To determine the effectiveness of using multidetector computed tomography (MDCT) data in preoperative planning of robot-assisted surgery. Fourteen patients indicated for surgery underwent MDCT using 64 and 256-slice MDCT. Before the examination, a specially constructed navigation net was placed on the patient's anterior abdominal wall. Processing of MDCT data was performed on a Brilliance Workspace 4 (Philips). Virtual vectors that imitate robotic and assistant ports were placed on the anterior abdominal wall of the 3D model of the patient, considering the individual anatomy of the patient and the technical capabilities of robotic arms. Sites for location of the ports were directed by projection on the roentgen-positive tags of the navigation net. There were no complications observed during surgery or in the post-operative period. We were able to reduce robotic arm interference during surgery. The surgical area was optimal for robotic and assistant manipulators without any need for reinstallation of the trocars. This method allows modeling of the main steps in robot-assisted intervention, optimizing operation of the manipulator and lowering the risk of injuries to internal organs.

Evaluation of parallel reduction strategies for fusion of sensory information from a robot team

NASA Astrophysics Data System (ADS)

Lyons, Damian M.; Leroy, Joseph

2015-05-01

The advantage of using a team of robots to search or to map an area is that by navigating the robots to different parts of the area, searching or mapping can be completed more quickly. A crucial aspect of the problem is the combination, or fusion, of data from team members to generate an integrated model of the search/mapping area. In prior work we looked at the issue of removing mutual robots views from an integrated point cloud model built from laser and stereo sensors, leading to a cleaner and more accurate model. This paper addresses a further challenge: Even with mutual views removed, the stereo data from a team of robots can quickly swamp a WiFi connection. This paper proposes and evaluates a communication and fusion approach based on the parallel reduction operation, where data is combined in a series of steps of increasing subsets of the team. Eight different strategies for selecting the subsets are evaluated for bandwidth requirements using three robot missions, each carried out with teams of four Pioneer 3-AT robots. Our results indicate that selecting groups to combine based on similar pose but distant location yields the best results.

Development of the first force-controlled robot for otoneurosurgery.

PubMed

Federspil, Philipp A; Geisthoff, Urban W; Henrich, Dominik; Plinkert, Peter K

2003-03-01

In some surgical specialties (eg, orthopedics), robots are already used in the operating room for bony milling work. Otological surgery and otoneurosurgery may also greatly benefit from the enhanced precision of robotics. Experimental study on robotic milling of oak wood and human temporal bone specimen. A standard industrial robot with a six-degrees-of-freedom serial kinematics was used, with force feedback to proportionally control the robot speed. Different milling modes and characteristic path parameters were evaluated to generate milling paths based on computer-aided design (CAD) geometry data of a cochlear implant and an implantable hearing system. The best-suited strategy proved to be the spiral horizontal milling mode with the burr held perpendicular to the temporal bone surface. To reduce groove height, the distance between paths should equal half the radius of the cutting burr head. Because of the vibration of the robot's own motors, a high oscillation of the SD of forces was encountered. This oscillation dropped drastically to nearly 0 Newton (N) when the burr head made contact with the dura mater, because of its damping characteristics. The cutting burr could be kept in contact with the dura mater for an extended period without damaging it, because of the burr's blunt head form. The robot moved the burr smoothly according to the encountered resistances. The study reports the first development of a functional robotic milling procedure for otoneurosurgery with force-based speed control. Future plans include implementation of ultrasound-based local navigation and performance of robotic mastoidectomy.

Navigation within the heart and vessels in clinical practice.

PubMed

Beyar, Rafael

2010-02-01

The field of interventional cardiology has developed at an unprecedented pace on account of the visual and imaging power provided by constantly improving biomedical technologies. Transcatheter-based technology is now routinely used for coronary revascularization and noncoronary interventions using balloon angioplasty, stents, and many other devices. In the early days of interventional practice, the operating physician had to manually navigate catheters and devices under fluoroscopic imaging and was exposed to radiation, with its comcomitant necessity for wearing heavy lead aprons for protection. Until recently, very little has changed in the way procedures have been carried out in the catheterization laboratory. The technological capacity to remotely manipulate devices, using robotic arms and computational tools, has been developed for surgery and other medical procedures. This has brought to practice the powerful combination of the abilities afforded by imaging, navigational tools, and remote control manipulation. This review covers recent developments in navigational tools for catheter positioning, electromagnetic mapping, magnetic resonance imaging (MRI)-based cardiac electrophysiological interventions, and navigation tools through coronary arteries.

Real-time adaptive off-road vehicle navigation and terrain classification

NASA Astrophysics Data System (ADS)

Muller, Urs A.; Jackel, Lawrence D.; LeCun, Yann; Flepp, Beat

2013-05-01

We are developing a complete, self-contained autonomous navigation system for mobile robots that learns quickly, uses commodity components, and has the added benefit of emitting no radiation signature. It builds on the au­tonomous navigation technology developed by Net-Scale and New York University during the Defense Advanced Research Projects Agency (DARPA) Learning Applied to Ground Robots (LAGR) program and takes advantage of recent scientific advancements achieved during the DARPA Deep Learning program. In this paper we will present our approach and algorithms, show results from our vision system, discuss lessons learned from the past, and present our plans for further advancing vehicle autonomy.

Robust Planning for Autonomous Navigation of Mobile Robots in Unstructured, Dynamic Environments: An LDRD Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

EISLER, G. RICHARD

This report summarizes the analytical and experimental efforts for the Laboratory Directed Research and Development (LDRD) project entitled ''Robust Planning for Autonomous Navigation of Mobile Robots In Unstructured, Dynamic Environments (AutoNav)''. The project goal was to develop an algorithmic-driven, multi-spectral approach to point-to-point navigation characterized by: segmented on-board trajectory planning, self-contained operation without human support for mission duration, and the development of appropriate sensors and algorithms to navigate unattended. The project was partially successful in achieving gains in sensing, path planning, navigation, and guidance. One of three experimental platforms, the Minimalist Autonomous Testbed, used a repetitive sense-and-re-plan combination to demonstratemore » the majority of elements necessary for autonomous navigation. However, a critical goal for overall success in arbitrary terrain, that of developing a sensor that is able to distinguish true obstacles that need to be avoided as a function of vehicle scale, still needs substantial research to bring to fruition.« less

Evaluation of a novel flexible snake robot for endoluminal surgery.

PubMed

Patel, Nisha; Seneci, Carlo A; Shang, Jianzhong; Leibrandt, Konrad; Yang, Guang-Zhong; Darzi, Ara; Teare, Julian

2015-11-01

Endoluminal therapeutic procedures such as endoscopic submucosal dissection are increasingly attractive given the shift in surgical paradigm towards minimally invasive surgery. This novel three-channel articulated robot was developed to overcome the limitations of the flexible endoscope which poses a number of challenges to endoluminal surgery. The device enables enhanced movement in a restricted workspace, with improved range of motion and with the accuracy required for endoluminal surgery. To evaluate a novel flexible robot for therapeutic endoluminal surgery. Bench-top studies. Research laboratory. Targeting and navigation tasks of the robot were performed to explore the range of motion and retroflexion capabilities. Complex endoluminal tasks such as endoscopic mucosal resection were also simulated. Successful completion, accuracy and time to perform the bench-top tasks were the main outcome measures. The robot ranges of movement, retroflexion and navigation capabilities were demonstrated. The device showed significantly greater accuracy of targeting in a retroflexed position compared to a conventional endoscope. Bench-top study and small study sample. We were able to demonstrate a number of simulated endoscopy tasks such as navigation, targeting, snaring and retroflexion. The improved accuracy of targeting whilst in a difficult configuration is extremely promising and may facilitate endoluminal surgery which has been notoriously challenging with a conventional endoscope.

The impact of goal-oriented task design on neurofeedback learning for brain-computer interface control.

PubMed

McWhinney, S R; Tremblay, A; Boe, S G; Bardouille, T

2018-02-01

Neurofeedback training teaches individuals to modulate brain activity by providing real-time feedback and can be used for brain-computer interface control. The present study aimed to optimize training by maximizing engagement through goal-oriented task design. Participants were shown either a visual display or a robot, where each was manipulated using motor imagery (MI)-related electroencephalography signals. Those with the robot were instructed to quickly navigate grid spaces, as the potential for goal-oriented design to strengthen learning was central to our investigation. Both groups were hypothesized to show increased magnitude of these signals across 10 sessions, with the greatest gains being seen in those navigating the robot due to increased engagement. Participants demonstrated the predicted increase in magnitude, with no differentiation between hemispheres. Participants navigating the robot showed stronger left-hand MI increases than those with the computer display. This is likely due to success being reliant on maintaining strong MI-related signals. While older participants showed stronger signals in early sessions, this trend later reversed, suggesting greater natural proficiency but reduced flexibility. These results demonstrate capacity for modulating neurofeedback using MI over a series of training sessions, using tasks of varied design. Importantly, the more goal-oriented robot control task resulted in greater improvements.

Virtual and Actual Humanoid Robot Control with Four-Class Motor-Imagery-Based Optical Brain-Computer Interface

PubMed Central

Kim, Youngmoo E.

2017-01-01

Motor-imagery tasks are a popular input method for controlling brain-computer interfaces (BCIs), partially due to their similarities to naturally produced motor signals. The use of functional near-infrared spectroscopy (fNIRS) in BCIs is still emerging and has shown potential as a supplement or replacement for electroencephalography. However, studies often use only two or three motor-imagery tasks, limiting the number of available commands. In this work, we present the results of the first four-class motor-imagery-based online fNIRS-BCI for robot control. Thirteen participants utilized upper- and lower-limb motor-imagery tasks (left hand, right hand, left foot, and right foot) that were mapped to four high-level commands (turn left, turn right, move forward, and move backward) to control the navigation of a simulated or real robot. A significant improvement in classification accuracy was found between the virtual-robot-based BCI (control of a virtual robot) and the physical-robot BCI (control of the DARwIn-OP humanoid robot). Differences were also found in the oxygenated hemoglobin activation patterns of the four tasks between the first and second BCI. These results corroborate previous findings that motor imagery can be improved with feedback and imply that a four-class motor-imagery-based fNIRS-BCI could be feasible with sufficient subject training. PMID:28804712

Virtual and Actual Humanoid Robot Control with Four-Class Motor-Imagery-Based Optical Brain-Computer Interface.

PubMed

Batula, Alyssa M; Kim, Youngmoo E; Ayaz, Hasan

2017-01-01

Motor-imagery tasks are a popular input method for controlling brain-computer interfaces (BCIs), partially due to their similarities to naturally produced motor signals. The use of functional near-infrared spectroscopy (fNIRS) in BCIs is still emerging and has shown potential as a supplement or replacement for electroencephalography. However, studies often use only two or three motor-imagery tasks, limiting the number of available commands. In this work, we present the results of the first four-class motor-imagery-based online fNIRS-BCI for robot control. Thirteen participants utilized upper- and lower-limb motor-imagery tasks (left hand, right hand, left foot, and right foot) that were mapped to four high-level commands (turn left, turn right, move forward, and move backward) to control the navigation of a simulated or real robot. A significant improvement in classification accuracy was found between the virtual-robot-based BCI (control of a virtual robot) and the physical-robot BCI (control of the DARwIn-OP humanoid robot). Differences were also found in the oxygenated hemoglobin activation patterns of the four tasks between the first and second BCI. These results corroborate previous findings that motor imagery can be improved with feedback and imply that a four-class motor-imagery-based fNIRS-BCI could be feasible with sufficient subject training.

Motion-adapted catheter navigation with real-time instantiation and improved visualisation

PubMed Central

Kwok, Ka-Wai; Wang, Lichao; Riga, Celia; Bicknell, Colin; Cheshire, Nicholas; Yang, Guang-Zhong

2014-01-01

The improvements to catheter manipulation by the use of robot-assisted catheter navigation for endovascular procedures include increased precision, stability of motion and operator comfort. However, navigation through the vasculature under fluoroscopic guidance is still challenging, mostly due to physiological motion and when tortuous vessels are involved. In this paper, we propose a motion-adaptive catheter navigation scheme based on shape modelling to compensate for these dynamic effects, permitting predictive and dynamic navigations. This allows for timed manipulations synchronised with the vascular motion. The technical contribution of the paper includes the following two aspects. Firstly, a dynamic shape modelling and real-time instantiation scheme based on sparse data obtained intra-operatively is proposed for improved visualisation of the 3D vasculature during endovascular intervention. Secondly, a reconstructed frontal view from the catheter tip using the derived dynamic model is used as an interventional aid to user guidance. To demonstrate the practical value of the proposed framework, a simulated aortic branch cannulation procedure is used with detailed user validation to demonstrate the improvement in navigation quality and efficiency. PMID:24744817

Collision-free motion planning for fiber positioner robots: discretization of velocity profiles

NASA Astrophysics Data System (ADS)

Makarem, Laleh; Kneib, Jean-Paul; Gillet, Denis; Bleuler, Hannes; Bouri, Mohamed; Hörler, Philippe; Jenni, Laurent; Prada, Francisco; Sánchez, Justo

2014-07-01

The next generation of large-scale spectroscopic survey experiments such as DESI, will use thousands of fiber positioner robots packed on a focal plate. In order to maximize the observing time with this robotic system we need to move in parallel the fiber-ends of all positioners from the previous to the next target coordinates. Direct trajectories are not feasible due to collision risks that could undeniably damage the robots and impact the survey operation and performance. We have previously developed a motion planning method based on a novel decentralized navigation function for collision-free coordination of fiber positioners. The navigation function takes into account the configuration of positioners as well as their envelope constraints. The motion planning scheme has linear complexity and short motion duration (2.5 seconds with the maximum speed of 30 rpm for the positioner), which is independent of the number of positioners. These two key advantages of the decentralization designate the method as a promising solution for the collision-free motion-planning problem in the next-generation of fiber-fed spectrographs. In a framework where a centralized computer communicates with the positioner robots, communication overhead can be reduced significantly by using velocity profiles consisting of a few bits only. We present here the discretization of velocity profiles to ensure the feasibility of a real-time coordination for a large number of positioners. The modified motion planning method that generates piecewise linearized position profiles guarantees collision-free trajectories for all the robots. The velocity profiles fit few bits at the expense of higher computational costs.

Building an environment model using depth information

NASA Technical Reports Server (NTRS)

Roth-Tabak, Y.; Jain, Ramesh

1989-01-01

Modeling the environment is one of the most crucial issues for the development and research of autonomous robot and tele-perception. Though the physical robot operates (navigates and performs various tasks) in the real world, any type of reasoning, such as situation assessment, planning or reasoning about action, is performed based on information in its internal world. Hence, the robot's intentional actions are inherently constrained by the models it has. These models may serve as interfaces between sensing modules and reasoning modules, or in the case of telerobots serve as interface between the human operator and the distant robot. A robot operating in a known restricted environment may have a priori knowledge of its whole possible work domain, which will be assimilated in its World Model. As the information in the World Model is relatively fixed, an Environment Model must be introduced to cope with the changes in the environment and to allow exploring entirely new domains. Introduced here is an algorithm that uses dense range data collected at various positions in the environment to refine and update or generate a 3-D volumetric model of an environment. The model, which is intended for autonomous robot navigation and tele-perception, consists of cubic voxels with the possible attributes: Void, Full, and Unknown. Experimental results from simulations of range data in synthetic environments are given. The quality of the results show great promise for dealing with noisy input data. The performance measures for the algorithm are defined, and quantitative results for noisy data and positional uncertainty are presented.

Precursors and adjuncts of a lunar base

NASA Technical Reports Server (NTRS)

Burke, J. D.

1988-01-01

The automated, teleoperated, robotic and human-tended subsystems which will precede and accompany a lunar base program are discussed. The information about lunar conditions that can be provided by such precursors and adjuncts is addressed. The use of precursors and adjuncts for communications and navigation, for safety and survival, for lunar archives, and for entertainment and leisure is examined.

Astrobee Guest Science

NASA Technical Reports Server (NTRS)

Barlow, Jonathan; Benavides, Jose; Provencher, Chris; Bualat, Maria; Smith, Marion F.; Mora Vargas, Andres

2017-01-01

At the end of 2017, Astrobee will launch three free-flying robots that will navigate the entire US segment of the ISS (International Space Station) and serve as a payload facility. These robots will provide guest science payloads with processor resources, space within the robot for physical attachment, power, communication, propulsion, and human interfaces.

Vision Sensor-Based Road Detection for Field Robot Navigation

PubMed Central

Lu, Keyu; Li, Jian; An, Xiangjing; He, Hangen

2015-01-01

Road detection is an essential component of field robot navigation systems. Vision sensors play an important role in road detection for their great potential in environmental perception. In this paper, we propose a hierarchical vision sensor-based method for robust road detection in challenging road scenes. More specifically, for a given road image captured by an on-board vision sensor, we introduce a multiple population genetic algorithm (MPGA)-based approach for efficient road vanishing point detection. Superpixel-level seeds are then selected in an unsupervised way using a clustering strategy. Then, according to the GrowCut framework, the seeds proliferate and iteratively try to occupy their neighbors. After convergence, the initial road segment is obtained. Finally, in order to achieve a globally-consistent road segment, the initial road segment is refined using the conditional random field (CRF) framework, which integrates high-level information into road detection. We perform several experiments to evaluate the common performance, scale sensitivity and noise sensitivity of the proposed method. The experimental results demonstrate that the proposed method exhibits high robustness compared to the state of the art. PMID:26610514

Center for Neural Engineering at Tennessee State University, ASSERT Annual Progress Report.

DTIC Science & Technology

1995-07-01

neural networks . Their research topics are: (1) developing frequency dependent oscillatory neural networks ; (2) long term pontentiation learning rules...as applied to spatial navigation; (3) design and build a servo joint robotic arm and (4) neural network based prothesis control. One graduate student

Allothetic and idiothetic sensor fusion in rat-inspired robot localization

NASA Astrophysics Data System (ADS)

Weitzenfeld, Alfredo; Fellous, Jean-Marc; Barrera, Alejandra; Tejera, Gonzalo

2012-06-01

We describe a spatial cognition model based on the rat's brain neurophysiology as a basis for new robotic navigation architectures. The model integrates allothetic (external visual landmarks) and idiothetic (internal kinesthetic information) cues to train either rat or robot to learn a path enabling it to reach a goal from multiple starting positions. It stands in contrast to most robotic architectures based on SLAM, where a map of the environment is built to provide probabilistic localization information computed from robot odometry and landmark perception. Allothetic cues suffer in general from perceptual ambiguity when trying to distinguish between places with equivalent visual patterns, while idiothetic cues suffer from imprecise motions and limited memory recalls. We experiment with both types of cues in different maze configurations by training rats and robots to find the goal starting from a fixed location, and then testing them to reach the same target from new starting locations. We show that the robot, after having pre-explored a maze, can find a goal with improved efficiency, and is able to (1) learn the correct route to reach the goal, (2) recognize places already visited, and (3) exploit allothetic and idiothetic cues to improve on its performance. We finally contrast our biologically-inspired approach to more traditional robotic approaches and discuss current work in progress.

Piezoelectrically Actuated Robotic System for MRI-Guided Prostate Percutaneous Therapy

PubMed Central

Su, Hao; Shang, Weijian; Cole, Gregory; Li, Gang; Harrington, Kevin; Camilo, Alexander; Tokuda, Junichi; Tempany, Clare M.; Hata, Nobuhiko; Fischer, Gregory S.

2014-01-01

This paper presents a fully-actuated robotic system for percutaneous prostate therapy under continuously acquired live magnetic resonance imaging (MRI) guidance. The system is composed of modular hardware and software to support the surgical workflow of intra-operative MRI-guided surgical procedures. We present the development of a 6-degree-of-freedom (DOF) needle placement robot for transperineal prostate interventions. The robot consists of a 3-DOF needle driver module and a 3-DOF Cartesian motion module. The needle driver provides needle cannula translation and rotation (2-DOF) and stylet translation (1-DOF). A custom robot controller consisting of multiple piezoelectric motor drivers provides precision closed-loop control of piezoelectric motors and enables simultaneous robot motion and MR imaging. The developed modular robot control interface software performs image-based registration, kinematics calculation, and exchanges robot commands and coordinates between the navigation software and the robot controller with a new implementation of the open network communication protocol OpenIGTLink. Comprehensive compatibility of the robot is evaluated inside a 3-Tesla MRI scanner using standard imaging sequences and the signal-to-noise ratio (SNR) loss is limited to 15%. The image deterioration due to the present and motion of robot demonstrates unobservable image interference. Twenty-five targeted needle placements inside gelatin phantoms utilizing an 18-gauge ceramic needle demonstrated 0.87 mm root mean square (RMS) error in 3D Euclidean distance based on MRI volume segmentation of the image-guided robotic needle placement procedure. PMID:26412962

Human Flight to Lunar and Beyond - Re-Learning Operations Paradigms

NASA Technical Reports Server (NTRS)

Kenny, Edward (Ted); Statman, Joseph

2016-01-01

For the first time since the Apollo era, NASA is planning on sending astronauts on flights beyond LEO. The Human Space Flight (HSF) program started with a successful initial flight in Earth orbit, in December 2014. The program will continue with two Exploration Missions (EM): EM-1 will be unmanned and EM-2, carrying astronauts, will follow. NASA established a multi-center team to address the communications, and related tacking/navigation needs. This paper will focus on the lessons learned by the team designing the architecture and operations for the missions. Many of these Beyond Earth Orbit lessons had to be re-learned, as the HSF program has operated for many years in Earth orbit. Unlike the Apollo missions that were largely tracked by a dedicated ground network, the HSF planned missions will be tracked (at distances beyond GEO) by the DSN, a network that mostly serves robotic missions. There have been surprising challenges to the DSN as unique modern human spaceflight needs stretch the experience base beyond that of tracking robotic missions in deep space. Close interaction between the DSN and the HSF community to understand the unique needs (e.g. 2-way voice) resulted in a Concept of Operations (ConOps) that leverages both the deep space robotic and the Human LEO experiences. Several examples will be used to highlight the unique challenges the team faced in establishing the communications and tracking capabilities for HSF missions beyond Earth Orbit, including: Navigation. At LEO, HSF missions can rely on GPS devices for orbit determination. For Lunar-and-beyond HSF missions, techniques such as precision 2-way and 3-way Doppler and ranging, Delta-Difference-of-range, and eventually possibly on-board navigation will be used. At the same time, HSF presents a challenge to navigators, beyond those presented by robotic missions - navigating a dynamic/"noisy" spacecraft. Impact of latency - the delay associated with Round-Trip-Light-Time (RTLT). Imagine trying to have a 2-way discussion (audio or video) with an astronaut, with a 2-3 sec or more delay inserted (for lunar distances) or 20 minutes delay (for Mars distances). Balanced communications link. For robotic missions, there has been a heavy emphasis on higher downlink data rates, e.g. bringing back science data. Higher uplink data rates were of secondary importance, as uplink was used only to send commands (and occasionally small files) to the spacecraft. The ratio of downlink-to-uplink data rates was often 10:1 or more. For HSF, a continuous forward link is established and rates for uplink and downlink are more similar.

Control of free-flying space robot manipulator systems

NASA Technical Reports Server (NTRS)

Cannon, Robert H., Jr.

1989-01-01

Control techniques for self-contained, autonomous free-flying space robots are being tested and developed. Free-flying space robots are envisioned as a key element of any successful long term presence in space. These robots must be capable of performing the assembly, maintenance, and inspection, and repair tasks that currently require astronaut extra-vehicular activity (EVA). Use of robots will provide economic savings as well as improved astronaut safety by reducing and in many cases, eliminating the need for human EVA. The focus of the work is to develop and carry out a set of research projects using laboratory models of satellite robots. These devices use air-cushion-vehicle (ACV) technology to simulate in two dimensions the drag-free, zero-g conditions of space. Current work is divided into six major projects or research areas. Fixed-base cooperative manipulation work represents our initial entry into multiple arm cooperation and high-level control with a sophisticated user interface. The floating-base cooperative manipulation project strives to transfer some of the technologies developed in the fixed-base work onto a floating base. The global control and navigation experiment seeks to demonstrate simultaneous control of the robot manipulators and the robot base position so that tasks can be accomplished while the base is undergoing a controlled motion. The multiple-vehicle cooperation project's goal is to demonstrate multiple free-floating robots working in teams to carry out tasks too difficult or complex for a single robot to perform. The Location Enhancement Arm Push-off (LEAP) activity's goal is to provide a viable alternative to expendable gas thrusters for vehicle propulsion wherein the robot uses its manipulators to throw itself from place to place. Because the successful execution of the LEAP technique requires an accurate model of the robot and payload mass properties, it was deemed an attractive testbed for adaptive control technology.

Sensor fusion III: 3-D perception and recognition; Proceedings of the Meeting, Boston, MA, Nov. 5-8, 1990

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1991-01-01

The volume on data fusion from multiple sources discusses fusing multiple views, temporal analysis and 3D motion interpretation, sensor fusion and eye-to-hand coordination, and integration in human shape perception. Attention is given to surface reconstruction, statistical methods in sensor fusion, fusing sensor data with environmental knowledge, computational models for sensor fusion, and evaluation and selection of sensor fusion techniques. Topics addressed include the structure of a scene from two and three projections, optical flow techniques for moving target detection, tactical sensor-based exploration in a robotic environment, and the fusion of human and machine skills for remote robotic operations. Also discussed are K-nearest-neighbor concepts for sensor fusion, surface reconstruction with discontinuities, a sensor-knowledge-command fusion paradigm for man-machine systems, coordinating sensing and local navigation, and terrain map matching using multisensing techniques for applications to autonomous vehicle navigation.

Robot soccer anywhere: achieving persistent autonomous navigation, mapping, and object vision tracking in dynamic environments

NASA Astrophysics Data System (ADS)

Dragone, Mauro; O'Donoghue, Ruadhan; Leonard, John J.; O'Hare, Gregory; Duffy, Brian; Patrikalakis, Andrew; Leederkerken, Jacques

2005-06-01

The paper describes an ongoing effort to enable autonomous mobile robots to play soccer in unstructured, everyday environments. Unlike conventional robot soccer competitions that are usually held on purpose-built robot soccer "fields", in our work we seek to develop the capability for robots to demonstrate aspects of soccer-playing in more diverse environments, such as schools, hospitals, or shopping malls, with static obstacles (furniture) and dynamic natural obstacles (people). This problem of "Soccer Anywhere" presents numerous research challenges including: (1) Simultaneous Localization and Mapping (SLAM) in dynamic, unstructured environments, (2) software control architectures for decentralized, distributed control of mobile agents, (3) integration of vision-based object tracking with dynamic control, and (4) social interaction with human participants. In addition to the intrinsic research merit of these topics, we believe that this capability would prove useful for outreach activities, in demonstrating robotics technology to primary and secondary school students, to motivate them to pursue careers in science and engineering.

Mobile Robot and Mobile Manipulator Research Towards ASTM Standards Development.

PubMed

Bostelman, Roger; Hong, Tsai; Legowik, Steven

2016-01-01

Performance standards for industrial mobile robots and mobile manipulators (robot arms onboard mobile robots) have only recently begun development. Low cost and standardized measurement techniques are needed to characterize system performance, compare different systems, and to determine if recalibration is required. This paper discusses work at the National Institute of Standards and Technology (NIST) and within the ASTM Committee F45 on Driverless Automatic Guided Industrial Vehicles. This includes standards for both terminology, F45.91, and for navigation performance test methods, F45.02. The paper defines terms that are being considered. Additionally, the paper describes navigation test methods that are near ballot and docking test methods being designed for consideration within F45.02. This includes the use of low cost artifacts that can provide alternatives to using relatively expensive measurement systems.

Mobile Robot and Mobile Manipulator Research Towards ASTM Standards Development

PubMed Central

Bostelman, Roger; Hong, Tsai; Legowik, Steven

2017-01-01

Performance standards for industrial mobile robots and mobile manipulators (robot arms onboard mobile robots) have only recently begun development. Low cost and standardized measurement techniques are needed to characterize system performance, compare different systems, and to determine if recalibration is required. This paper discusses work at the National Institute of Standards and Technology (NIST) and within the ASTM Committee F45 on Driverless Automatic Guided Industrial Vehicles. This includes standards for both terminology, F45.91, and for navigation performance test methods, F45.02. The paper defines terms that are being considered. Additionally, the paper describes navigation test methods that are near ballot and docking test methods being designed for consideration within F45.02. This includes the use of low cost artifacts that can provide alternatives to using relatively expensive measurement systems. PMID:28690359

Guidance Of A Mobile Robot Using An Omnidirectional Vision Navigation System

NASA Astrophysics Data System (ADS)

Oh, Sung J.; Hall, Ernest L.

1987-01-01

Navigation and visual guidance are key topics in the design of a mobile robot. Omnidirectional vision using a very wide angle or fisheye lens provides a hemispherical view at a single instant that permits target location without mechanical scanning. The inherent image distortion with this view and the numerical errors accumulated from vision components can be corrected to provide accurate position determination for navigation and path control. The purpose of this paper is to present the experimental results and analyses of the imaging characteristics of the omnivision system including the design of robot-oriented experiments and the calibration of raw results. Errors less than one picture element on each axis were observed by testing the accuracy and repeatability of the experimental setup and the alignment between the robot and the sensor. Similar results were obtained for four different locations using corrected results of the linearity test between zenith angle and image location. Angular error of less than one degree and radial error of less than one Y picture element were observed at moderate relative speed. The significance of this work is that the experimental information and the test of coordinated operation of the equipment provide a greater understanding of the dynamic omnivision system characteristics, as well as insight into the evaluation and improvement of the prototype sensor for a mobile robot. Also, the calibration of the sensor is important, since the results provide a cornerstone for future developments. This sensor system is currently being developed for a robot lawn mower.

SPHERES Vertigo

NASA Image and Video Library

2014-07-25

ISS040-E-079355 (25 July 2014) --- In the International Space Station?s Kibo laboratory, NASA astronaut Steve Swanson (foreground), Expedition 40 commander; and European Space Agency astronaut Alexander Gerst, flight engineer, conduct a session with a trio of soccer-ball-sized robots known as the Synchronized Position Hold, Engage, Reorient, Experimental Satellites, or SPHERES. The free-flying robots were equipped with stereoscopic goggles called the Visual Estimation and Relative Tracking for Inspection of Generic Objects, or VERTIGO, to enable the SPHERES to perform relative navigation based on a 3D model of a target object.

SPHERES Vertigo

NASA Image and Video Library

2014-07-25

ISS040-E-079129 (25 July 2014) --- In the International Space Station?s Kibo laboratory, NASA astronaut Steve Swanson (left), Expedition 40 commander; and European Space Agency astronaut Alexander Gerst, flight engineer, conduct a session with a trio of soccer-ball-sized robots known as the Synchronized Position Hold, Engage, Reorient, Experimental Satellites, or SPHERES. The free-flying robots were equipped with stereoscopic goggles called the Visual Estimation and Relative Tracking for Inspection of Generic Objects, or VERTIGO, to enable the SPHERES to perform relative navigation based on a 3D model of a target object.

SPHERES Vertigo

NASA Image and Video Library

2014-07-25

ISS040-E-079910 (25 July 2014) --- In the International Space Station?s Kibo laboratory, NASA astronaut Steve Swanson (left), Expedition 40 commander; and European Space Agency astronaut Alexander Gerst, flight engineer, conduct a session with a trio of soccer-ball-sized robots known as the Synchronized Position Hold, Engage, Reorient, Experimental Satellites, or SPHERES. The free-flying robots were equipped with stereoscopic goggles called the Visual Estimation and Relative Tracking for Inspection of Generic Objects, or VERTIGO, to enable the SPHERES to perform relative navigation based on a 3D model of a target object.

SPHERES Vertigo

NASA Image and Video Library

2014-07-25

ISS040-E-079332 (25 July 2014) --- In the International Space Station?s Kibo laboratory, NASA astronaut Steve Swanson (foreground), Expedition 40 commander; and European Space Agency astronaut Alexander Gerst, flight engineer, conduct a session with a trio of soccer-ball-sized robots known as the Synchronized Position Hold, Engage, Reorient, Experimental Satellites, or SPHERES. The free-flying robots were equipped with stereoscopic goggles called the Visual Estimation and Relative Tracking for Inspection of Generic Objects, or VERTIGO, to enable the SPHERES to perform relative navigation based on a 3D model of a target object.

An Efficient Model-Based Image Understanding Method for an Autonomous Vehicle.

DTIC Science & Technology

1997-09-01

The problem discussed in this dissertation is the development of an efficient method for visual navigation of autonomous vehicles . The approach is to... autonomous vehicles . Thus the new method is implemented as a component of the image-understanding system in the autonomous mobile robot Yamabico-11 at

Gyro and Accelerometer Based Navigation System for a Mobile Autonomous Robot.

DTIC Science & Technology

1985-12-02

special thanks goes to our thesis advisor Dr. Matthew Kabrisky for having the confidence to turn us loose on this project. Additionally, we would...Wordmaster Word Processor 1 Wordstar Word Processor 1 Virtual Devices Robo A 6802 Cross Assembler 1 Modem 720 Communication Program 1 CP/M Operating

Closing the Loop: Control and Robot Navigation in Wireless Sensor Networks

DTIC Science & Technology

2006-09-05

University of California at Berkeley Technical Report No. UCB/EECS- 2006 -112 http://www.eecs.berkeley.edu/Pubs/TechRpts/ 2006 /EECS- 2006 -112.html September 5... 2006 Report Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1...DATE 05 SEP 2006 2. REPORT TYPE 3. DATES COVERED 00-00- 2006 to 00-00- 2006 4. TITLE AND SUBTITLE Closing the Loop: Control and Robot Navigation in

Design and control of an embedded vision guided robotic fish with multiple control surfaces.

PubMed

Yu, Junzhi; Wang, Kai; Tan, Min; Zhang, Jianwei

2014-01-01

This paper focuses on the development and control issues of a self-propelled robotic fish with multiple artificial control surfaces and an embedded vision system. By virtue of the hybrid propulsion capability in the body plus the caudal fin and the complementary maneuverability in accessory fins, a synthesized propulsion scheme including a caudal fin, a pair of pectoral fins, and a pelvic fin is proposed. To achieve flexible yet stable motions in aquatic environments, a central pattern generator- (CPG-) based control method is employed. Meanwhile, a monocular underwater vision serves as sensory feedback that modifies the control parameters. The integration of the CPG-based motion control and the visual processing in an embedded microcontroller allows the robotic fish to navigate online. Aquatic tests demonstrate the efficacy of the proposed mechatronic design and swimming control methods. Particularly, a pelvic fin actuated sideward swimming gait was first implemented. It is also found that the speeds and maneuverability of the robotic fish with coordinated control surfaces were largely superior to that of the swimming robot propelled by a single control surface.

Design and Control of an Embedded Vision Guided Robotic Fish with Multiple Control Surfaces

PubMed Central

Wang, Kai; Tan, Min; Zhang, Jianwei

2014-01-01

This paper focuses on the development and control issues of a self-propelled robotic fish with multiple artificial control surfaces and an embedded vision system. By virtue of the hybrid propulsion capability in the body plus the caudal fin and the complementary maneuverability in accessory fins, a synthesized propulsion scheme including a caudal fin, a pair of pectoral fins, and a pelvic fin is proposed. To achieve flexible yet stable motions in aquatic environments, a central pattern generator- (CPG-) based control method is employed. Meanwhile, a monocular underwater vision serves as sensory feedback that modifies the control parameters. The integration of the CPG-based motion control and the visual processing in an embedded microcontroller allows the robotic fish to navigate online. Aquatic tests demonstrate the efficacy of the proposed mechatronic design and swimming control methods. Particularly, a pelvic fin actuated sideward swimming gait was first implemented. It is also found that the speeds and maneuverability of the robotic fish with coordinated control surfaces were largely superior to that of the swimming robot propelled by a single control surface. PMID:24688413

Perception system and functions for autonomous navigation in a natural environment

NASA Technical Reports Server (NTRS)

Chatila, Raja; Devy, Michel; Lacroix, Simon; Herrb, Matthieu

1994-01-01

This paper presents the approach, algorithms, and processes we developed for the perception system of a cross-country autonomous robot. After a presentation of the tele-programming context we favor for intervention robots, we introduce an adaptive navigation approach, well suited for the characteristics of complex natural environments. This approach lead us to develop a heterogeneous perception system that manages several different terrain representatives. The perception functionalities required during navigation are listed, along with the corresponding representations we consider. The main perception processes we developed are presented. They are integrated within an on-board control architecture we developed. First results of an ambitious experiment currently underway at LAAS are then presented.

A self-paced motor imagery based brain-computer interface for robotic wheelchair control.

PubMed

Tsui, Chun Sing Louis; Gan, John Q; Hu, Huosheng

2011-10-01

This paper presents a simple self-paced motor imagery based brain-computer interface (BCI) to control a robotic wheelchair. An innovative control protocol is proposed to enable a 2-class self-paced BCI for wheelchair control, in which the user makes path planning and fully controls the wheelchair except for the automatic obstacle avoidance based on a laser range finder when necessary. In order for the users to train their motor imagery control online safely and easily, simulated robot navigation in a specially designed environment was developed. This allowed the users to practice motor imagery control with the core self-paced BCI system in a simulated scenario before controlling the wheelchair. The self-paced BCI can then be applied to control a real robotic wheelchair using a protocol similar to that controlling the simulated robot. Our emphasis is on allowing more potential users to use the BCI controlled wheelchair with minimal training; a simple 2-class self paced system is adequate with the novel control protocol, resulting in a better transition from offline training to online control. Experimental results have demonstrated the usefulness of the online practice under the simulated scenario, and the effectiveness of the proposed self-paced BCI for robotic wheelchair control.

A simple, inexpensive, and effective implementation of a vision-guided autonomous robot

NASA Astrophysics Data System (ADS)

Tippetts, Beau; Lillywhite, Kirt; Fowers, Spencer; Dennis, Aaron; Lee, Dah-Jye; Archibald, James

2006-10-01

This paper discusses a simple, inexpensive, and effective implementation of a vision-guided autonomous robot. This implementation is a second year entrance for Brigham Young University students to the Intelligent Ground Vehicle Competition. The objective of the robot was to navigate a course constructed of white boundary lines and orange obstacles for the autonomous competition. A used electric wheelchair was used as the robot base. The wheelchair was purchased from a local thrift store for $28. The base was modified to include Kegresse tracks using a friction drum system. This modification allowed the robot to perform better on a variety of terrains, resolving issues with last year's design. In order to control the wheelchair and retain the robust motor controls already on the wheelchair the wheelchair joystick was simply removed and replaced with a printed circuit board that emulated joystick operation and was capable of receiving commands through a serial port connection. Three different algorithms were implemented and compared: a purely reactive approach, a potential fields approach, and a machine learning approach. Each of the algorithms used color segmentation methods to interpret data from a digital camera in order to identify the features of the course. This paper will be useful to those interested in implementing an inexpensive vision-based autonomous robot.

Distributed multirobot sensing and tracking: a behavior-based approach

NASA Astrophysics Data System (ADS)

Parker, Lynne E.

1995-09-01

An important issue that arises in the automation of many large-scale surveillance and reconnaissance tasks is that of tracking the movements of (or maintaining passive contact with) objects navigating in a bounded area of interest. Oftentimes in these problems, the area to be monitored will move over time or will not permit fixed sensors, thus requiring a team of mobile sensors--or robots--to monitor the area collectively. In these situations, the robots must not only have mechanisms for determining how to track objects and how to fuse information from neighboring robots, but they must also have distributed control strategies for ensuring that the entire area of interest is continually covered to the greatest extent possible. This paper focuses on the distributed control issue by describing a proposed decentralized control mechanism that allows a team of robots to collectively track and monitor objects in an uncluttered area of interest. The approach is based upon an extension to the ALLIANCE behavior-based architecture that generalizes from the domain of loosely-coupled, independent applications to the domain of strongly cooperative applications, in which the action selection of a robot is dependent upon the actions selected by its teammates. We conclude the paper be describing our ongoing implementation of the proposed approach on a team of four mobile robots.

Approach-Phase Precision Landing with Hazard Relative Navigation: Terrestrial Test Campaign Results of the Morpheus/ALHAT Project

NASA Technical Reports Server (NTRS)

Crain, Timothy P.; Bishop, Robert H.; Carson, John M., III; Trawny, Nikolas; Hanak, Chad; Sullivan, Jacob; Christian, John; DeMars, Kyle; Campbell, Tom; Getchius, Joel

2016-01-01

The Morpheus Project began in late 2009 as an ambitious e ort code-named Project M to integrate three ongoing multi-center NASA technology developments: humanoid robotics, liquid oxygen/liquid methane (LOX/LCH4) propulsion and Autonomous Precision Landing and Hazard Avoidance Technology (ALHAT) into a single engineering demonstration mission to be own to the Moon by 2013. The humanoid robot e ort was redirected to a deploy- ment of Robonaut 2 on the International Space Station in February of 2011 while Morpheus continued as a terrestrial eld test project integrating the existing ALHAT Project's tech- nologies into a sub-orbital ight system using the world's rst LOX/LCH4 main propulsion and reaction control system fed from the same blowdown tanks. A series of 33 tethered tests with the Morpheus 1.0 vehicle and Morpheus 1.5 vehicle were conducted from April 2011 - December 2013 before successful, sustained free ights with the primary Vertical Testbed (VTB) navigation con guration began with Free Flight 3 on December 10, 2013. Over the course of the following 12 free ights and 3 tethered ights, components of the ALHAT navigation system were integrated into the Morpheus vehicle, operations, and ight control loop. The ALHAT navigation system was integrated and run concurrently with the VTB navigation system as a reference and fail-safe option in ight (see touchdown position esti- mate comparisons in Fig. 1). Flight testing completed with Free Flight 15 on December 15, 2014 with a completely autonomous Hazard Detection and Avoidance (HDA), integration of surface relative and Hazard Relative Navigation (HRN) measurements into the onboard dual-state inertial estimator Kalman lter software, and landing within 2 meters of the VTB GPS-based navigation solution at the safe landing site target. This paper describes the Mor- pheus joint VTB/ALHAT navigation architecture, the sensors utilized during the terrestrial ight campaign, issues resolved during testing, and the navigation results from the ight tests.

Mobile robot navigation modulated by artificial emotions.

PubMed

Lee-Johnson, C P; Carnegie, D A

2010-04-01

For artificial intelligence research to progress beyond the highly specialized task-dependent implementations achievable today, researchers may need to incorporate aspects of biological behavior that have not traditionally been associated with intelligence. Affective processes such as emotions may be crucial to the generalized intelligence possessed by humans and animals. A number of robots and autonomous agents have been created that can emulate human emotions, but the majority of this research focuses on the social domain. In contrast, we have developed a hybrid reactive/deliberative architecture that incorporates artificial emotions to improve the general adaptive performance of a mobile robot for a navigation task. Emotions are active on multiple architectural levels, modulating the robot's decisions and actions to suit the context of its situation. Reactive emotions interact with the robot's control system, altering its parameters in response to appraisals from short-term sensor data. Deliberative emotions are learned associations that bias path planning in response to eliciting objects or events. Quantitative results are presented that demonstrate situations in which each artificial emotion can be beneficial to performance.

Real-time maneuver optimization of space-based robots in a dynamic environment: Theory and on-orbit experiments

NASA Astrophysics Data System (ADS)

Chamitoff, Gregory E.; Saenz-Otero, Alvar; Katz, Jacob G.; Ulrich, Steve; Morrell, Benjamin J.; Gibbens, Peter W.

2018-01-01

This paper presents the development of a real-time path-planning optimization approach to controlling the motion of space-based robots. The algorithm is capable of planning three dimensional trajectories for a robot to navigate within complex surroundings that include numerous static and dynamic obstacles, path constraints and performance limitations. The methodology employs a unique transformation that enables rapid generation of feasible solutions for complex geometries, making it suitable for application to real-time operations and dynamic environments. This strategy was implemented on the Synchronized Position Hold Engage Reorient Experimental Satellite (SPHERES) test-bed on the International Space Station (ISS), and experimental testing was conducted onboard the ISS during Expedition 17 by the first author. Lessons learned from the on-orbit tests were used to further refine the algorithm for future implementations.

Adaptive multisensor fusion for planetary exploration rovers

NASA Technical Reports Server (NTRS)

Collin, Marie-France; Kumar, Krishen; Pampagnin, Luc-Henri

1992-01-01

The purpose of the adaptive multisensor fusion system currently being designed at NASA/Johnson Space Center is to provide a robotic rover with assured vision and safe navigation capabilities during robotic missions on planetary surfaces. Our approach consists of using multispectral sensing devices ranging from visible to microwave wavelengths to fulfill the needs of perception for space robotics. Based on the illumination conditions and the sensors capabilities knowledge, the designed perception system should automatically select the best subset of sensors and their sensing modalities that will allow the perception and interpretation of the environment. Then, based on reflectance and emittance theoretical models, the sensor data are fused to extract the physical and geometrical surface properties of the environment surface slope, dielectric constant, temperature and roughness. The theoretical concepts, the design and first results of the multisensor perception system are presented.

Self-Organized Multi-Camera Network for a Fast and Easy Deployment of Ubiquitous Robots in Unknown Environments

PubMed Central

Canedo-Rodriguez, Adrián; Iglesias, Roberto; Regueiro, Carlos V.; Alvarez-Santos, Victor; Pardo, Xose Manuel

2013-01-01

To bring cutting edge robotics from research centres to social environments, the robotics community must start providing affordable solutions: the costs must be reduced and the quality and usefulness of the robot services must be enhanced. Unfortunately, nowadays the deployment of robots and the adaptation of their services to new environments are tasks that usually require several days of expert work. With this in view, we present a multi-agent system made up of intelligent cameras and autonomous robots, which is easy and fast to deploy in different environments. The cameras will enhance the robot perceptions and allow them to react to situations that require their services. Additionally, the cameras will support the movement of the robots. This will enable our robots to navigate even when there are not maps available. The deployment of our system does not require expertise and can be done in a short period of time, since neither software nor hardware tuning is needed. Every system task is automatic, distributed and based on self-organization processes. Our system is scalable, robust, and flexible to the environment. We carried out several real world experiments, which show the good performance of our proposal. PMID:23271604

Self-organized multi-camera network for a fast and easy deployment of ubiquitous robots in unknown environments.

PubMed

Canedo-Rodriguez, Adrián; Iglesias, Roberto; Regueiro, Carlos V; Alvarez-Santos, Victor; Pardo, Xose Manuel

2012-12-27

To bring cutting edge robotics from research centres to social environments, the robotics community must start providing affordable solutions: the costs must be reduced and the quality and usefulness of the robot services must be enhanced. Unfortunately, nowadays the deployment of robots and the adaptation of their services to new environments are tasks that usually require several days of expert work. With this in view, we present a multi-agent system made up of intelligent cameras and autonomous robots, which is easy and fast to deploy in different environments. The cameras will enhance the robot perceptions and allow them to react to situations that require their services. Additionally, the cameras will support the movement of the robots. This will enable our robots to navigate even when there are not maps available. The deployment of our system does not require expertise and can be done in a short period of time, since neither software nor hardware tuning is needed. Every system task is automatic, distributed and based on self-organization processes. Our system is scalable, robust, and flexible to the environment. We carried out several real world experiments, which show the good performance of our proposal.

Toward real-time endoscopically-guided robotic navigation based on a 3D virtual surgical field model

NASA Astrophysics Data System (ADS)

Gong, Yuanzheng; Hu, Danying; Hannaford, Blake; Seibel, Eric J.

2015-03-01

The challenge is to accurately guide the surgical tool within the three-dimensional (3D) surgical field for roboticallyassisted operations such as tumor margin removal from a debulked brain tumor cavity. The proposed technique is 3D image-guided surgical navigation based on matching intraoperative video frames to a 3D virtual model of the surgical field. A small laser-scanning endoscopic camera was attached to a mock minimally-invasive surgical tool that was manipulated toward a region of interest (residual tumor) within a phantom of a debulked brain tumor. Video frames from the endoscope provided features that were matched to the 3D virtual model, which were reconstructed earlier by raster scanning over the surgical field. Camera pose (position and orientation) is recovered by implementing a constrained bundle adjustment algorithm. Navigational error during the approach to fluorescence target (residual tumor) is determined by comparing the calculated camera pose to the measured camera pose using a micro-positioning stage. From these preliminary results, computation efficiency of the algorithm in MATLAB code is near real-time (2.5 sec for each estimation of pose), which can be improved by implementation in C++. Error analysis produced 3-mm distance error and 2.5 degree of orientation error on average. The sources of these errors come from 1) inaccuracy of the 3D virtual model, generated on a calibrated RAVEN robotic platform with stereo tracking; 2) inaccuracy of endoscope intrinsic parameters, such as focal length; and 3) any endoscopic image distortion from scanning irregularities. This work demonstrates feasibility of micro-camera 3D guidance of a robotic surgical tool.

HERMIES-I: a mobile robot for navigation and manipulation experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weisbin, C.R.; Barhen, J.; de Saussure, G.

1985-01-01

The purpose of this paper is to report the current status of investigations ongoing at the Center for Engineering Systems Advanced Research (CESAR) in the areas of navigation and manipulation in unstructured environments. The HERMIES-I mobile robot, a prototype of a series which contains many of the major features needed for remote work in hazardous environments is discussed. Initial experimental work at CESAR has begun in the area of navigation. It briefly reviews some of the ongoing research in autonomous navigation and describes initial research with HERMIES-I and associated graphic simulation. Since the HERMIES robots will generally be composed ofmore » a variety of asynchronously controlled hardware components (such as manipulator arms, digital image sensors, sonars, etc.) it seems appropriate to consider future development of the HERMIES brain as a hypercube ensemble machine with concurrent computation and associated message passing. The basic properties of such a hypercube architecture are presented. Decision-making under uncertainty eventually permeates all of our work. Following a survey of existing analytical approaches, it was decided that a stronger theoretical basis is required. As such, this paper presents the framework for a recently developed hybrid uncertainty theory. 21 refs., 2 figs.« less

Application of neural models as controllers in mobile robot velocity control loop

NASA Astrophysics Data System (ADS)

Cerkala, Jakub; Jadlovska, Anna

2017-01-01

This paper presents the application of an inverse neural models used as controllers in comparison to classical PI controllers for velocity tracking control task used in two-wheel, differentially driven mobile robot. The PI controller synthesis is based on linear approximation of actuators with equivalent load. In order to obtain relevant datasets for training of feed-forward multi-layer perceptron based neural network used as neural model, the mathematical model of mobile robot, that combines its kinematic and dynamic properties such as chassis dimensions, center of gravity offset, friction and actuator parameters is used. Neural models are trained off-line to act as an inverse dynamics of DC motors with particular load using data collected in simulation experiment for motor input voltage step changes within bounded operating area. The performances of PI controllers versus inverse neural models in mobile robot internal velocity control loops are demonstrated and compared in simulation experiment of navigation control task for line segment motion in plane.

Reactive navigation in extremely dense and highly intricate environments

PubMed Central

2017-01-01

Reactive navigation is a well-known paradigm for controlling an autonomous mobile robot, which suggests making all control decisions through some light processing of the current/recent sensor data. Among the many advantages of this paradigm are: 1) the possibility to apply it to robots with limited and low-priced hardware resources, and 2) the fact of being able to safely navigate a robot in completely unknown environments containing unpredictable moving obstacles. As a major disadvantage, nevertheless, the reactive paradigm may occasionally cause robots to get trapped in certain areas of the environment—typically, these conflicting areas have a large concave shape and/or are full of closely-spaced obstacles. In this last respect, an enormous effort has been devoted to overcome such a serious drawback during the last two decades. As a result of this effort, a substantial number of new approaches for reactive navigation have been put forward. Some of these approaches have clearly improved the way how a reactively-controlled robot can move among densely cluttered obstacles; some other approaches have essentially focused on increasing the variety of obstacle shapes and sizes that could be successfully circumnavigated; etc. In this paper, as a starting point, we choose the best existing reactive approach to move in densely cluttered environments, and we also choose the existing reactive approach with the greatest ability to circumvent large intricate-shaped obstacles. Then, we combine these two approaches in a way that makes the most of them. From the experimental point of view, we use both simulated and real scenarios of challenging complexity for testing purposes. In such scenarios, we demonstrate that the combined approach herein proposed clearly outperforms the two individual approaches on which it is built. PMID:29287078

Passive mapping and intermittent exploration for mobile robots

NASA Technical Reports Server (NTRS)

Engleson, Sean P.

1994-01-01

An adaptive state space architecture is combined with diktiometric representation to provide the framework for designing a robot mapping system with flexible navigation planning tasks. This involves indexing waypoints described as expectations, geometric indexing, and perceptual indexing. Matching and updating the robot's projected position and sensory inputs with indexing waypoints involves matchers, dynamic priorities, transients, and waypoint restructuring. The robot's map learning can be opganized around the principles of passive mapping.

Image Mapping and Visual Attention on the Sensory Ego-Sphere

NASA Technical Reports Server (NTRS)

Fleming, Katherine Achim; Peters, Richard Alan, II

2012-01-01

The Sensory Ego-Sphere (SES) is a short-term memory for a robot in the form of an egocentric, tessellated, spherical, sensory-motor map of the robot s locale. Visual attention enables fast alignment of overlapping images without warping or position optimization, since an attentional point (AP) on the composite typically corresponds to one on each of the collocated regions in the images. Such alignment speeds analysis of the multiple images of the area. Compositing and attention were performed two ways and compared: (1) APs were computed directly on the composite and not on the full-resolution images until the time of retrieval; and (2) the attentional operator was applied to all incoming imagery. It was found that although the second method was slower, it produced consistent and, thereby, more useful APs. The SES is an integral part of a control system that will enable a robot to learn new behaviors based on its previous experiences, and that will enable it to recombine its known behaviors in such a way as to solve related, but novel, task problems with apparent creativity. The approach is to combine sensory-motor data association and dimensionality reduction to learn navigation and manipulation tasks as sequences of basic behaviors that can be implemented with a small set of closed-loop controllers. Over time, the aggregate of behaviors and their transition probabilities form a stochastic network. Then given a task, the robot finds a path in the network that leads from its current state to the goal. The SES provides a short-term memory for the cognitive functions of the robot, association of sensory and motor data via spatio-temporal coincidence, direction of the attention of the robot, navigation through spatial localization with respect to known or discovered landmarks, and structured data sharing between the robot and human team members, the individuals in multi-robot teams, or with a C3 center.

Human-Robot Interaction

NASA Technical Reports Server (NTRS)

Sandor, Aniko; Cross, E. Vincent, II; Chang, Mai Lee

2015-01-01

Human-robot interaction (HRI) is a discipline investigating the factors affecting the interactions between humans and robots. It is important to evaluate how the design of interfaces affect the human's ability to perform tasks effectively and efficiently when working with a robot. By understanding the effects of interface design on human performance, workload, and situation awareness, interfaces can be developed to appropriately support the human in performing tasks with minimal errors and with appropriate interaction time and effort. Thus, the results of research on human-robot interfaces have direct implications for the design of robotic systems. For efficient and effective remote navigation of a rover, a human operator needs to be aware of the robot's environment. However, during teleoperation, operators may get information about the environment only through a robot's front-mounted camera causing a keyhole effect. The keyhole effect reduces situation awareness which may manifest in navigation issues such as higher number of collisions, missing critical aspects of the environment, or reduced speed. One way to compensate for the keyhole effect and the ambiguities operators experience when they teleoperate a robot is adding multiple cameras and including the robot chassis in the camera view. Augmented reality, such as overlays, can also enhance the way a person sees objects in the environment or in camera views by making them more visible. Scenes can be augmented with integrated telemetry, procedures, or map information. Furthermore, the addition of an exocentric (i.e., third-person) field of view from a camera placed in the robot's environment may provide operators with the additional information needed to gain spatial awareness of the robot. Two research studies investigated possible mitigation approaches to address the keyhole effect: 1) combining the inclusion of the robot chassis in the camera view with augmented reality overlays, and 2) modifying the camera frame of reference. The first study investigated the effects of inclusion and exclusion of the robot chassis along with superimposing a simple arrow overlay onto the video feed of operator task performance during teleoperation of a mobile robot in a driving task. In this study, the front half of the robot chassis was made visible through the use of three cameras, two side-facing and one forward-facing. The purpose of the second study was to compare operator performance when teleoperating a robot from an egocentric-only and combined (egocentric plus exocentric camera) view. Camera view parameters that are found to be beneficial in these laboratory experiments can be implemented on NASA rovers and tested in a real-world driving and navigation scenario on-site at the Johnson Space Center.

Interaction dynamics of multiple autonomous mobile robots in bounded spatial domains

NASA Technical Reports Server (NTRS)

Wang, P. K. C.

1989-01-01

A general navigation strategy for multiple autonomous robots in a bounded domain is developed analytically. Each robot is modeled as a spherical particle (i.e., an effective spatial domain about the center of mass); its interactions with other robots or with obstacles and domain boundaries are described in terms of the classical many-body problem; and a collision-avoidance strategy is derived and combined with homing, robot-robot, and robot-obstacle collision-avoidance strategies. Results from homing simulations involving (1) a single robot in a circular domain, (2) two robots in a circular domain, and (3) one robot in a domain with an obstacle are presented in graphs and briefly characterized.

Quantifying Traversability of Terrain for a Mobile Robot

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Seraji, Homayoun; Werger, Barry

2005-01-01

A document presents an updated discussion on a method of autonomous navigation for a robotic vehicle navigating across rough terrain. The method involves, among other things, the use of a measure of traversability, denoted the fuzzy traversability index, which embodies the information about the slope and roughness of terrain obtained from analysis of images acquired by cameras mounted on the robot. The improvements presented in the report focus on the use of the fuzzy traversability index to generate a traversability map and a grid map for planning the safest path for the robot. Once grid traversability values have been computed, they are utilized for rejecting unsafe path segments and for computing a traversalcost function for ranking candidate paths, selected by a search algorithm, from a specified initial position to a specified final position. The output of the algorithm is a set of waypoints designating a path having a minimal-traversal cost.

A biomimetic vision-based hovercraft accounts for bees' complex behaviour in various corridors.

PubMed

Roubieu, Frédéric L; Serres, Julien R; Colonnier, Fabien; Franceschini, Nicolas; Viollet, Stéphane; Ruffier, Franck

2014-09-01

Here we present the first systematic comparison between the visual guidance behaviour of a biomimetic robot and those of honeybees flying in similar environments. We built a miniature hovercraft which can travel safely along corridors with various configurations. For the first time, we implemented on a real physical robot the 'lateral optic flow regulation autopilot', which we previously studied computer simulations. This autopilot inspired by the results of experiments on various species of hymenoptera consists of two intertwined feedback loops, the speed and lateral control loops, each of which has its own optic flow (OF) set-point. A heading-lock system makes the robot move straight ahead as fast as 69 cm s(-1) with a clearance from one wall as small as 31 cm, giving an unusually high translational OF value (125° s(-1)). Our biomimetic robot was found to navigate safely along straight, tapered and bent corridors, and to react appropriately to perturbations such as the lack of texture on one wall, the presence of a tapering or non-stationary section of the corridor and even a sloping terrain equivalent to a wind disturbance. The front end of the visual system consists of only two local motion sensors (LMS), one on each side. This minimalistic visual system measuring the lateral OF suffices to control both the robot's forward speed and its clearance from the walls without ever measuring any speeds or distances. We added two additional LMSs oriented at +/-45° to improve the robot's performances in stiffly tapered corridors. The simple control system accounts for worker bees' ability to navigate safely in six challenging environments: straight corridors, single walls, tapered corridors, straight corridors with part of one wall moving or missing, as well as in the presence of wind.

Grid occupancy estimation for environment perception based on belief functions and PCR6

NASA Astrophysics Data System (ADS)

Moras, Julien; Dezert, Jean; Pannetier, Benjamin

2015-05-01

In this contribution, we propose to improve the grid map occupancy estimation method developed so far based on belief function modeling and the classical Dempster's rule of combination. Grid map offers a useful representation of the perceived world for mobile robotics navigation. It will play a major role for the security (obstacle avoidance) of next generations of terrestrial vehicles, as well as for future autonomous navigation systems. In a grid map, the occupancy of each cell representing a small piece of the surrounding area of the robot must be estimated at first from sensors measurements (typically LIDAR, or camera), and then it must also be classified into different classes in order to get a complete and precise perception of the dynamic environment where the robot moves. So far, the estimation and the grid map updating have been done using fusion techniques based on the probabilistic framework, or on the classical belief function framework thanks to an inverse model of the sensors. Mainly because the latter offers an interesting management of uncertainties when the quality of available information is low, and when the sources of information appear as conflicting. To improve the performances of the grid map estimation, we propose in this paper to replace Dempster's rule of combination by the PCR6 rule (Proportional Conflict Redistribution rule #6) proposed in DSmT (Dezert-Smarandache) Theory. As an illustrating scenario, we consider a platform moving in dynamic area and we compare our new realistic simulation results (based on a LIDAR sensor) with those obtained by the probabilistic and the classical belief-based approaches.

The JPL Serpentine Robot: A 12 DOF System for Inspection

NASA Technical Reports Server (NTRS)

Paljug, E.; Ohm, T.; Hayati, S.

1995-01-01

The Serpentine Robot is a prototype hyper-redundant (snake-like) manipulator system developed at the Jet Propulsion Laboratory. It is designed to navigate and perform tasks in obstructed and constrained environments in which conventional 6 DOF manipulators cannot function. Described are the robot mechanical design, a joint assembly low level inverse kinematic algorithm, control development, and applications.

Query Processing for Probabilistic State Diagrams Describing Multiple Robot Navigation in an Indoor Environment

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.

Videoexoscopic real-time intraoperative navigation for spinal neurosurgery: a novel co-adaptation of two existing technology platforms, technical note.

PubMed

Huang, Meng; Barber, Sean Michael; Steele, William James; Boghani, Zain; Desai, Viren Rajendrakumar; Britz, Gavin Wayne; West, George Alexander; Trask, Todd Wilson; Holman, Paul Joseph

2018-06-01

Image-guided approaches to spinal instrumentation and interbody fusion have been widely popularized in the last decade [1-5]. Navigated pedicle screws are significantly less likely to breach [2, 3, 5, 6]. Navigation otherwise remains a point reference tool because the projection is off-axis to the surgeon's inline loupe or microscope view. The Synaptive robotic brightmatter drive videoexoscope monitor system represents a new paradigm for off-axis high-definition (HD) surgical visualization. It has many advantages over the traditional microscope and loupes, which have already been demonstrated in a cadaveric study [7]. An auxiliary, but powerful capability of this system is projection of a second, modifiable image in a split-screen configuration. We hypothesized that integration of both Medtronic and Synaptive platforms could permit the visualization of reconstructed navigation and surgical field images simultaneously. By utilizing navigated instruments, this configuration has the ability to support live image-guided surgery or real-time navigation (RTN). Medtronic O-arm/Stealth S7 navigation, MetRx, NavLock, and SureTrak spinal systems were implemented on a prone cadaveric specimen with a stream output to the Synaptive Display. Surgical visualization was provided using a Storz Image S1 platform and camera mounted to the Synaptive robotic brightmatter drive. We were able to successfully technically co-adapt both platforms. A minimally invasive transforaminal lumbar interbody fusion (MIS TLIF) and an open pedicle subtraction osteotomy (PSO) were performed using a navigated high-speed drill under RTN. Disc Shaver and Trials under RTN were implemented on the MIS TLIF. The synergy of Synaptive HD videoexoscope robotic drive and Medtronic Stealth platforms allow for live image-guided surgery or real-time navigation (RTN). Off-axis projection also allows upright neutral cervical spine operative ergonomics for the surgeons and improved surgical team visualization and education compared to traditional means. This technique has the potential to augment existing minimally invasive and open approaches, but will require long-term outcome measurements for efficacy.

Bildbasierte Navigation eines mobilen Roboters mittels omnidirektionaler und schwenkbarer Kamera

NASA Astrophysics Data System (ADS)

Nierobisch, Thomas; Hoffmann, Frank; Krettek, Johannes; Bertram, Torsten

Dieser Beitrag präsentiert einen neuartigen Ansatz zur entkoppelten Regelung der Kamera-Blickrichtung und der Bewegung eines mobilen Roboters im Kontext der bildbasierten Navigation. Eine schwenkbare monokulare Kamera hält unabhängig von der Roboterbewegung die relevanten Merkmale für die Navigation im Sichtfeld. Die Entkopplung der Kamerablickrichtung von der eigentlichen Roboterbewegung wird durch die Projektion der Merkmale auf eine virtuelle Bildebene realisiert. In der virtuellen Bildebene hängt die Ausprägung der visuellen Merkmale für die bildbasierte Regelung nur von der Roboterposition ab und ist unabhängig gegenüber der tatsächlichen Blickrichtung der Kamera. Durch die Schwenkbarkeit der monokularen Kamera wird der Arbeitsbereich, über dem sich ein Referenzbild zur bildbasierten Regelung eignet, gegenüber einer statischen Kamera signifikant vergrößert. Dies ermöglicht die Navigation auch in texturarmen Umgebungen, die wenig verwertbare Textur- und Strukturmerkmale aufweisen.

Integrated system for single leg walking

NASA Astrophysics Data System (ADS)

Simmons, Reid; Krotkov, Eric; Roston, Gerry

1990-07-01

The Carnegie Mellon University Planetary Rover project is developing a six-legged walking robot capable of autonomously navigating, exploring, and acquiring samples in rugged, unknown environments. This report describes an integrated software system capable of navigating a single leg of the robot over rugged terrain. The leg, based on an early design of the Ambler Planetary Rover, is suspended below a carriage that slides along rails. To walk, the system creates an elevation map of the terrain from laser scanner images, plans an appropriate foothold based on terrain and geometric constraints, weaves the leg through the terrain to position it above the foothold, contacts the terrain with the foot, and applies force enough to advance the carriage along the rails. Walking both forward and backward, the system has traversed hundreds of meters of rugged terrain including obstacles too tall to step over, trenches too deep to step in, closely spaced obstacles, and sand hills. The implemented system consists of a number of task-specific processes (two for planning, two for perception, one for real-time control) and a central control process that directs the flow of communication between processes.

Mobile Robot Navigation and Obstacle Avoidance in Unstructured Outdoor Environments

DTIC Science & Technology

2017-12-01

to pull information from the network, it subscribes to a specific topic and is able to receive the messages that are published to that topic. In order...total artificial potential field is characterized “as the sum of an attractive potential pulling the robot toward the goal…and a repulsive potential...of robot laser_max = 20; % robot laser view horizon goaldist = 0.5; % distance metric for reaching goal goali = 1

A Concept of the Differentially Driven Three Wheeled Robot

NASA Astrophysics Data System (ADS)

Kelemen, M.; Colville, D. J.; Kelemenová, T.; Virgala, I.; Miková, L.

2013-08-01

The paper deals with the concept of a differentially driven three wheeled robot. The main task for the robot is to follow the navigation black line on white ground. The robot also contains anti-collision sensors for avoiding obstacles on track. Students learn how to deal with signals from sensors and how to control DC motors. Students work with the controller and develop the locomotion algorithm and can attend a competition

Absolute position calculation for a desktop mobile rehabilitation robot based on three optical mouse sensors.

PubMed

Zabaleta, Haritz; Valencia, David; Perry, Joel; Veneman, Jan; Keller, Thierry

2011-01-01

ArmAssist is a wireless robot for post stroke upper limb rehabilitation. Knowing the position of the arm is essential for any rehabilitation device. In this paper, we describe a method based on an artificial landmark navigation system. The navigation system uses three optical mouse sensors. This enables the building of a cheap but reliable position sensor. Two of the sensors are the data source for odometry calculations, and the third optical mouse sensor takes very low resolution pictures of a custom designed mat. These pictures are processed by an optical symbol recognition algorithm which will estimate the orientation of the robot and recognize the landmarks placed on the mat. The data fusion strategy is described to detect the misclassifications of the landmarks in order to fuse only reliable information. The orientation given by the optical symbol recognition (OSR) algorithm is used to improve significantly the odometry and the recognition of the landmarks is used to reference the odometry to a absolute coordinate system. The system was tested using a 3D motion capture system. With the actual mat configuration, in a field of motion of 710 × 450 mm, the maximum error in position estimation was 49.61 mm with an average error of 36.70 ± 22.50 mm. The average test duration was 36.5 seconds and the average path length was 4173 mm.

Terrain classification in navigation of an autonomous mobile robot

NASA Astrophysics Data System (ADS)

Dodds, David R.

1991-03-01

In this paper we describe a method of path planning that integrates terrain classification (by means of fractals) the certainty grid method of spatial representation Kehtarnavaz Griswold collision-zones Dubois Prade fuzzy temporal and spatial knowledge and non-point sized qualitative navigational planning. An initially planned (" end-to-end" ) path is piece-wise modified to accommodate known and inferred moving obstacles and includes attention to time-varying multiple subgoals which may influence a section of path at a time after the robot has begun traversing that planned path.

Remote controlled robot assisted cardiac navigation: feasibility assessment and validation in a porcine model.

PubMed

Ganji, Yusof; Janabi-Sharifi, Farrokh; Cheema, Asim N

2011-12-01

Despite the recent advances in catheter design and technology, intra-cardiac navigation during electrophysiology procedures remains challenging. Incorporation of imaging along with magnetic or robotic guidance may improve navigation accuracy and procedural safety. In the present study, the in vivo performance of a novel remote controlled Robot Assisted Cardiac Navigation System (RACN) was evaluated in a porcine model. The navigation catheter and target sensor were advanced to the right atrium using fluoroscopic and intra-cardiac echo guidance. The target sensor was positioned at three target locations in the right atrium (RA) and the navigation task was completed by an experienced physician using both manual and RACN guidance. The navigation time, final distance between the catheter tip and target sensor, and variability in final catheter tip position were determined and compared for manual and RACN guided navigation. The experiments were completed in three animals and five measurements recorded for each target location. The mean distance (mm) between catheter tip and target sensor at the end of the navigation task was significantly less using RACN guidance compared with manual navigation (5.02 ± 0.31 vs. 9.66 ± 2.88, p = 0.050 for high RA, 9.19 ± 1.13 vs. 13.0 ± 1.00, p = 0.011 for low RA and 6.77 ± 0.59 vs. 15.66 ± 2.51, p = 0.003 for tricuspid valve annulus). The average time (s) needed to complete the navigation task was significantly longer by RACN guided navigation compared with manual navigation (43.31 ± 18.19 vs. 13.54 ± 1.36, p = 0.047 for high RA, 43.71 ± 11.93 vs. 22.71 ± 3.79, p = 0.043 for low RA and 37.84 ± 3.71 vs. 16.13 ± 4.92, p = 0.003 for tricuspid valve annulus. RACN guided navigation resulted in greater consistency in performance compared with manual navigation as evidenced by lower variability in final distance measurements (0.41 vs. 0.99 mm, p = 0.04). This study demonstrated the safety and feasibility of the RACN system for cardiac navigation. The results demonstrated that RACN performed comparably with manual navigation, with improved precision and consistency for targets located in and near the right atrial chamber. Copyright © 2011 John Wiley & Sons, Ltd.

On autonomous terrain model acquistion by a mobile robot

NASA Technical Reports Server (NTRS)

Rao, N. S. V.; Iyengar, S. S.; Weisbin, C. R.

1987-01-01

The following problem is considered: A point robot is placed in a terrain populated by an unknown number of polyhedral obstacles of varied sizes and locations in two/three dimensions. The robot is equipped with a sensor capable of detecting all the obstacle vertices and edges that are visible from the present location of the robot. The robot is required to autonomously navigate and build the complete terrain model using the sensor information. It is established that the necessary number of scanning operations needed for complete terrain model acquisition by any algorithm that is based on scan from vertices strategy is given by the summation of i = 1 (sup n) N(O sub i)-n and summation of i = 1 (sup n) N(O sub i)-2n in two- and three-dimensional terrains respectively, where O = (O sub 1, O sub 2,....O sub n) set of the obstacles in the terrain, and N(O sub i) is the number of vertices of the obstacle O sub i.

A Novel Robot Visual Homing Method Based on SIFT Features

PubMed Central

Zhu, Qidan; Liu, Chuanjia; Cai, Chengtao

2015-01-01

Warping is an effective visual homing method for robot local navigation. However, the performance of the warping method can be greatly influenced by the changes of the environment in a real scene, thus resulting in lower accuracy. In order to solve the above problem and to get higher homing precision, a novel robot visual homing algorithm is proposed by combining SIFT (scale-invariant feature transform) features with the warping method. The algorithm is novel in using SIFT features as landmarks instead of the pixels in the horizon region of the panoramic image. In addition, to further improve the matching accuracy of landmarks in the homing algorithm, a novel mismatching elimination algorithm, based on the distribution characteristics of landmarks in the catadioptric panoramic image, is proposed. Experiments on image databases and on a real scene confirm the effectiveness of the proposed method. PMID:26473880

Integrated Network Architecture for Sustained Human and Robotic Exploration

NASA Technical Reports Server (NTRS)

Noreen, Gary; Cesarone, Robert; Deutsch, Leslie; Edwards, Charles; Soloff, Jason; Ely, Todd; Cook, Brian; Morabito, David; Hemmati, Hamid; Piazolla, Sabino;

Vision based object pose estimation for mobile robots

NASA Technical Reports Server (NTRS)

Wu, Annie; Bidlack, Clint; Katkere, Arun; Feague, Roy; Weymouth, Terry

1994-01-01

Mobile robot navigation using visual sensors requires that a robot be able to detect landmarks and obtain pose information from a camera image. This paper presents a vision system for finding man-made markers of known size and calculating the pose of these markers. The algorithm detects and identifies the markers using a weighted pattern matching template. Geometric constraints are then used to calculate the position of the markers relative to the robot. The selection of geometric constraints comes from the typical pose of most man-made signs, such as the sign standing vertical and the dimensions of known size. This system has been tested successfully on a wide range of real images. Marker detection is reliable, even in cluttered environments, and under certain marker orientations, estimation of the orientation has proven accurate to within 2 degrees, and distance estimation to within 0.3 meters.

Telecommunications, navigation and information management concept overview for the Space Exploration Initiative program

NASA Technical Reports Server (NTRS)

Bell, Jerome A.; Stephens, Elaine; Barton, Gregg

1991-01-01

An overview is provided of the Space Exploration Initiative (SEI) concepts for telecommunications, information systems, and navigation (TISN), and engineering and architecture issues are discussed. The SEI program data system is reviewed to identify mission TISN interfaces, and reference TISN concepts are described for nominal, degraded, and mission-critical data services. The infrastructures reviewed include telecommunications for robotics support, autonomous navigation without earth-based support, and information networks for tracking and data acquisition. Four options for TISN support architectures are examined which relate to unique SEI exploration strategies. Detailed support estimates are given for: (1) a manned stay on Mars; (2) permanent lunar and Martian settlements; short-duration missions; and (4) systematic exploration of the moon and Mars.

Robotics and Virtual Reality for Cultural Heritage Digitization and Fruition

NASA Astrophysics Data System (ADS)

Calisi, D.; Cottefoglie, F.; D'Agostini, L.; Giannone, F.; Nenci, F.; Salonia, P.; Zaratti, M.; Ziparo, V. A.

2017-05-01

In this paper we present our novel approach for acquiring and managing digital models of archaeological sites, and the visualization techniques used to showcase them. In particular, we will demonstrate two technologies: our robotic system for digitization of archaeological sites (DigiRo) result of over three years of efforts by a group of cultural heritage experts, computer scientists and roboticists, and our cloud-based archaeological information system (ARIS). Finally we describe the viewers we developed to inspect and navigate the 3D models: a viewer for the web (ROVINA Web Viewer) and an immersive viewer for Virtual Reality (ROVINA VR Viewer).

Efficient Multi-Concept Visual Classifier Adaptation in Changing Environments

DTIC Science & Technology

2016-09-01

yet to be discussed in existing supervised multi-concept visual perception systems used in robotics applications.1,5–7 Anno - tation of images is...Autonomous robot navigation in highly populated pedestrian zones. J Field Robotics. 2015;32(4):565–589. 3. Milella A, Reina G, Underwood J . A self...learning framework for statistical ground classification using RADAR and monocular vision. J Field Robotics. 2015;32(1):20–41. 4. Manjanna S, Dudek G

Bio-inspired vision based robot control using featureless estimations of time-to-contact.

PubMed

Zhang, Haijie; Zhao, Jianguo

2017-01-31

Marvelous vision based dynamic behaviors of insects and birds such as perching, landing, and obstacle avoidance have inspired scientists to propose the idea of time-to-contact, which is defined as the time for a moving observer to contact an object or surface if the current velocity is maintained. Since with only a vision sensor, time-to-contact can be directly estimated from consecutive images, it is widely used for a variety of robots to fulfill various tasks such as obstacle avoidance, docking, chasing, perching and landing. However, most of existing methods to estimate the time-to-contact need to extract and track features during the control process, which is time-consuming and cannot be applied to robots with limited computation power. In this paper, we adopt a featureless estimation method, extend this method to more general settings with angular velocities, and improve the estimation results using Kalman filtering. Further, we design an error based controller with gain scheduling strategy to control the motion of mobile robots. Experiments for both estimation and control are conducted using a customized mobile robot platform with low-cost embedded systems. Onboard experimental results demonstrate the effectiveness of the proposed approach, with the robot being controlled to successfully dock in front of a vertical wall. The estimation and control methods presented in this paper can be applied to computation-constrained miniature robots for agile locomotion such as landing, docking, or navigation.

ATON (Autonomous Terrain-based Optical Navigation) for exploration missions: recent flight test results

NASA Astrophysics Data System (ADS)

Theil, S.; Ammann, N.; Andert, F.; Franz, T.; Krüger, H.; Lehner, H.; Lingenauber, M.; Lüdtke, D.; Maass, B.; Paproth, C.; Wohlfeil, J.

2018-03-01

Since 2010 the German Aerospace Center is working on the project Autonomous Terrain-based Optical Navigation (ATON). Its objective is the development of technologies which allow autonomous navigation of spacecraft in orbit around and during landing on celestial bodies like the Moon, planets, asteroids and comets. The project developed different image processing techniques and optical navigation methods as well as sensor data fusion. The setup—which is applicable to many exploration missions—consists of an inertial measurement unit, a laser altimeter, a star tracker and one or multiple navigation cameras. In the past years, several milestones have been achieved. It started with the setup of a simulation environment including the detailed simulation of camera images. This was continued by hardware-in-the-loop tests in the Testbed for Robotic Optical Navigation (TRON) where images were generated by real cameras in a simulated downscaled lunar landing scene. Data were recorded in helicopter flight tests and post-processed in real-time to increase maturity of the algorithms and to optimize the software. Recently, two more milestones have been achieved. In late 2016, the whole navigation system setup was flying on an unmanned helicopter while processing all sensor information onboard in real time. For the latest milestone the navigation system was tested in closed-loop on the unmanned helicopter. For that purpose the ATON navigation system provided the navigation state for the guidance and control of the unmanned helicopter replacing the GPS-based standard navigation system. The paper will give an introduction to the ATON project and its concept. The methods and algorithms of ATON are briefly described. The flight test results of the latest two milestones are presented and discussed.

Path planning in GPS-denied environments via collective intelligence of distributed sensor networks

NASA Astrophysics Data System (ADS)

Jha, Devesh K.; Chattopadhyay, Pritthi; Sarkar, Soumik; Ray, Asok

2016-05-01

This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin's car-like robot.

An Intelligent Robotic Hospital Bed for Safe Transportation of Critical Neurosurgery Patients Along Crowded Hospital Corridors.

PubMed

Wang, Chao; Savkin, Andrey V; Clout, Ray; Nguyen, Hung T

2015-09-01

We present a novel design of an intelligent robotic hospital bed, named Flexbed, with autonomous navigation ability. The robotic bed is developed for fast and safe transportation of critical neurosurgery patients without changing beds. Flexbed is more efficient and safe during the transportation process comparing to the conventional hospital beds. Flexbed is able to avoid en-route obstacles with an efficient easy-to-implement collision avoidance strategy when an obstacle is nearby and to move towards its destination at maximum speed when there is no threat of collision. We present extensive simulation results of navigation of Flexbed in the crowded hospital corridor environments with moving obstacles. Moreover, results of experiments with Flexbed in the real world scenarios are also presented and discussed.

Draper Laboratory small autonomous aerial vehicle

NASA Astrophysics Data System (ADS)

DeBitetto, Paul A.; Johnson, Eric N.; Bosse, Michael C.; Trott, Christian A.

1997-06-01

The Charles Stark Draper Laboratory, Inc. and students from Massachusetts Institute of Technology and Boston University have cooperated to develop an autonomous aerial vehicle that won the 1996 International Aerial Robotics Competition. This paper describes the approach, system architecture and subsystem designs for the entry. This entry represents a combination of many technology areas: navigation, guidance, control, vision processing, human factors, packaging, power, real-time software, and others. The aerial vehicle, an autonomous helicopter, performs navigation and control functions using multiple sensors: differential GPS, inertial measurement unit, sonar altimeter, and a flux compass. The aerial transmits video imagery to the ground. A ground based vision processor converts the image data into target position and classification estimates. The system was designed, built, and flown in less than one year and has provided many lessons about autonomous vehicle systems, several of which are discussed. In an appendix, our current research in augmenting the navigation system with vision- based estimates is presented.

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-11

Team KuuKulgur waits to begin the level one challenge during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Wednesday, June 11, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Wednesday, June 11, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

Robot map building based on fuzzy-extending DSmT

NASA Astrophysics Data System (ADS)

Li, Xinde; Huang, Xinhan; Wu, Zuyu; Peng, Gang; Wang, Min; Xiong, Youlun

2007-11-01

With the extensive application of mobile robots in many different fields, map building in unknown environments has been one of the principal issues in the field of intelligent mobile robot. However, Information acquired in map building presents characteristics of uncertainty, imprecision and even high conflict, especially in the course of building grid map using sonar sensors. In this paper, we extended DSmT with Fuzzy theory by considering the different fuzzy T-norm operators (such as Algebraic Product operator, Bounded Product operator, Einstein Product operator and Default minimum operator), in order to develop a more general and flexible combinational rule for more extensive application. At the same time, we apply fuzzy-extended DSmT to mobile robot map building with the help of new self-localization method based on neighboring field appearance matching( -NFAM), to make the new tool more robust in very complex environment. An experiment is conducted to reconstruct the map with the new tool in indoor environment, in order to compare their performances in map building with four T-norm operators, when Pioneer II mobile robot runs along the same trace. Finally, a conclusion is reached that this study develops a new idea to extend DSmT, also provides a new approach for autonomous navigation of mobile robot, and provides a human-computer interactive interface to manage and manipulate the robot remotely.

Soft Robotic Manipulator for Improving Dexterity in Minimally Invasive Surgery.

PubMed

Diodato, Alessandro; Brancadoro, Margherita; De Rossi, Giacomo; Abidi, Haider; Dall'Alba, Diego; Muradore, Riccardo; Ciuti, Gastone; Fiorini, Paolo; Menciassi, Arianna; Cianchetti, Matteo

2018-02-01

Combining the strengths of surgical robotics and minimally invasive surgery (MIS) holds the potential to revolutionize surgical interventions. The MIS advantages for the patients are obvious, but the use of instrumentation suitable for MIS often translates in limiting the surgeon capabilities (eg, reduction of dexterity and maneuverability and demanding navigation around organs). To overcome these shortcomings, the application of soft robotics technologies and approaches can be beneficial. The use of devices based on soft materials is already demonstrating several advantages in all the exploitation areas where dexterity and safe interaction are needed. In this article, the authors demonstrate that soft robotics can be synergistically used with traditional rigid tools to improve the robotic system capabilities and without affecting the usability of the robotic platform. A bioinspired soft manipulator equipped with a miniaturized camera has been integrated with the Endoscopic Camera Manipulator arm of the da Vinci Research Kit both from hardware and software viewpoints. Usability of the integrated system has been evaluated with nonexpert users through a standard protocol to highlight difficulties in controlling the soft manipulator. This is the first time that an endoscopic tool based on soft materials has been integrated into a surgical robot. The soft endoscopic camera can be easily operated through the da Vinci Research Kit master console, thus increasing the workspace and the dexterity, and without limiting intuitive and friendly use.

New methods of measuring and calibrating robots

NASA Astrophysics Data System (ADS)

Janocha, Hartmut; Diewald, Bernd

1995-10-01

ISO 9283 and RIA R15.05 define industrial robot parameters which are applied to compare the efficiency of different robots. Hitherto, however, no suitable measurement systems have been available. ICAROS is a system which combines photogrammetrical procedures with an inertial navigation system. For the first time, this combination allows the high-precision static and dynamic measurement of the position as well as of the orientation of the robot endeffector. Thus, not only the measuring data for the determination of all industrial robot parameters can be acquired. By integration of a new over-all-calibration procedure, ICAROS also allows the reduction of the absolute robot pose errors to the range of its repeatability. The integration of both system components as well as measurement and calibration results are presented in this paper, using a six-axes robot as example. A further approach also presented here takes into consideration not only the individual robot errors but also the tolerances of workpieces. This allows the adjustment of off-line programs of robots based on inexact or idealized CAD data in any pose. Thus the robot position which is defined relative to the workpiece to be processed, is achieved as required. This includes the possibility to transfer teached robot programs to other devices without additional expenditure. The adjustment is based on the measurement of the robot position using two miniaturized CCD cameras mounted near the endeffector which are carried along by the robot during the correction phase. In the area viewed by both cameras, the robot position is determined in relation to prominent geometry elements, e.g. lines or holes. The scheduled data to be compared therewith can either be calculated in modern off-line programming systems during robot programming, or they can be determined at the so-called master robot if a transfer of the robot program is desired.

Flexible Virtual Structure Consideration in Dynamic Modeling of Mobile Robots Formation

NASA Astrophysics Data System (ADS)

El Kamel, A. Essghaier; Beji, L.; Lerbet, J.; Abichou, A.

2009-03-01

In cooperative mobile robotics, we look for formation keeping and maintenance of a geometric configuration during movement. As a solution to these problems, the concept of a virtual structure is considered. Based on this idea, we have developed an efficient flexible virtual structure, describing the dynamic model of n vehicles in formation and where the whole formation is kept dependant. Notes that, for 2D and 3D space navigation, only a rigid virtual structure was proposed in the literature. Further, the problem was limited to a kinematic behavior of the structure. Hence, the flexible virtual structure in dynamic modeling of mobile robots formation presented in this paper, gives more capabilities to the formation to avoid obstacles in hostile environment while keeping formation and avoiding inter-agent collision.

Automated site characterization for robotic sample acquisition systems

NASA Astrophysics Data System (ADS)

Scholl, Marija S.; Eberlein, Susan J.

1993-04-01

A mobile, semiautonomous vehicle with multiple sensors and on-board intelligence is proposed for performing preliminary scientific investigations on extraterrestrial bodies prior to human exploration. Two technologies, a hybrid optical-digital computer system based on optical correlator technology and an image and instrument data analysis system, provide complementary capabilities that might be part of an instrument package for an intelligent robotic vehicle. The hybrid digital-optical vision system could perform real-time image classification tasks using an optical correlator with programmable matched filters under control of a digital microcomputer. The data analysis system would analyze visible and multiband imagery to extract mineral composition and textural information for geologic characterization. Together these technologies would support the site characterization needs of a robotic vehicle for both navigational and scientific purposes.

Human-like robots for space and hazardous environments

NASA Technical Reports Server (NTRS)

1994-01-01

The three year goal for the Kansas State USRA/NASA Senior Design team is to design and build a walking autonomous robotic rover. The rover should be capable of crossing rough terrain, traversing human made obstacles (such as stairs and doors), and moving through human and robot occupied spaces without collision. The rover is also to evidence considerable decision making ability, navigation, and path planning skills.

Human-like robots for space and hazardous environments

NASA Astrophysics Data System (ADS)

The three year goal for the Kansas State USRA/NASA Senior Design team is to design and build a walking autonomous robotic rover. The rover should be capable of crossing rough terrain, traversing human made obstacles (such as stairs and doors), and moving through human and robot occupied spaces without collision. The rover is also to evidence considerable decision making ability, navigation, and path planning skills.

Human-like robots for space and hazardous environments

NASA Technical Reports Server (NTRS)

Cogley, Allen; Gustafson, David; White, Warren; Dyer, Ruth; Hampton, Tom (Editor); Freise, Jon (Editor)

1990-01-01

The three year goal for this NASA Senior Design team is to design and build a walking autonomous robotic rover. The rover should be capable of rough terrain crossing, traversing human made obstacles (such as stairs and doors), and moving through human and robot occupied spaces without collision. The rover is also to evidence considerable decision making ability, navigation and path planning skills. These goals came from the concept that the robot should have the abilities of both a planetary rover and a hazardous waste site scout.

Human-like robots for space and hazardous environments

NASA Astrophysics Data System (ADS)

Cogley, Allen; Gustafson, David; White, Warren; Dyer, Ruth; Hampton, Tom; Freise, Jon

The three year goal for this NASA Senior Design team is to design and build a walking autonomous robotic rover. The rover should be capable of rough terrain crossing, traversing human made obstacles (such as stairs and doors), and moving through human and robot occupied spaces without collision. The rover is also to evidence considerable decision making ability, navigation and path planning skills. These goals came from the concept that the robot should have the abilities of both a planetary rover and a hazardous waste site scout.

Online Learning Techniques for Improving Robot Navigation in Unfamiliar Domains

DTIC Science & Technology

2010-12-01

In In Proceedings of the 1996 Symposium on Human Interaction and Complex Systems, pages 276–283, 1996. 6.1 [15] Colin Campbell and Kristin P. Bennett...ISBN 0-262-19450-3. 5.1 [104] Jean Scholtz, Jeff Young, Jill L. Drury , and Holly A. Yanco. Evaluation of human-robot interaction awareness in search...2004. 6.1 [147] Holly A. Yanco and Jill L. Drury . Rescuing interfaces: A multi-year study of human-robot interaction at the AAAI robot rescue

Autonomous Robotic Inspection in Tunnels

NASA Astrophysics Data System (ADS)

Protopapadakis, E.; Stentoumis, C.; Doulamis, N.; Doulamis, A.; Loupos, K.; Makantasis, K.; Kopsiaftis, G.; Amditis, A.

2016-06-01

In this paper, an automatic robotic inspector for tunnel assessment is presented. The proposed platform is able to autonomously navigate within the civil infrastructures, grab stereo images and process/analyse them, in order to identify defect types. At first, there is the crack detection via deep learning approaches. Then, a detailed 3D model of the cracked area is created, utilizing photogrammetric methods. Finally, a laser profiling of the tunnel's lining, for a narrow region close to detected crack is performed; allowing for the deduction of potential deformations. The robotic platform consists of an autonomous mobile vehicle; a crane arm, guided by the computer vision-based crack detector, carrying ultrasound sensors, the stereo cameras and the laser scanner. Visual inspection is based on convolutional neural networks, which support the creation of high-level discriminative features for complex non-linear pattern classification. Then, real-time 3D information is accurately calculated and the crack position and orientation is passed to the robotic platform. The entire system has been evaluated in railway and road tunnels, i.e. in Egnatia Highway and London underground infrastructure.

A Robot to Help Make the Rounds

NASA Technical Reports Server (NTRS)

2003-01-01

This paper presents a discussion on the Pyxis HelpMate SecurePak (SP) trackless robotic courier designed by Transitions Research Corporation, to navigate autonomously throughout medical facilities, transporting pharmaceuticals, laboratory specimens, equipment, supplies, meals, medical records, and radiology films between support departments and nursing floors.

Kennedy Space Center, Space Shuttle Processing, and International Space Station Program Overview

NASA Technical Reports Server (NTRS)

Higginbotham, Scott Alan

2011-01-01

Topics include: International Space Station assembly sequence; Electrical power substation; Thermal control substation; Guidance, navigation and control; Command data and handling; Robotics; Human and robotic integration; Additional modes of re-supply; NASA and International partner control centers; Space Shuttle ground operations.

Combined Feature Based and Shape Based Visual Tracker for Robot Navigation

NASA Technical Reports Server (NTRS)

Deans, J.; Kunz, C.; Sargent, R.; Park, E.; Pedersen, L.

2005-01-01

We have developed a combined feature based and shape based visual tracking system designed to enable a planetary rover to visually track and servo to specific points chosen by a user with centimeter precision. The feature based tracker uses invariant feature detection and matching across a stereo pair, as well as matching pairs before and after robot movement in order to compute an incremental 6-DOF motion at each tracker update. This tracking method is subject to drift over time, which can be compensated by the shape based method. The shape based tracking method consists of 3D model registration, which recovers 6-DOF motion given sufficient shape and proper initialization. By integrating complementary algorithms, the combined tracker leverages the efficiency and robustness of feature based methods with the precision and accuracy of model registration. In this paper, we present the algorithms and their integration into a combined visual tracking system.

Technological advances in robotic-assisted laparoscopic surgery.

PubMed

Tan, Gerald Y; Goel, Raj K; Kaouk, Jihad H; Tewari, Ashutosh K

2009-05-01

In this article, the authors describe the evolution of urologic robotic systems and the current state-of-the-art features and existing limitations of the da Vinci S HD System (Intuitive Surgical, Inc.). They then review promising innovations in scaling down the footprint of robotic platforms, the early experience with mobile miniaturized in vivo robots, advances in endoscopic navigation systems using augmented reality technologies and tracking devices, the emergence of technologies for robotic natural orifice transluminal endoscopic surgery and single-port surgery, advances in flexible robotics and haptics, the development of new virtual reality simulator training platforms compatible with the existing da Vinci system, and recent experiences with remote robotic surgery and telestration.

Multigait soft robot

PubMed Central

Shepherd, Robert F.; Ilievski, Filip; Choi, Wonjae; Morin, Stephen A.; Stokes, Adam A.; Mazzeo, Aaron D.; Chen, Xin; Wang, Michael; Whitesides, George M.

2011-01-01

This manuscript describes a unique class of locomotive robot: A soft robot, composed exclusively of soft materials (elastomeric polymers), which is inspired by animals (e.g., squid, starfish, worms) that do not have hard internal skeletons. Soft lithography was used to fabricate a pneumatically actuated robot capable of sophisticated locomotion (e.g., fluid movement of limbs and multiple gaits). This robot is quadrupedal; it uses no sensors, only five actuators, and a simple pneumatic valving system that operates at low pressures (< 10 psi). A combination of crawling and undulation gaits allowed this robot to navigate a difficult obstacle. This demonstration illustrates an advantage of soft robotics: They are systems in which simple types of actuation produce complex motion. PMID:22123978

Optimal Navigation of Self-Propelled Colloids in Microstructured Mazes

NASA Astrophysics Data System (ADS)

Yang, Yuguang; Bevan, Michael

Controlling navigation of self-propelled microscopic `robots' subject to random Brownian motion in complex microstructured environments (e.g., porous media, tumor vasculature) is important to many emerging applications (e.g., enhanced oil recovery, drug delivery). In this work, we design an optimal feedback policy to navigate an active self-propelled colloidal rod in complex mazes with various obstacle types. Actuation of the rods is modelled based on a light-controlled osmotic flow mechanism, which produces different propulsion velocities along the rod's long axis. Actuator-parameterized Langevin equations, with soft rod-obstacle repulsive interactions, are developed to describe the system dynamics. A Markov decision process (MDP) framework is used for optimal policy calculations with design goals of colloidal rods reaching target end points in minimum time. Simulations show that optimal MDP-based policies are able to control rod trajectories to reach target regions order-of-magnitudes faster than uncontrolled rods, which diverges as maze complexity increases. An efficient multi-graph based implementation for MDP is also presented, which scales linearly with the maze dimension.

Extraction of user's navigation commands from upper body force interaction in walker assisted gait.

PubMed

Frizera Neto, Anselmo; Gallego, Juan A; Rocon, Eduardo; Pons, José L; Ceres, Ramón

2010-08-05

The advances in technology make possible the incorporation of sensors and actuators in rollators, building safer robots and extending the use of walkers to a more diverse population. This paper presents a new method for the extraction of navigation related components from upper-body force interaction data in walker assisted gait. A filtering architecture is designed to cancel: (i) the high-frequency noise caused by vibrations on the walker's structure due to irregularities on the terrain or walker's wheels and (ii) the cadence related force components caused by user's trunk oscillations during gait. As a result, a third component related to user's navigation commands is distinguished. For the cancelation of high-frequency noise, a Benedict-Bordner g-h filter was designed presenting very low values for Kinematic Tracking Error ((2.035 +/- 0.358).10(-2) kgf) and delay ((1.897 +/- 0.3697).10(1)ms). A Fourier Linear Combiner filtering architecture was implemented for the adaptive attenuation of about 80% of the cadence related components' energy from force data. This was done without compromising the information contained in the frequencies close to such notch filters. The presented methodology offers an effective cancelation of the undesired components from force data, allowing the system to extract in real-time voluntary user's navigation commands. Based on this real-time identification of voluntary user's commands, a classical approach to the control architecture of the robotic walker is being developed, in order to obtain stable and safe user assisted locomotion.

Collective navigation of cargo-carrying swarms

PubMed Central

Shklarsh, Adi; Finkelshtein, Alin; Ariel, Gil; Kalisman, Oren; Ingham, Colin; Ben-Jacob, Eshel

2012-01-01

Much effort has been devoted to the study of swarming and collective navigation of micro-organisms, insects, fish, birds and other organisms, as well as multi-agent simulations and to the study of real robots. It is well known that insect swarms can carry cargo. The studies here are motivated by a less well-known phenomenon: cargo transport by bacteria swarms. We begin with a concise review of how bacteria swarms carry natural, micrometre-scale objects larger than the bacteria (e.g. fungal spores) as well as man-made beads and capsules (for drug delivery). A comparison of the trajectories of virtual beads in simulations (using different putative coupling between the virtual beads and the bacteria) with the observed trajectories of transported fungal spores implies the existence of adaptable coupling. Motivated by these observations, we devised new, multi-agent-based studies of cargo transport by agent swarms. As a first step, we extended previous modelling of collective navigation of simple bacteria-inspired agents in complex terrain, using three putative models of agent–cargo coupling. We found that cargo-carrying swarms can navigate efficiently in a complex landscape. We further investigated how the stability, elasticity and other features of agent–cargo bonds influence the collective motion and the transport of the cargo, and found sharp phase shifts and dual successful strategies for cargo delivery. Further understanding of such mechanisms may provide valuable clues to understand cargo-transport by smart swarms of other organisms as well as by man-made swarming robots. PMID:24312731

Cerebellum Augmented Rover Development

NASA Technical Reports Server (NTRS)

King, Matthew

2005-01-01

Bio-Inspired Technologies and Systems (BITS) are a very natural result of thinking about Nature's way of solving problems. Knowledge of animal behaviors an be used in developing robotic behaviors intended for planetary exploration. This is the expertise of the JFL BITS Group and has served as a philosophical model for NMSU RioRobolab. Navigation is a vital function for any autonomous system. Systems must have the ability to determine a safe path between their current location and some target location. The MER mission, as well as other JPL rover missions, uses a method known as dead-reckoning to determine position information. Dead-reckoning uses wheel encoders to sense the wheel's rotation. In a sandy environment such as Mars, this method is highly inaccurate because the wheels will slip in the sand. Improving positioning error will allow the speed of an autonomous navigating rover to be greatly increased. Therefore, local navigation based upon landmark tracking is desirable in planetary exploration. The BITS Group is developing navigation technology based upon landmark tracking. Integration of the current rover architecture with a cerebellar neural network tracking algorithm will demonstrate that this approach to navigation is feasible and should be implemented in future rover and spacecraft missions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pin, F.G.; Bender, S.R.

Most fuzzy logic-based reasoning schemes developed for robot control are fully reactive, i.e., the reasoning modules consist of fuzzy rule bases that represent direct mappings from the stimuli provided by the perception systems to the responses implemented by the motion controllers. Due to their totally reactive nature, such reasoning systems can encounter problems such as infinite loops and limit cycles. In this paper, we proposed an approach to remedy these problems by adding a memory and memory-related behaviors to basic reactive systems. Three major types of memory behaviors are addressed: memory creation, memory management, and memory utilization. These are firstmore » presented, and examples of their implementation for the recognition of limit cycles during the navigation of an autonomous robot in a priori unknown environments are then discussed.« less

Goal-recognition-based adaptive brain-computer interface for navigating immersive robotic systems.

PubMed

Abu-Alqumsan, Mohammad; Ebert, Felix; Peer, Angelika

2017-06-01

This work proposes principled strategies for self-adaptations in EEG-based Brain-computer interfaces (BCIs) as a way out of the bandwidth bottleneck resulting from the considerable mismatch between the low-bandwidth interface and the bandwidth-hungry application, and a way to enable fluent and intuitive interaction in embodiment systems. The main focus is laid upon inferring the hidden target goals of users while navigating in a remote environment as a basis for possible adaptations. To reason about possible user goals, a general user-agnostic Bayesian update rule is devised to be recursively applied upon the arrival of evidences, i.e. user input and user gaze. Experiments were conducted with healthy subjects within robotic embodiment settings to evaluate the proposed method. These experiments varied along three factors: the type of the robot/environment (simulated and physical), the type of the interface (keyboard or BCI), and the way goal recognition (GR) is used to guide a simple shared control (SC) driving scheme. Our results show that the proposed GR algorithm is able to track and infer the hidden user goals with relatively high precision and recall. Further, the realized SC driving scheme benefits from the output of the GR system and is able to reduce the user effort needed to accomplish the assigned tasks. Despite the fact that the BCI requires higher effort compared to the keyboard conditions, most subjects were able to complete the assigned tasks, and the proposed GR system is additionally shown able to handle the uncertainty in user input during SSVEP-based interaction. The SC application of the belief vector indicates that the benefits of the GR module are more pronounced for BCIs, compared to the keyboard interface. Being based on intuitive heuristics that model the behavior of the general population during the execution of navigation tasks, the proposed GR method can be used without prior tuning for the individual users. The proposed methods can be easily integrated in devising more advanced SC schemes and/or strategies for automatic BCI self-adaptations.

Goal-recognition-based adaptive brain-computer interface for navigating immersive robotic systems

NASA Astrophysics Data System (ADS)

Abu-Alqumsan, Mohammad; Ebert, Felix; Peer, Angelika

2017-06-01

Objective. This work proposes principled strategies for self-adaptations in EEG-based Brain-computer interfaces (BCIs) as a way out of the bandwidth bottleneck resulting from the considerable mismatch between the low-bandwidth interface and the bandwidth-hungry application, and a way to enable fluent and intuitive interaction in embodiment systems. The main focus is laid upon inferring the hidden target goals of users while navigating in a remote environment as a basis for possible adaptations. Approach. To reason about possible user goals, a general user-agnostic Bayesian update rule is devised to be recursively applied upon the arrival of evidences, i.e. user input and user gaze. Experiments were conducted with healthy subjects within robotic embodiment settings to evaluate the proposed method. These experiments varied along three factors: the type of the robot/environment (simulated and physical), the type of the interface (keyboard or BCI), and the way goal recognition (GR) is used to guide a simple shared control (SC) driving scheme. Main results. Our results show that the proposed GR algorithm is able to track and infer the hidden user goals with relatively high precision and recall. Further, the realized SC driving scheme benefits from the output of the GR system and is able to reduce the user effort needed to accomplish the assigned tasks. Despite the fact that the BCI requires higher effort compared to the keyboard conditions, most subjects were able to complete the assigned tasks, and the proposed GR system is additionally shown able to handle the uncertainty in user input during SSVEP-based interaction. The SC application of the belief vector indicates that the benefits of the GR module are more pronounced for BCIs, compared to the keyboard interface. Significance. Being based on intuitive heuristics that model the behavior of the general population during the execution of navigation tasks, the proposed GR method can be used without prior tuning for the individual users. The proposed methods can be easily integrated in devising more advanced SC schemes and/or strategies for automatic BCI self-adaptations.

Medical robotics.

PubMed

Ferrigno, Giancarlo; Baroni, Guido; Casolo, Federico; De Momi, Elena; Gini, Giuseppina; Matteucci, Matteo; Pedrocchi, Alessandra

2011-01-01

Information and communication technology (ICT) and mechatronics play a basic role in medical robotics and computer-aided therapy. In the last three decades, in fact, ICT technology has strongly entered the health-care field, bringing in new techniques to support therapy and rehabilitation. In this frame, medical robotics is an expansion of the service and professional robotics as well as other technologies, as surgical navigation has been introduced especially in minimally invasive surgery. Localization systems also provide treatments in radiotherapy and radiosurgery with high precision. Virtual or augmented reality plays a role for both surgical training and planning and for safe rehabilitation in the first stage of the recovery from neurological diseases. Also, in the chronic phase of motor diseases, robotics helps with special assistive devices and prostheses. Although, in the past, the actual need and advantage of navigation, localization, and robotics in surgery and therapy has been in doubt, today, the availability of better hardware (e.g., microrobots) and more sophisticated algorithms(e.g., machine learning and other cognitive approaches)has largely increased the field of applications of these technologies,making it more likely that, in the near future, their presence will be dramatically increased, taking advantage of the generational change of the end users and the increasing request of quality in health-care delivery and management.

A tesselated probabilistic representation for spatial robot perception and navigation

NASA Technical Reports Server (NTRS)

Elfes, Alberto

1989-01-01

The ability to recover robust spatial descriptions from sensory information and to efficiently utilize these descriptions in appropriate planning and problem-solving activities are crucial requirements for the development of more powerful robotic systems. Traditional approaches to sensor interpretation, with their emphasis on geometric models, are of limited use for autonomous mobile robots operating in and exploring unknown and unstructured environments. Here, researchers present a new approach to robot perception that addresses such scenarios using a probabilistic tesselated representation of spatial information called the Occupancy Grid. The Occupancy Grid is a multi-dimensional random field that maintains stochastic estimates of the occupancy state of each cell in the grid. The cell estimates are obtained by interpreting incoming range readings using probabilistic models that capture the uncertainty in the spatial information provided by the sensor. A Bayesian estimation procedure allows the incremental updating of the map using readings taken from several sensors over multiple points of view. An overview of the Occupancy Grid framework is given, and its application to a number of problems in mobile robot mapping and navigation are illustrated. It is argued that a number of robotic problem-solving activities can be performed directly on the Occupancy Grid representation. Some parallels are drawn between operations on Occupancy Grids and related image processing operations.

A 6-DOF parallel bone-grinding robot for cervical disc replacement surgery.

PubMed

Tian, Heqiang; Wang, Chenchen; Dang, Xiaoqing; Sun, Lining

2017-12-01

Artificial cervical disc replacement surgery has become an effective and main treatment method for cervical disease, which has become a more common and serious problem for people with sedentary work. To improve cervical disc replacement surgery significantly, a 6-DOF parallel bone-grinding robot is developed for cervical bone-grinding by image navigation and surgical plan. The bone-grinding robot including mechanical design and low level control is designed. The bone-grinding robot navigation is realized by optical positioning with spatial registration coordinate system defined. And a parametric robot bone-grinding plan and high level control have been developed for plane grinding for cervical top endplate and tail endplate grinding by a cylindrical grinding drill and spherical grinding for two articular surfaces of bones by a ball grinding drill. Finally, the surgical flow for a robot-assisted cervical disc replacement surgery procedure is present. The final experiments results verified the key technologies and performance of the robot-assisted surgery system concept excellently, which points out a promising clinical application with higher operability. Finally, study innovations, study limitations, and future works of this present study are discussed, and conclusions of this paper are also summarized further. This bone-grinding robot is still in the initial stage, and there are many problems to be solved from a clinical point of view. Moreover, the technique is promising and can give a good support for surgeons in future clinical work.

Image navigation as a means to expand the boundaries of fluorescence-guided surgery

NASA Astrophysics Data System (ADS)

Brouwer, Oscar R.; Buckle, Tessa; Bunschoten, Anton; Kuil, Joeri; Vahrmeijer, Alexander L.; Wendler, Thomas; Valdés-Olmos, Renato A.; van der Poel, Henk G.; van Leeuwen, Fijs W. B.

2012-05-01

Hybrid tracers that are both radioactive and fluorescent help extend the use of fluorescence-guided surgery to deeper structures. Such hybrid tracers facilitate preoperative surgical planning using (3D) scintigraphic images and enable synchronous intraoperative radio- and fluorescence guidance. Nevertheless, we previously found that improved orientation during laparoscopic surgery remains desirable. Here we illustrate how intraoperative navigation based on optical tracking of a fluorescence endoscope may help further improve the accuracy of hybrid surgical guidance. After feeding SPECT/CT images with an optical fiducial as a reference target to the navigation system, optical tracking could be used to position the tip of the fluorescence endoscope relative to the preoperative 3D imaging data. This hybrid navigation approach allowed us to accurately identify marker seeds in a phantom setup. The multispectral nature of the fluorescence endoscope enabled stepwise visualization of the two clinically approved fluorescent dyes, fluorescein and indocyanine green. In addition, the approach was used to navigate toward the prostate in a patient undergoing robot-assisted prostatectomy. Navigation of the tracked fluorescence endoscope toward the target identified on SPECT/CT resulted in real-time gradual visualization of the fluorescent signal in the prostate, thus providing an intraoperative confirmation of the navigation accuracy.

Insect-Based Vision for Autonomous Vehicles: A Feasibility Study

NASA Technical Reports Server (NTRS)

Srinivasan, Mandyam V.

1999-01-01

The aims of the project were to use a high-speed digital video camera to pursue two questions: i) To explore the influence of temporal imaging constraints on the performance of vision systems for autonomous mobile robots; To study the fine structure of insect flight trajectories with in order to better understand the characteristics of flight control, orientation and navigation.

Insect-Based Vision for Autonomous Vehicles: A Feasibility Study

NASA Technical Reports Server (NTRS)

Srinivasan, Mandyam V.

1999-01-01

The aims of the project were to use a high-speed digital video camera to pursue two questions: (1) To explore the influence of temporal imaging constraints on the performance of vision systems for autonomous mobile robots; (2) To study the fine structure of insect flight trajectories in order to better understand the characteristics of flight control, orientation and navigation.

Control of free-flying space robot manipulator systems

NASA Technical Reports Server (NTRS)

Cannon, Robert H., Jr.

1990-01-01

New control techniques for self contained, autonomous free flying space robots were developed and tested experimentally. Free flying robots are envisioned as a key element of any successful long term presence in space. These robots must be capable of performing the assembly, maintenance, and inspection, and repair tasks that currently require human extravehicular activity (EVA). A set of research projects were developed and carried out using lab models of satellite robots and a flexible manipulator. The second generation space robot models use air cushion vehicle (ACV) technology to simulate in 2-D the drag free, zero g conditions of space. The current work is divided into 5 major projects: Global Navigation and Control of a Free Floating Robot, Cooperative Manipulation from a Free Flying Robot, Multiple Robot Cooperation, Thrusterless Robotic Locomotion, and Dynamic Payload Manipulation. These projects are examined in detail.

Architectural Design for a Mars Communications and Navigation Orbital Infrastructure

NASA Technical Reports Server (NTRS)

Ceasrone R. J.; Hastrup, R. C.; Bell, D. J.; Roncoli, R. B.; Nelson, K.

1999-01-01

The planet Mars has become the focus of an intensive series of missions that span decades of time, a wide array of international agencies and an evolution from robotics to humans. The number of missions to Mars at any one time, and over a period of time, is unprecedented in the annals of space exploration. To meet the operational needs of this exploratory fleet will require the implementation of new architectural concepts for communications and navigation. To this end, NASA's Jet Propulsion Laboratory has begun to define and develop a Mars communications and navigation orbital infrastructure. This architecture will make extensive use of assets at Mars, as well as use of traditional Earth-based assets, such as the Deep Space Network, DSN. Indeed, the total system can be thought of as an extension of DSN nodes and services to the Mars in-situ region. The concept has been likened to the beginnings of an interplanetary Internet that will bring the exploration of Mars right into our living rooms. The paper will begin with a high-level overview of the concept for the Mars communications and navigation infrastructure. Next, the mission requirements will be presented. These will include the relatively near-term needs of robotic landers, rovers, ascent vehicles, balloons, airplanes, and possibly orbiting, arriving and departing spacecraft. Requirements envisioned for the human exploration of Mars will also be described. The important Mars orbit design trades on telecommunications and navigation capabilities will be summarized, and the baseline infrastructure will be described. A roadmap of NASA's plan to evolve this infrastructure over time will be shown. Finally, launch considerations and delivery to Mars will be briefly treated.

A Coordinated Control Architecture for Disaster Response Robots

DTIC Science & Technology

2016-01-01

to use these same algorithms to provide navigation Odometry for the vehicle motions when the robot is driving. Visual Odometry The YouTube link... depressed the accelerator pedal. We relied on the fact that the vehicle quickly comes to rest when the accelerator pedal is not being pressed. The

Observability-Based Guidance and Sensor Placement

NASA Astrophysics Data System (ADS)

Hinson, Brian T.

Control system performance is highly dependent on the quality of sensor information available. In a growing number of applications, however, the control task must be accomplished with limited sensing capabilities. This thesis addresses these types of problems from a control-theoretic point-of-view, leveraging system nonlinearities to improve sensing performance. Using measures of observability as an information quality metric, guidance trajectories and sensor distributions are designed to improve the quality of sensor information. An observability-based sensor placement algorithm is developed to compute optimal sensor configurations for a general nonlinear system. The algorithm utilizes a simulation of the nonlinear system as the source of input data, and convex optimization provides a scalable solution method. The sensor placement algorithm is applied to a study of gyroscopic sensing in insect wings. The sensor placement algorithm reveals information-rich areas on flexible insect wings, and a comparison to biological data suggests that insect wings are capable of acting as gyroscopic sensors. An observability-based guidance framework is developed for robotic navigation with limited inertial sensing. Guidance trajectories and algorithms are developed for range-only and bearing-only navigation that improve navigation accuracy. Simulations and experiments with an underwater vehicle demonstrate that the observability measure allows tuning of the navigation uncertainty.

Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1992-01-01

Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)

Mars Rover Navigation Results Using Sun Sensor Heading Determination

NASA Technical Reports Server (NTRS)

Volpe, Richard

1998-01-01

Upcoming missions to the surface of Mars will use mobile robots to traverse long distances from the landing site. To prepare for these missions, the prototype rover, Rocky 7, has been tested in desert field trials conducted with a team of planetary scientists. While several new capabilities have been demonstrated, foremost among these was sun-sensor based traversal of natural terrain totaling a distance of one kilometer. This paper describes navigation results obtained in the field tests, where cross-track error was only 6% of distance traveled. Comparison with previous results of other planetary rover systems shows this to be a significant improvement.

Semi autonomous mine detection system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Douglas Few; Roelof Versteeg; Herman Herman

2010-04-01

CMMAD is a risk reduction effort for the AMDS program. As part of CMMAD, multiple instances of semi autonomous robotic mine detection systems were created. Each instance consists of a robotic vehicle equipped with sensors required for navigation and marking, a countermine sensors and a number of integrated software packages which provide for real time processing of the countermine sensor data as well as integrated control of the robotic vehicle, the sensor actuator and the sensor. These systems were used to investigate critical interest functions (CIF) related to countermine robotic systems. To address the autonomy CIF, the INL developed RIKmore » was extended to allow for interaction with a mine sensor processing code (MSPC). In limited field testing this system performed well in detecting, marking and avoiding both AT and AP mines. Based on the results of the CMMAD investigation we conclude that autonomous robotic mine detection is feasible. In addition, CMMAD contributed critical technical advances with regard to sensing, data processing and sensor manipulation, which will advance the performance of future fieldable systems. As a result, no substantial technical barriers exist which preclude – from an autonomous robotic perspective – the rapid development and deployment of fieldable systems.« less

Biobotic insect swarm based sensor networks for search and rescue

NASA Astrophysics Data System (ADS)

Bozkurt, Alper; Lobaton, Edgar; Sichitiu, Mihail; Hedrick, Tyson; Latif, Tahmid; Dirafzoon, Alireza; Whitmire, Eric; Verderber, Alexander; Marin, Juan; Xiong, Hong

2014-06-01

The potential benefits of distributed robotics systems in applications requiring situational awareness, such as search-and-rescue in emergency situations, are indisputable. The efficiency of such systems requires robotic agents capable of coping with uncertain and dynamic environmental conditions. For example, after an earthquake, a tremendous effort is spent for days to reach to surviving victims where robotic swarms or other distributed robotic systems might play a great role in achieving this faster. However, current technology falls short of offering centimeter scale mobile agents that can function effectively under such conditions. Insects, the inspiration of many robotic swarms, exhibit an unmatched ability to navigate through such environments while successfully maintaining control and stability. We have benefitted from recent developments in neural engineering and neuromuscular stimulation research to fuse the locomotory advantages of insects with the latest developments in wireless networking technologies to enable biobotic insect agents to function as search-and-rescue agents. Our research efforts towards this goal include development of biobot electronic backpack technologies, establishment of biobot tracking testbeds to evaluate locomotion control efficiency, investigation of biobotic control strategies with Gromphadorhina portentosa cockroaches and Manduca sexta moths, establishment of a localization and communication infrastructure, modeling and controlling collective motion by learning deterministic and stochastic motion models, topological motion modeling based on these models, and the development of a swarm robotic platform to be used as a testbed for our algorithms.

Using arm and hand gestures to command robots during stealth operations

NASA Astrophysics Data System (ADS)

Stoica, Adrian; Assad, Chris; Wolf, Michael; You, Ki Sung; Pavone, Marco; Huntsberger, Terry; Iwashita, Yumi

2012-06-01

Command of support robots by the warfighter requires intuitive interfaces to quickly communicate high degree-offreedom (DOF) information while leaving the hands unencumbered. Stealth operations rule out voice commands and vision-based gesture interpretation techniques, as they often entail silent operations at night or in other low visibility conditions. Targeted at using bio-signal inputs to set navigation and manipulation goals for the robot (say, simply by pointing), we developed a system based on an electromyography (EMG) "BioSleeve", a high density sensor array for robust, practical signal collection from forearm muscles. The EMG sensor array data is fused with inertial measurement unit (IMU) data. This paper describes the BioSleeve system and presents initial results of decoding robot commands from the EMG and IMU data using a BioSleeve prototype with up to sixteen bipolar surface EMG sensors. The BioSleeve is demonstrated on the recognition of static hand positions (e.g. palm facing front, fingers upwards) and on dynamic gestures (e.g. hand wave). In preliminary experiments, over 90% correct recognition was achieved on five static and nine dynamic gestures. We use the BioSleeve to control a team of five LANdroid robots in individual and group/squad behaviors. We define a gesture composition mechanism that allows the specification of complex robot behaviors with only a small vocabulary of gestures/commands, and we illustrate it with a set of complex orders.

Using Arm and Hand Gestures to Command Robots during Stealth Operations

NASA Technical Reports Server (NTRS)

Stoica, Adrian; Assad, Chris; Wolf, Michael; You, Ki Sung; Pavone, Marco; Huntsberger, Terry; Iwashita, Yumi

2012-01-01

Command of support robots by the warfighter requires intuitive interfaces to quickly communicate high degree-of-freedom (DOF) information while leaving the hands unencumbered. Stealth operations rule out voice commands and vision-based gesture interpretation techniques, as they often entail silent operations at night or in other low visibility conditions. Targeted at using bio-signal inputs to set navigation and manipulation goals for the robot (say, simply by pointing), we developed a system based on an electromyography (EMG) "BioSleeve", a high density sensor array for robust, practical signal collection from forearm muscles. The EMG sensor array data is fused with inertial measurement unit (IMU) data. This paper describes the BioSleeve system and presents initial results of decoding robot commands from the EMG and IMU data using a BioSleeve prototype with up to sixteen bipolar surface EMG sensors. The BioSleeve is demonstrated on the recognition of static hand positions (e.g. palm facing front, fingers upwards) and on dynamic gestures (e.g. hand wave). In preliminary experiments, over 90% correct recognition was achieved on five static and nine dynamic gestures. We use the BioSleeve to control a team of five LANdroid robots in individual and group/squad behaviors. We define a gesture composition mechanism that allows the specification of complex robot behaviors with only a small vocabulary of gestures/commands, and we illustrate it with a set of complex orders.

Graph Structure-Based Simultaneous Localization and Mapping Using a Hybrid Method of 2D Laser Scan and Monocular Camera Image in Environments with Laser Scan Ambiguity

PubMed Central

Oh, Taekjun; Lee, Donghwa; Kim, Hyungjin; Myung, Hyun

2015-01-01

Localization is an essential issue for robot navigation, allowing the robot to perform tasks autonomously. However, in environments with laser scan ambiguity, such as long corridors, the conventional SLAM (simultaneous localization and mapping) algorithms exploiting a laser scanner may not estimate the robot pose robustly. To resolve this problem, we propose a novel localization approach based on a hybrid method incorporating a 2D laser scanner and a monocular camera in the framework of a graph structure-based SLAM. 3D coordinates of image feature points are acquired through the hybrid method, with the assumption that the wall is normal to the ground and vertically flat. However, this assumption can be relieved, because the subsequent feature matching process rejects the outliers on an inclined or non-flat wall. Through graph optimization with constraints generated by the hybrid method, the final robot pose is estimated. To verify the effectiveness of the proposed method, real experiments were conducted in an indoor environment with a long corridor. The experimental results were compared with those of the conventional GMappingapproach. The results demonstrate that it is possible to localize the robot in environments with laser scan ambiguity in real time, and the performance of the proposed method is superior to that of the conventional approach. PMID:26151203

Synopsis of Precision Landing and Hazard Avoidance (PL&HA) Capabilities for Space Exploration

NASA Technical Reports Server (NTRS)

Robertson, Edward A.

2017-01-01

Until recently, robotic exploration missions to the Moon, Mars, and other solar system bodies relied upon controlled blind landings. Because terrestrial techniques for terrain relative navigation (TRN) had not yet been evolved to support space exploration, landing dispersions were driven by the capabilities of inertial navigation systems combined with surface relative altimetry and velocimetry. Lacking tight control over the actual landing location, mission success depended on the statistical vetting of candidate landing areas within the predicted landing dispersion ellipse based on orbital reconnaissance data, combined with the ability of the spacecraft to execute a controlled landing in terms of touchdown attitude, attitude rates, and velocity. In addition, the sensors, algorithms, and processing technologies required to perform autonomous hazard detection and avoidance in real time during the landing sequence were not yet available. Over the past decade, NASA has invested substantial resources on the development, integration, and testing of autonomous precision landing and hazard avoidance (PL&HA) capabilities. In addition to substantially improving landing accuracy and safety, these autonomous PL&HA functions also offer access to targets of interest located within more rugged and hazardous terrain. Optical TRN systems are baselined on upcoming robotic landing missions to the Moon and Mars, and NASA JPL is investigating the development of a comprehensive PL&HA system for a Europa lander. These robotic missions will demonstrate and mature PL&HA technologies that are considered essential for future human exploration missions. PL&HA technologies also have applications to rendezvous and docking/berthing with other spacecraft, as well as proximity navigation, contact, and retrieval missions to smaller bodies with microgravity environments, such as asteroids.

Learning for autonomous navigation

NASA Technical Reports Server (NTRS)

Angelova, Anelia; Howard, Andrew; Matthies, Larry; Tang, Benyang; Turmon, Michael; Mjolsness, Eric

2005-01-01

Autonomous off-road navigation of robotic ground vehicles has important applications on Earth and in space exploration. Progress in this domain has been retarded by the limited lookahead range of 3-D sensors and by the difficulty of preprogramming systems to understand the traversability of the wide variety of terrain they can encounter.

Robotic air vehicle. Blending artificial intelligence with conventional software

NASA Technical Reports Server (NTRS)

Mcnulty, Christa; Graham, Joyce; Roewer, Paul

1987-01-01

The Robotic Air Vehicle (RAV) system is described. The program's objectives were to design, implement, and demonstrate cooperating expert systems for piloting robotic air vehicles. The development of this system merges conventional programming used in passive navigation with Artificial Intelligence techniques such as voice recognition, spatial reasoning, and expert systems. The individual components of the RAV system are discussed as well as their interactions with each other and how they operate as a system.

On-Line Point Positioning with Single Frame Camera Data

DTIC Science & Technology

1992-03-15

tion algorithms and methods will be found in robotics and industrial quality control. 1. Project data The project has been defined as "On-line point...development and use of the OLT algorithms and meth- ods for applications in robotics , industrial quality control and autonomous vehicle naviga- tion...Of particular interest in robotics and autonomous vehicle navigation is, for example, the task of determining the position and orientation of a mobile

Computer graphics testbed to simulate and test vision systems for space applications

NASA Technical Reports Server (NTRS)

Cheatham, John B.

1991-01-01

Artificial intelligence concepts are applied to robotics. Artificial neural networks, expert systems and laser imaging techniques for autonomous space robots are being studied. A computer graphics laser range finder simulator developed by Wu has been used by Weiland and Norwood to study use of artificial neural networks for path planning and obstacle avoidance. Interest is expressed in applications of CLIPS, NETS, and Fuzzy Control. These applications are applied to robot navigation.

Odometry and Laser Scanner Fusion Based on a Discrete Extended Kalman Filter for Robotic Platooning Guidance

PubMed Central

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

Odometry and laser scanner fusion based on a discrete extended Kalman Filter for robotic platooning guidance.

PubMed

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.

A Novel Cloud-Based Service Robotics Application to Data Center Environmental Monitoring

PubMed Central

Russo, Ludovico Orlando; Rosa, Stefano; Maggiora, Marcello; Bona, Basilio

2016-01-01

This work presents a robotic application aimed at performing environmental monitoring in data centers. Due to the high energy density managed in data centers, environmental monitoring is crucial for controlling air temperature and humidity throughout the whole environment, in order to improve power efficiency, avoid hardware failures and maximize the life cycle of IT devices. State of the art solutions for data center monitoring are nowadays based on environmental sensor networks, which continuously collect temperature and humidity data. These solutions are still expensive and do not scale well in large environments. This paper presents an alternative to environmental sensor networks that relies on autonomous mobile robots equipped with environmental sensors. The robots are controlled by a centralized cloud robotics platform that enables autonomous navigation and provides a remote client user interface for system management. From the user point of view, our solution simulates an environmental sensor network. The system can easily be reconfigured in order to adapt to management requirements and changes in the layout of the data center. For this reason, it is called the virtual sensor network. This paper discusses the implementation choices with regards to the particular requirements of the application and presents and discusses data collected during a long-term experiment in a real scenario. PMID:27509505

An Improved Otsu Threshold Segmentation Method for Underwater Simultaneous Localization and Mapping-Based Navigation

PubMed Central

Yuan, Xin; Martínez, José-Fernán; Eckert, Martina; López-Santidrián, Lourdes

2016-01-01

The main focus of this paper is on extracting features with SOund Navigation And Ranging (SONAR) sensing for further underwater landmark-based Simultaneous Localization and Mapping (SLAM). According to the characteristics of sonar images, in this paper, an improved Otsu threshold segmentation method (TSM) has been developed for feature detection. In combination with a contour detection algorithm, the foreground objects, although presenting different feature shapes, are separated much faster and more precisely than by other segmentation methods. Tests have been made with side-scan sonar (SSS) and forward-looking sonar (FLS) images in comparison with other four TSMs, namely the traditional Otsu method, the local TSM, the iterative TSM and the maximum entropy TSM. For all the sonar images presented in this work, the computational time of the improved Otsu TSM is much lower than that of the maximum entropy TSM, which achieves the highest segmentation precision among the four above mentioned TSMs. As a result of the segmentations, the centroids of the main extracted regions have been computed to represent point landmarks which can be used for navigation, e.g., with the help of an Augmented Extended Kalman Filter (AEKF)-based SLAM algorithm. The AEKF-SLAM approach is a recursive and iterative estimation-update process, which besides a prediction and an update stage (as in classical Extended Kalman Filter (EKF)), includes an augmentation stage. During navigation, the robot localizes the centroids of different segments of features in sonar images, which are detected by our improved Otsu TSM, as point landmarks. Using them with the AEKF achieves more accurate and robust estimations of the robot pose and the landmark positions, than with those detected by the maximum entropy TSM. Together with the landmarks identified by the proposed segmentation algorithm, the AEKF-SLAM has achieved reliable detection of cycles in the map and consistent map update on loop closure, which is shown in simulated experiments. PMID:27455279

An Improved Otsu Threshold Segmentation Method for Underwater Simultaneous Localization and Mapping-Based Navigation.

PubMed

Yuan, Xin; Martínez, José-Fernán; Eckert, Martina; López-Santidrián, Lourdes

2016-07-22

The main focus of this paper is on extracting features with SOund Navigation And Ranging (SONAR) sensing for further underwater landmark-based Simultaneous Localization and Mapping (SLAM). According to the characteristics of sonar images, in this paper, an improved Otsu threshold segmentation method (TSM) has been developed for feature detection. In combination with a contour detection algorithm, the foreground objects, although presenting different feature shapes, are separated much faster and more precisely than by other segmentation methods. Tests have been made with side-scan sonar (SSS) and forward-looking sonar (FLS) images in comparison with other four TSMs, namely the traditional Otsu method, the local TSM, the iterative TSM and the maximum entropy TSM. For all the sonar images presented in this work, the computational time of the improved Otsu TSM is much lower than that of the maximum entropy TSM, which achieves the highest segmentation precision among the four above mentioned TSMs. As a result of the segmentations, the centroids of the main extracted regions have been computed to represent point landmarks which can be used for navigation, e.g., with the help of an Augmented Extended Kalman Filter (AEKF)-based SLAM algorithm. The AEKF-SLAM approach is a recursive and iterative estimation-update process, which besides a prediction and an update stage (as in classical Extended Kalman Filter (EKF)), includes an augmentation stage. During navigation, the robot localizes the centroids of different segments of features in sonar images, which are detected by our improved Otsu TSM, as point landmarks. Using them with the AEKF achieves more accurate and robust estimations of the robot pose and the landmark positions, than with those detected by the maximum entropy TSM. Together with the landmarks identified by the proposed segmentation algorithm, the AEKF-SLAM has achieved reliable detection of cycles in the map and consistent map update on loop closure, which is shown in simulated experiments.

Scene Segmentation For Autonomous Robotic Navigation Using Sequential Laser Projected Structured Light

NASA Astrophysics Data System (ADS)

Brown, C. David; Ih, Charles S.; Arce, Gonzalo R.; Fertell, David A.

1987-01-01

Vision systems for mobile robots or autonomous vehicles navigating in an unknown terrain environment must provide a rapid and accurate method of segmenting the scene ahead into regions of pathway and background. A major distinguishing feature between the pathway and background is the three dimensional texture of these two regions. Typical methods of textural image segmentation are very computationally intensive, often lack the required robustness, and are incapable of sensing the three dimensional texture of various regions of the scene. A method is presented where scanned laser projected lines of structured light, viewed by a stereoscopically located single video camera, resulted in an image in which the three dimensional characteristics of the scene were represented by the discontinuity of the projected lines. This image was conducive to processing with simple regional operators to classify regions as pathway or background. Design of some operators and application methods, and demonstration on sample images are presented. This method provides rapid and robust scene segmentation capability that has been implemented on a microcomputer in near real time, and should result in higher speed and more reliable robotic or autonomous navigation in unstructured environments.

Key Issues for Navigation and Time Dissemination in NASA's Space Exploration Program

NASA Technical Reports Server (NTRS)

Nelson, R. A.; Brodsky, B.; Oria, A. J.; Connolly, J. W.; Sands, O. S.; Welch, B. W.; Ely T.; Orr, R.; Schuchman, L.

2006-01-01

The renewed emphasis on robotic and human missions within NASA's space exploration program warrants a detailed consideration of how the positions of objects in space will be determined and tracked, whether they be spacecraft, human explorers, robots, surface vehicles, or science instrumentation. The Navigation Team within the NASA Space Communications Architecture Working Group (SCAWG) has addressed several key technical issues in this area and the principle findings are reported here. For navigation in the vicinity of the Moon, a variety of satellite constellations have been investigated that provide global or regional surface position determination and timely services analogous to those offered by GPS at Earth. In the vicinity of Mars, there are options for satellite constellations not available at the Moon due to the gravitational perturbations from Earth, such as two satellites in an aerostationary orbit. Alternate methods of radiometric navigation as considered, including one- and two-way signals, as well as autonomous navigation. The use of a software radio capable of receiving all available signal sources, such as GPS, pseudolites, and communication channels, is discussed. Methods of time transfer and dissemination are also considered in this paper.

Deep space telecommunications, navigation, and information management. Support of the space exploration initiative

NASA Astrophysics Data System (ADS)

Hall, Justin R.; Hastrup, Rolf C.

The United States Space Exploration Initiative (SEI) calls for the charting of a new and evolving manned course to the Moon, Mars, and beyond. This paper discusses key challenges in providing effective deep space telecommunications, navigation, and information management (TNIM) architectures and designs for Mars exploration support. The fundamental objectives are to provide the mission with means to monitor and control mission elements, acquire engineering, science, and navigation data, compute state vectors and navigate, and move these data efficiently and automatically between mission nodes for timely analysis and decision-making. Although these objectives do not depart, fundamentally, from those evolved over the past 30 years in supporting deep space robotic exploration, there are several new issues. This paper focuses on summarizing new requirements, identifying related issues and challenges, responding with concepts and strategies which are enabling, and, finally, describing candidate architectures, and driving technologies. The design challenges include the attainment of: 1) manageable interfaces in a large distributed system, 2) highly unattended operations for in-situ Mars telecommunications and navigation functions, 3) robust connectivity for manned and robotic links, 4) information management for efficient and reliable interchange of data between mission nodes, and 5) an adequate Mars-Earth data rate.

Accurate multi-robot targeting for keyhole neurosurgery based on external sensor monitoring.

PubMed

Comparetti, Mirko Daniele; Vaccarella, Alberto; Dyagilev, Ilya; Shoham, Moshe; Ferrigno, Giancarlo; De Momi, Elena

2012-05-01

Robotics has recently been introduced in surgery to improve intervention accuracy, to reduce invasiveness and to allow new surgical procedures. In this framework, the ROBOCAST system is an optically surveyed multi-robot chain aimed at enhancing the accuracy of surgical probe insertion during keyhole neurosurgery procedures. The system encompasses three robots, connected as a multiple kinematic chain (serial and parallel), totalling 13 degrees of freedom, and it is used to automatically align the probe onto a desired planned trajectory. The probe is then inserted in the brain, towards the planned target, by means of a haptic interface. This paper presents a new iterative targeting approach to be used in surgical robotic navigation, where the multi-robot chain is used to align the surgical probe to the planned pose, and an external sensor is used to decrease the alignment errors. The iterative targeting was tested in an operating room environment using a skull phantom, and the targets were selected on magnetic resonance images. The proposed targeting procedure allows about 0.3 mm to be obtained as the residual median Euclidean distance between the planned and the desired targets, thus satisfying the surgical accuracy requirements (1 mm), due to the resolution of the diffused medical images. The performances proved to be independent of the robot optical sensor calibration accuracy.

Improving Emergency Response and Human-Robotic Performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

David I. Gertman; David J. Bruemmer; R. Scott Hartley

2007-08-01

Preparedness for chemical, biological, and radiological/nuclear incidents at nuclear power plants (NPPs) includes the deployment of well trained emergency response teams. While teams are expected to do well, data from other domains suggests that the timeliness and accuracy associated with incident response can be improved through collaborative human-robotic interaction. Many incident response scenarios call for multiple, complex procedure-based activities performed by personnel wearing cumbersome personal protective equipment (PPE) and operating under high levels of stress and workload. While robotic assistance is postulated to reduce workload and exposure, limitations associated with communications and the robot’s ability to act independently have servedmore » to limit reliability and reduce our potential to exploit human –robotic interaction and efficacy of response. Recent work at the Idaho National Laboratory (INL) on expanding robot capability has the potential to improve human-system response during disaster management and recovery. Specifically, increasing the range of higher level robot behaviors such as autonomous navigation and mapping, evolving new abstractions for sensor and control data, and developing metaphors for operator control have the potential to improve state-of-the-art in incident response. This paper discusses these issues and reports on experiments underway intelligence residing on the robot to enhance emergency response.« less

Application requirements for Robotic Nursing Assistants in hospital environments

NASA Astrophysics Data System (ADS)

Cremer, Sven; Doelling, Kris; Lundberg, Cody L.; McNair, Mike; Shin, Jeongsik; Popa, Dan

2016-05-01

In this paper we report on analysis toward identifying design requirements for an Adaptive Robotic Nursing Assistant (ARNA). Specifically, the paper focuses on application requirements for ARNA, envisioned as a mobile assistive robot that can navigate hospital environments to perform chores in roles such as patient sitter and patient walker. The role of a sitter is primarily related to patient observation from a distance, and fetching objects at the patient's request, while a walker provides physical assistance for ambulation and rehabilitation. The robot will be expected to not only understand nurse and patient intent but also close the decision loop by automating several routine tasks. As a result, the robot will be equipped with sensors such as distributed pressure sensitive skins, 3D range sensors, and so on. Modular sensor and actuator hardware configured in the form of several multi-degree-of-freedom manipulators, and a mobile base are expected to be deployed in reconfigurable platforms for physical assistance tasks. Furthermore, adaptive human-machine interfaces are expected to play a key role, as they directly impact the ability of robots to assist nurses in a dynamic and unstructured environment. This paper discusses required tasks for the ARNA robot, as well as sensors and software infrastructure to carry out those tasks in the aspects of technical resource availability, gaps, and needed experimental studies.

A lightweight, inexpensive robotic system for insect vision.

PubMed

Sabo, Chelsea; Chisholm, Robert; Petterson, Adam; Cope, Alex

2017-09-01

Designing hardware for miniaturized robotics which mimics the capabilities of flying insects is of interest, because they share similar constraints (i.e. small size, low weight, and low energy consumption). Research in this area aims to enable robots with similarly efficient flight and cognitive abilities. Visual processing is important to flying insects' impressive flight capabilities, but currently, embodiment of insect-like visual systems is limited by the hardware systems available. Suitable hardware is either prohibitively expensive, difficult to reproduce, cannot accurately simulate insect vision characteristics, and/or is too heavy for small robotic platforms. These limitations hamper the development of platforms for embodiment which in turn hampers the progress on understanding of how biological systems fundamentally work. To address this gap, this paper proposes an inexpensive, lightweight robotic system for modelling insect vision. The system is mounted and tested on a robotic platform for mobile applications, and then the camera and insect vision models are evaluated. We analyse the potential of the system for use in embodiment of higher-level visual processes (i.e. motion detection) and also for development of navigation based on vision for robotics in general. Optic flow from sample camera data is calculated and compared to a perfect, simulated bee world showing an excellent resemblance. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

HERMIES-3: A step toward autonomous mobility, manipulation, and perception

NASA Technical Reports Server (NTRS)

Weisbin, C. R.; Burks, B. L.; Einstein, J. R.; Feezell, R. R.; Manges, W. W.; Thompson, D. H.

1989-01-01

HERMIES-III is an autonomous robot comprised of a seven degree-of-freedom (DOF) manipulator designed for human scale tasks, a laser range finder, a sonar array, an omni-directional wheel-driven chassis, multiple cameras, and a dual computer system containing a 16-node hypercube expandable to 128 nodes. The current experimental program involves performance of human-scale tasks (e.g., valve manipulation, use of tools), integration of a dexterous manipulator and platform motion in geometrically complex environments, and effective use of multiple cooperating robots (HERMIES-IIB and HERMIES-III). The environment in which the robots operate has been designed to include multiple valves, pipes, meters, obstacles on the floor, valves occluded from view, and multiple paths of differing navigation complexity. The ongoing research program supports the development of autonomous capability for HERMIES-IIB and III to perform complex navigation and manipulation under time constraints, while dealing with imprecise sensory information.

A novel semi-automatic snake robot for natural orifice transluminal endoscopic surgery: preclinical tests in animal and human cadaver models (with video).

PubMed

Son, Jaebum; Cho, Chang Nho; Kim, Kwang Gi; Chang, Tae Young; Jung, Hyunchul; Kim, Sung Chun; Kim, Min-Tae; Yang, Nari; Kim, Tae-Yun; Sohn, Dae Kyung

2015-06-01

Natural orifice transluminal endoscopic surgery (NOTES) is an emerging surgical technique. We aimed to design, create, and evaluate a new semi-automatic snake robot for NOTES. The snake robot employs the characteristics of both a manual endoscope and a multi-segment snake robot. This robot is inserted and retracted manually, like a classical endoscope, while its shape is controlled using embedded robot technology. The feasibility of a prototype robot for NOTES was evaluated in animals and human cadavers. The transverse stiffness and maneuverability of the snake robot appeared satisfactory. It could be advanced through the anus as far as the peritoneal cavity without any injury to adjacent organs. Preclinical tests showed that the device could navigate the peritoneal cavity. The snake robot has advantages of high transverse force and intuitive control. This new robot may be clinically superior to conventional tools for transanal NOTES.

Robotics in Arthroplasty: A Comprehensive Review.

PubMed

Jacofsky, David J; Allen, Mark

2016-10-01

Robotic-assisted orthopedic surgery has been available clinically in some form for over 2 decades, claiming to improve total joint arthroplasty by enhancing the surgeon's ability to reproduce alignment and therefore better restore normal kinematics. Various current systems include a robotic arm, robotic-guided cutting jigs, and robotic milling systems with a diversity of different navigation strategies using active, semiactive, or passive control systems. Semiactive systems have become dominant, providing a haptic window through which the surgeon is able to consistently prepare an arthroplasty based on preoperative planning. A review of previous designs and clinical studies demonstrate that these robotic systems decrease variability and increase precision, primarily focusing on component positioning and alignment. Some early clinical results indicate decreased revision rates and improved patient satisfaction with robotic-assisted arthroplasty. The future design objectives include precise planning and even further improved consistent intraoperative execution. Despite this cautious optimism, many still wonder whether robotics will ultimately increase cost and operative time without objectively improving outcomes. Over the long term, every industry that has seen robotic technology be introduced, ultimately has shown an increase in production capacity, improved accuracy and precision, and lower cost. A new generation of robotic systems is now being introduced into the arthroplasty arena, and early results with unicompartmental knee arthroplasty and total hip arthroplasty have demonstrated improved accuracy of placement, improved satisfaction, and reduced complications. Further studies are needed to confirm the cost effectiveness of these technologies. Copyright © 2016 Elsevier Inc. All rights reserved.

HRI usability evaluation of interaction modes for a teleoperated agricultural robotic sprayer.

PubMed

Adamides, George; Katsanos, Christos; Parmet, Yisrael; Christou, Georgios; Xenos, Michalis; Hadzilacos, Thanasis; Edan, Yael

2017-07-01

Teleoperation of an agricultural robotic system requires effective and efficient human-robot interaction. This paper investigates the usability of different interaction modes for agricultural robot teleoperation. Specifically, we examined the overall influence of two types of output devices (PC screen, head mounted display), two types of peripheral vision support mechanisms (single view, multiple views), and two types of control input devices (PC keyboard, PS3 gamepad) on observed and perceived usability of a teleoperated agricultural sprayer. A modular user interface for teleoperating an agricultural robot sprayer was constructed and field-tested. Evaluation included eight interaction modes: the different combinations of the 3 factors. Thirty representative participants used each interaction mode to navigate the robot along a vineyard and spray grape clusters based on a 2 × 2 × 2 repeated measures experimental design. Objective metrics of the effectiveness and efficiency of the human-robot collaboration were collected. Participants also completed questionnaires related to their user experience with the system in each interaction mode. Results show that the most important factor for human-robot interface usability is the number and placement of views. The type of robot control input device was also a significant factor in certain dependents, whereas the effect of the screen output type was only significant on the participants' perceived workload index. Specific recommendations for mobile field robot teleoperation to improve HRI awareness for the agricultural spraying task are presented. Copyright © 2017 Elsevier Ltd. All rights reserved.

Guidance and control 1991; Proceedings of the Annual Rocky Mountain Guidance and Control Conference, Keystone, CO, Feb. 2-6, 1991

NASA Astrophysics Data System (ADS)

Culp, Robert D.; McQuerry, James P.

1991-07-01

The present conference on guidance and control encompasses advances in guidance, navigation, and control, storyboard displays, approaches to space-borne pointing control, international space programs, recent experiences with systems, and issues regarding navigation in the low-earth-orbit space environment. Specific issues addressed include a scalable architecture for an operational spaceborne autonavigation system, the mitigation of multipath error in GPS-based attitude determination, microgravity flight testing of a laboratory robot, and the application of neural networks. Other issues addressed include image navigation with second-generation Meteosat, Magellan star-scanner experiences, high-precision control systems for telescopes and interferometers, gravitational effects on low-earth orbiters, experimental verification of nanometer-level optical pathlengths, and a flight telerobotic servicer prototype simulator. (For individual items see A93-15577 to A93-15613)

Local adjacency metric dimension of sun graph and stacked book graph

NASA Astrophysics Data System (ADS)

Yulisda Badri, Alifiah; Darmaji

2018-03-01

A graph is a mathematical system consisting of a non-empty set of nodes and a set of empty sides. One of the topics to be studied in graph theory is the metric dimension. Application in the metric dimension is the navigation robot system on a path. Robot moves from one vertex to another vertex in the field by minimizing the errors that occur in translating the instructions (code) obtained from the vertices of that location. To move the robot must give different instructions (code). In order for the robot to move efficiently, the robot must be fast to translate the code of the nodes of the location it passes. so that the location vertex has a minimum distance. However, if the robot must move with the vertex location on a very large field, so the robot can not detect because the distance is too far.[6] In this case, the robot can determine its position by utilizing location vertices based on adjacency. The problem is to find the minimum cardinality of the required location vertex, and where to put, so that the robot can determine its location. The solution to this problem is the dimension of adjacency metric and adjacency metric bases. Rodrguez-Velzquez and Fernau combine the adjacency metric dimensions with local metric dimensions, thus becoming the local adjacency metric dimension. In the local adjacency metric dimension each vertex in the graph may have the same adjacency representation as the terms of the vertices. To obtain the local metric dimension of values in the graph of the Sun and the stacked book graph is used the construction method by considering the representation of each adjacent vertex of the graph.

Developing Autonomous Vehicles That Learn to Navigate by Mimicking Human Behavior

DTIC Science & Technology

2006-09-28

navigate in an unstructured environment to a specific target or location. 15. SUBJECT TERMS autonomous vehicles , fuzzy logic, learning behavior...ANSI-Std Z39-18 Developing Autonomous Vehicles That Learn to Navigate by Mimicking Human Behavior FINAL REPORT 9/28/2006 Dean B. Edwards Department...the future, as greater numbers of autonomous vehicles are employed, it is hoped that lower LONG-TERM GOALS Use LAGR (Learning Applied to Ground Robots

Machine vision and appearance based learning

NASA Astrophysics Data System (ADS)

Bernstein, Alexander

2017-03-01

Smart algorithms are used in Machine vision to organize or extract high-level information from the available data. The resulted high-level understanding the content of images received from certain visual sensing system and belonged to an appearance space can be only a key first step in solving various specific tasks such as mobile robot navigation in uncertain environments, road detection in autonomous driving systems, etc. Appearance-based learning has become very popular in the field of machine vision. In general, the appearance of a scene is a function of the scene content, the lighting conditions, and the camera position. Mobile robots localization problem in machine learning framework via appearance space analysis is considered. This problem is reduced to certain regression on an appearance manifold problem, and newly regression on manifolds methods are used for its solution.

Collision detection in complex dynamic scenes using an LGMD-based visual neural network with feature enhancement.

PubMed

Yue, Shigang; Rind, F Claire

2006-05-01

The lobula giant movement detector (LGMD) is an identified neuron in the locust brain that responds most strongly to the images of an approaching object such as a predator. Its computational model can cope with unpredictable environments without using specific object recognition algorithms. In this paper, an LGMD-based neural network is proposed with a new feature enhancement mechanism to enhance the expanded edges of colliding objects via grouped excitation for collision detection with complex backgrounds. The isolated excitation caused by background detail will be filtered out by the new mechanism. Offline tests demonstrated the advantages of the presented LGMD-based neural network in complex backgrounds. Real time robotics experiments using the LGMD-based neural network as the only sensory system showed that the system worked reliably in a wide range of conditions; in particular, the robot was able to navigate in arenas with structured surrounds and complex backgrounds.

Cascaded Kalman and particle filters for photogrammetry based gyroscope drift and robot attitude estimation.

PubMed

Sadaghzadeh N, Nargess; Poshtan, Javad; Wagner, Achim; Nordheimer, Eugen; Badreddin, Essameddin

2014-03-01

Based on a cascaded Kalman-Particle Filtering, gyroscope drift and robot attitude estimation method is proposed in this paper. Due to noisy and erroneous measurements of MEMS gyroscope, it is combined with Photogrammetry based vision navigation scenario. Quaternions kinematics and robot angular velocity dynamics with augmented drift dynamics of gyroscope are employed as system state space model. Nonlinear attitude kinematics, drift and robot angular movement dynamics each in 3 dimensions result in a nonlinear high dimensional system. To reduce the complexity, we propose a decomposition of system to cascaded subsystems and then design separate cascaded observers. This design leads to an easier tuning and more precise debugging from the perspective of programming and such a setting is well suited for a cooperative modular system with noticeably reduced computation time. Kalman Filtering (KF) is employed for the linear and Gaussian subsystem consisting of angular velocity and drift dynamics together with gyroscope measurement. The estimated angular velocity is utilized as input of the second Particle Filtering (PF) based observer in two scenarios of stochastic and deterministic inputs. Simulation results are provided to show the efficiency of the proposed method. Moreover, the experimental results based on data from a 3D MEMS IMU and a 3D camera system are used to demonstrate the efficiency of the method. © 2013 ISA Published by ISA All rights reserved.

Assisted navigation based on shared-control, using discrete and sparse human-machine interfaces.

PubMed

Lopes, Ana C; Nunes, Urbano; Vaz, Luis; Vaz, Luís

2010-01-01

This paper presents a shared-control approach for Assistive Mobile Robots (AMR), which depends on the user's ability to navigate a semi-autonomous powered wheelchair, using a sparse and discrete human-machine interface (HMI). This system is primarily intended to help users with severe motor disabilities that prevent them to use standard human-machine interfaces. Scanning interfaces and Brain Computer Interfaces (BCI), characterized to provide a small set of commands issued sparsely, are possible HMIs. This shared-control approach is intended to be applied in an Assisted Navigation Training Framework (ANTF) that is used to train users' ability in steering a powered wheelchair in an appropriate manner, given the restrictions imposed by their limited motor capabilities. A shared-controller based on user characterization, is proposed. This controller is able to share the information provided by the local motion planning level with the commands issued sparsely by the user. Simulation results of the proposed shared-control method, are presented.

Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor.

PubMed

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

PubMed Central

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

Navigation of military and space unmanned ground vehicles in unstructured terrains

NASA Technical Reports Server (NTRS)

Lescoe, Paul; Lavery, David; Bedard, Roger

1991-01-01

Development of unmanned vehicles for local navigation in terrains unstructured by humans is reviewed. Modes of navigation include teleoperation or remote control, computer assisted remote driving (CARD), and semiautonomous navigation (SAN). A first implementation of a CARD system was successfully tested using the Robotic Technology Test Vehicle developed by Jet Propulsion Laboratory. Stereo pictures were transmitted to a remotely located human operator, who performed the sensing, perception, and planning functions of navigation. A computer provided range and angle measurements and the path plan was transmitted to the vehicle which autonomously executed the path. This implementation is to be enhanced by providing passive stereo vision and a reflex control system for autonomously stopping the vehicle if blocked by an obstacle. SAN achievements include implementation of a navigation testbed on a six wheel, three-body articulated rover vehicle, development of SAN algorithms and code, integration of SAN software onto the vehicle, and a successful feasibility demonstration that represents a step forward towards the technology required for long-range exploration of the lunar or Martian surface. The vehicle includes a passive stereo vision system with real-time area-based stereo image correlation, a terrain matcher, a path planner, and a path execution planner.

Modeling and experimental characterization of propulsion of a spiral-type microrobot for medical use in gastrointestinal tract.

PubMed

Zhou, Hao; Alici, Gursel; Than, Trung Duc; Li, Weihua

2013-06-01

In this paper, a spiral-type medical robot based on an endoscopic capsule was propelled in a fluidic and tubular environment using electromagnetic actuation. Both modeling and experimental methods have been employed to characterize the propulsion of the robotic capsule. The experiments were performed not only in a simulated environment (vinyl tube filled with silicone oil) but also in a real small intestine. The effects of the spiral parameters including lead, spiral height, the number of spirals, and cross section of the spirals on the propulsion efficiency of the robot are investigated. Based on the transmission efficiency from rotation to translation as well as the balancing of the microrobot in operation, it is demonstrated that the robot with two spirals could provide the best propulsion performance when its lead is slightly smaller than the perimeter of the capsule. As for the spiral height, it is better to use a larger one as long as the intestine's size allows. Based on the simulation and experimental results presented, this study quantifies the influence of the spiral structure on the capsule's propulsion. It provides a helpful reference for the design and optimization of the traction topology of the microrobot navigating inside the mucus-filled small intestine.

Control of autonomous robot using neural networks

NASA Astrophysics Data System (ADS)

Barton, Adam; Volna, Eva

2017-07-01

The aim of the article is to design a method of control of an autonomous robot using artificial neural networks. The introductory part describes control issues from the perspective of autonomous robot navigation and the current mobile robots controlled by neural networks. The core of the article is the design of the controlling neural network, and generation and filtration of the training set using ART1 (Adaptive Resonance Theory). The outcome of the practical part is an assembled Lego Mindstorms EV3 robot solving the problem of avoiding obstacles in space. To verify models of an autonomous robot behavior, a set of experiments was created as well as evaluation criteria. The speed of each motor was adjusted by the controlling neural network with respect to the situation in which the robot was found.

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-12

Sample Return Robot Challenge staff members confer before the team Survey robots makes it's attempt at the level two challenge during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Thursday, June 12, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-14

A robot from the University of Waterloo Robotics Team is seen during the rerun of the level one challenge during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Saturday, June 14, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

Experimental Semiautonomous Vehicle

NASA Technical Reports Server (NTRS)

Wilcox, Brian H.; Mishkin, Andrew H.; Litwin, Todd E.; Matthies, Larry H.; Cooper, Brian K.; Nguyen, Tam T.; Gat, Erann; Gennery, Donald B.; Firby, Robert J.; Miller, David P.;

A cognitive robotic system based on the Soar cognitive architecture for mobile robot navigation, search, and mapping missions

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.

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-11

Team KuuKulgur watches as their robots attempt the level one competition during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Wednesday, June 11, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-11

The Retrievers team robot is seen as it attempts the level one challenge the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Wednesday, June 11, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

Towards a new modality-independent interface for a robotic wheelchair.

PubMed

Bastos-Filho, Teodiano Freire; Cheein, Fernando Auat; Müller, Sandra Mara Torres; Celeste, Wanderley Cardoso; de la Cruz, Celso; Cavalieri, Daniel Cruz; Sarcinelli-Filho, Mário; Amaral, Paulo Faria Santos; Perez, Elisa; Soria, Carlos Miguel; Carelli, Ricardo

2014-05-01

This work presents the development of a robotic wheelchair that can be commanded by users in a supervised way or by a fully automatic unsupervised navigation system. It provides flexibility to choose different modalities to command the wheelchair, in addition to be suitable for people with different levels of disabilities. Users can command the wheelchair based on their eye blinks, eye movements, head movements, by sip-and-puff and through brain signals. The wheelchair can also operate like an auto-guided vehicle, following metallic tapes, or in an autonomous way. The system is provided with an easy to use and flexible graphical user interface onboard a personal digital assistant, which is used to allow users to choose commands to be sent to the robotic wheelchair. Several experiments were carried out with people with disabilities, and the results validate the developed system as an assistive tool for people with distinct levels of disability.

Environmental Recognition and Guidance Control for Autonomous Vehicles using Dual Vision Sensor and Applications

NASA Astrophysics Data System (ADS)

Moriwaki, Katsumi; Koike, Issei; Sano, Tsuyoshi; Fukunaga, Tetsuya; Tanaka, Katsuyuki

We propose a new method of environmental recognition around an autonomous vehicle using dual vision sensor and navigation control based on binocular images. We consider to develop a guide robot that can play the role of a guide dog as the aid to people such as the visually impaired or the aged, as an application of above-mentioned techniques. This paper presents a recognition algorithm, which finds out the line of a series of Braille blocks and the boundary line between a sidewalk and a roadway where a difference in level exists by binocular images obtained from a pair of parallelarrayed CCD cameras. This paper also presents a tracking algorithm, with which the guide robot traces along a series of Braille blocks and avoids obstacles and unsafe areas which exist in the way of a person with the guide robot.

Learning for Autonomous Navigation

NASA Technical Reports Server (NTRS)

Angelova, Anelia; Howard, Andrew; Matthies, Larry; Tang, Benyang; Turmon, Michael; Mjolsness, Eric

2005-01-01

Robotic ground vehicles for outdoor applications have achieved some remarkable successes, notably in autonomous highway following (Dickmanns, 1987), planetary exploration (1), and off-road navigation on Earth (1). Nevertheless, major challenges remain to enable reliable, high-speed, autonomous navigation in a wide variety of complex, off-road terrain. 3-D perception of terrain geometry with imaging range sensors is the mainstay of off-road driving systems. However, the stopping distance at high speed exceeds the effective lookahead distance of existing range sensors. Prospects for extending the range of 3-D sensors is strongly limited by sensor physics, eye safety of lasers, and related issues. Range sensor limitations also allow vehicles to enter large cul-de-sacs even at low speed, leading to long detours. Moreover, sensing only terrain geometry fails to reveal mechanical properties of terrain that are critical to assessing its traversability, such as potential for slippage, sinkage, and the degree of compliance of potential obstacles. Rovers in the Mars Exploration Rover (MER) mission have got stuck in sand dunes and experienced significant downhill slippage in the vicinity of large rock hazards. Earth-based off-road robots today have very limited ability to discriminate traversable vegetation from non-traversable vegetation or rough ground. It is impossible today to preprogram a system with knowledge of these properties for all types of terrain and weather conditions that might be encountered.

Afocal optical flow sensor for reducing vertical height sensitivity in indoor robot localization and navigation.

PubMed

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.

Deictic primitives for general purpose navigation

NASA Technical Reports Server (NTRS)

Crismann, Jill D.

1994-01-01

A visually-based deictic primative used as an elementary command set for general purpose navigation was investigated. It was shown that a simple 'follow your eyes' scenario is sufficient for tracking a moving target. Limitations of velocity, acceleration, and modeling of the response of the mechanical systems were enforced. Realistic paths of the robots were produced during the simulation. Scientists could remotely command a planetary rover to go to a particular rock formation that may be interesting. Similarly an expert at plant maintenance could obtain diagnostic information remotely by using deictic primitives on a mobile are used in the deictic primitives, we could imagine that the exact same control software could be used for all of these applications.

Dual-body magnetic helical robot for drilling and cargo delivery in human blood vessels

NASA Astrophysics Data System (ADS)

Lee, Wonseo; Jeon, Seungmun; Nam, Jaekwang; Jang, Gunhee

2015-05-01

We propose a novel dual-body magnetic helical robot (DMHR) manipulated by a magnetic navigation system. The proposed DMHR can generate helical motions to navigate in human blood vessels and to drill blood clots by an external rotating magnetic field. It can also generate release motions which are relative rotational motions between dual-bodies to release the carrying cargos to a target region by controlling the magnitude of an external magnetic field. Constraint equations were derived to selectively manipulate helical and release motions by controlling external magnetic fields. The DMHR was prototyped and various experiments were conducted to demonstrate its motions and verify its manipulation methods.

Integrated network architecture for sustained human and robotic exploration

NASA Technical Reports Server (NTRS)

Noreen, Gary K.; Cesarone, Robert; Deutsch, Leslie; Edwards, Charlie; Soloff, Jason; Ely, Todd; Cook, Brian; Morabito, David; Hemmati, Hamid; Piazzolla, Sabino;

Real-Time Motion Planning and Safe Navigation in Dynamic Multi-Robot Environments

DTIC Science & Technology

2006-12-15

referee against a robot for pushing or hitting an opponent excessively, as well as for a non- goalie robot entering the team’s own defense area. The DSS... pulling ” a search graph by choosing random samples and then trying to connect a path to those points, some planners “push” samples by first choosing...implement the various roles (attacker, goalie , defender), which in turn build on sub-tactics known as skills [16]. One primitive skill used by almost all

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-11

during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Wednesday, June 11, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-12

during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Thursday, June 12, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

High level functions for the intuitive use of an assistive robot.

PubMed

Lebec, Olivier; Ben Ghezala, Mohamed Walid; Leynart, Violaine; Laffont, Isabelle; Fattal, Charles; Devilliers, Laurence; Chastagnol, Clement; Martin, Jean-Claude; Mezouar, Youcef; Korrapatti, Hermanth; Dupourqué, Vincent; Leroux, Christophe

2013-06-01

This document presents the research project ARMEN (Assistive Robotics to Maintain Elderly People in a Natural environment), aimed at the development of a user friendly robot with advanced functions for assistance to elderly or disabled persons at home. Focus is given to the robot SAM (Smart Autonomous Majordomo) and its new features of navigation, manipulation, object recognition, and knowledge representation developed for the intuitive supervision of the robot. The results of the technical evaluations show the value and potential of these functions for practical applications. The paper also documents the details of the clinical evaluations carried out with elderly and disabled persons in a therapeutic setting to validate the project.

A subsumptive, hierarchical, and distributed vision-based architecture for smart robotics.

PubMed

DeSouza, Guilherme N; Kak, Avinash C

2004-10-01

We present a distributed vision-based architecture for smart robotics that is composed of multiple control loops, each with a specialized level of competence. Our architecture is subsumptive and hierarchical, in the sense that each control loop can add to the competence level of the loops below, and in the sense that the loops can present a coarse-to-fine gradation with respect to vision sensing. At the coarsest level, the processing of sensory information enables a robot to become aware of the approximate location of an object in its field of view. On the other hand, at the finest end, the processing of stereo information enables a robot to determine more precisely the position and orientation of an object in the coordinate frame of the robot. The processing in each module of the control loops is completely independent and it can be performed at its own rate. A control Arbitrator ranks the results of each loop according to certain confidence indices, which are derived solely from the sensory information. This architecture has clear advantages regarding overall performance of the system, which is not affected by the "slowest link," and regarding fault tolerance, since faults in one module does not affect the other modules. At this time we are able to demonstrate the utility of the architecture for stereoscopic visual servoing. The architecture has also been applied to mobile robot navigation and can easily be extended to tasks such as "assembly-on-the-fly."

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.

A simple map-based localization strategy using range measurements

NASA Astrophysics Data System (ADS)

Moore, Kevin L.; Kutiyanawala, Aliasgar; Chandrasekharan, Madhumita

2005-05-01

In this paper we present a map-based approach to localization. We consider indoor navigation in known environments based on the idea of a "vector cloud" by observing that any point in a building has an associated vector defining its distance to the key structural components (e.g., walls, ceilings, etc.) of the building in any direction. Given a building blueprint we can derive the "ideal" vector cloud at any point in space. Then, given measurements from sensors on the robot we can compare the measured vector cloud to the possible vector clouds cataloged from the blueprint, thus determining location. We present algorithms for implementing this approach to localization, using the Hamming norm, the 1-norm, and the 2-norm. The effectiveness of the approach is verified by experiments on a 2-D testbed using a mobile robot with a 360° laser range-finder and through simulation analysis of robustness.

Towards Camera-LIDAR Fusion-Based Terrain Modelling for Planetary Surfaces: Review and Analysis

PubMed Central

Shaukat, Affan; Blacker, Peter C.; Spiteri, Conrad; Gao, Yang

2016-01-01

In recent decades, terrain modelling and reconstruction techniques have increased research interest in precise short and long distance autonomous navigation, localisation and mapping within field robotics. One of the most challenging applications is in relation to autonomous planetary exploration using mobile robots. Rovers deployed to explore extraterrestrial surfaces are required to perceive and model the environment with little or no intervention from the ground station. Up to date, stereopsis represents the state-of-the art method and can achieve short-distance planetary surface modelling. However, future space missions will require scene reconstruction at greater distance, fidelity and feature complexity, potentially using other sensors like Light Detection And Ranging (LIDAR). LIDAR has been extensively exploited for target detection, identification, and depth estimation in terrestrial robotics, but is still under development to become a viable technology for space robotics. This paper will first review current methods for scene reconstruction and terrain modelling using cameras in planetary robotics and LIDARs in terrestrial robotics; then we will propose camera-LIDAR fusion as a feasible technique to overcome the limitations of either of these individual sensors for planetary exploration. A comprehensive analysis will be presented to demonstrate the advantages of camera-LIDAR fusion in terms of range, fidelity, accuracy and computation. PMID:27879625

Three-dimensional sensor system using multistripe laser and stereo camera for environment recognition of mobile robots

NASA Astrophysics Data System (ADS)

Kim, Min Young; Cho, Hyung Suck; Kim, Jae H.

2002-10-01

In recent years, intelligent autonomous mobile robots have drawn tremendous interests as service robots for serving human or industrial robots for replacing human. To carry out the task, robots must be able to sense and recognize 3D space that they live or work. In this paper, we deal with the topic related to 3D sensing system for the environment recognition of mobile robots. For this, the structured lighting is basically utilized for a 3D visual sensor system because of the robustness on the nature of the navigation environment and the easy extraction of feature information of interest. The proposed sensing system is classified into a trinocular vision system, which is composed of the flexible multi-stripe laser projector, and two cameras. The principle of extracting the 3D information is based on the optical triangulation method. With modeling the projector as another camera and using the epipolar constraints which the whole cameras makes, the point-to-point correspondence between the line feature points in each image is established. In this work, the principle of this sensor is described in detail, and a series of experimental tests is performed to show the simplicity and efficiency and accuracy of this sensor system for 3D the environment sensing and recognition.

Curvature-Based Environment Description for Robot Navigation Using Laser Range Sensors

PubMed Central

Vázquez-Martín, Ricardo; Núñez, Pedro; Bandera, Antonio; Sandoval, Francisco

2009-01-01

This work proposes a new feature detection and description approach for mobile robot navigation using 2D laser range sensors. The whole process consists of two main modules: a sensor data segmentation module and a feature detection and characterization module. The segmentation module is divided in two consecutive stages: First, the segmentation stage divides the laser scan into clusters of consecutive range readings using a distance-based criterion. Then, the second stage estimates the curvature function associated to each cluster and uses it to split it into a set of straight-line and curve segments. The curvature is calculated using a triangle-area representation where, contrary to previous approaches, the triangle side lengths at each range reading are adapted to the local variations of the laser scan, removing noise without missing relevant points. This representation remains unchanged in translation or rotation, and it is also robust against noise. Thus, it is able to provide the same segmentation results although the scene will be perceived from different viewpoints. Therefore, segmentation results are used to characterize the environment using line and curve segments, real and virtual corners and edges. Real scan data collected from different environments by using different platforms are used in the experiments in order to evaluate the proposed environment description algorithm. PMID:22461732

LIDAR-Aided Inertial Navigation with Extended Kalman Filtering for Pinpoint Landing

NASA Technical Reports Server (NTRS)

Busnardo, David M.; Aitken, Matthew L.; Tolson, Robert H.; Pierrottet, Diego; Amzajerdian, Farzin

2011-01-01

In support of NASA s Autonomous Landing and Hazard Avoidance Technology (ALHAT) project, an extended Kalman filter routine has been developed for estimating the position, velocity, and attitude of a spacecraft during the landing phase of a planetary mission. The proposed filter combines measurements of acceleration and angular velocity from an inertial measurement unit (IMU) with range and Doppler velocity observations from an onboard light detection and ranging (LIDAR) system. These high-precision LIDAR measurements of distance to the ground and approach velocity will enable both robotic and manned vehicles to land safely and precisely at scientifically interesting sites. The filter has been extensively tested using a lunar landing simulation and shown to improve navigation over flat surfaces or rough terrain. Experimental results from a helicopter flight test performed at NASA Dryden in August 2008 demonstrate that LIDAR can be employed to significantly improve navigation based exclusively on IMU integration.

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-11

The University of Waterloo Robotics Team, from Canada, prepares to place their robot on the start platform during the level one challenge at the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Wednesday, June 11, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-10

The University of Waterloo Robotics Team, from Ontario, Canada, prepares their robot for the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Tuesday, June 10, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. The team from the University of Waterloo is one of eighteen teams competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

Human-Robot Interaction Directed Research Project

NASA Technical Reports Server (NTRS)

Sandor, Aniko; Cross, Ernest V., II; Chang, Mai Lee

2014-01-01

Human-robot interaction (HRI) is a discipline investigating the factors affecting the interactions between humans and robots. It is important to evaluate how the design of interfaces and command modalities affect the human's ability to perform tasks accurately, efficiently, and effectively when working with a robot. By understanding the effects of interface design on human performance, workload, and situation awareness, interfaces can be developed to appropriately support the human in performing tasks with minimal errors and with appropriate interaction time and effort. Thus, the results of research on human-robot interfaces have direct implications for the design of robotic systems. This DRP concentrates on three areas associated with interfaces and command modalities in HRI which are applicable to NASA robot systems: 1) Video Overlays, 2) Camera Views, and 3) Command Modalities. The first study focused on video overlays that investigated how Augmented Reality (AR) symbology can be added to the human-robot interface to improve teleoperation performance. Three types of AR symbology were explored in this study, command guidance (CG), situation guidance (SG), and both (SCG). CG symbology gives operators explicit instructions on what commands to input, whereas SG symbology gives operators implicit cues so that operators can infer the input commands. The combination of CG and SG provided operators with explicit and implicit cues allowing the operator to choose which symbology to utilize. The objective of the study was to understand how AR symbology affects the human operator's ability to align a robot arm to a target using a flight stick and the ability to allocate attention between the symbology and external views of the world. The study evaluated the effects type of symbology (CG and SG) has on operator tasks performance and attention allocation during teleoperation of a robot arm. The second study expanded on the first study by evaluating the effects of the type of navigational guidance (CG and SG) on operator task performance and attention allocation during teleoperation of a robot arm through uplinked commands. Although this study complements the first study on navigational guidance with hand controllers, it is a separate investigation due to the distinction in intended operators (i.e., crewmembers versus ground-operators). A third study looked at superimposed and integrated overlays for teleoperation of a mobile robot using a hand controller. When AR is superimposed on the external world, it appears to be fixed onto the display and internal to the operators' workstation. Unlike superimposed overlays, integrated overlays often appear as three-dimensional objects and move as if part of the external world. Studies conducted in the aviation domain show that integrated overlays can improve situation awareness and reduce the amount of deviation from the optimal path. The purpose of the study was to investigate whether these results apply to HRI tasks, such as navigation with a mobile robot.

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-10

A team KuuKulgur Robot from Estonia is seen on the practice field during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Tuesday, June 10, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Team KuuKulgur is one of eighteen teams competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-14

Sam Ortega, NASA program manager of Centennial Challenges, watches as robots attempt the rerun of the level one challenge during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Saturday, June 14, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-12

The team Survey robot retrieves a sample during a demonstration of the level two challenge at the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Thursday, June 12, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-11

The team AERO robot drives off the starting platform during the level one competition at the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Wednesday, June 11, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-14

Team Cephal's robot is seen on the starting platform during a rerun of the level one challenge at the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Saturday, June 14, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-11

The Oregon State University Mars Rover Team's robot is seen during level one competition at the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Wednesday, June 11, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-10

Jerry Waechter of team Middleman from Dunedin, Florida, works on their robot named Ro-Bear during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Tuesday, June 10, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Team Middleman is one of eighteen teams competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-14

A robot from the Intrepid Systems team is seen during the rerun of the level one challenge during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Saturday, June 14, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-11

A team KuuKulgur robot is seen as it begins the level one challenge during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Wednesday, June 11, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-11

The team Mountaineers robot is seen as it attempts the level one challenge during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Wednesday, June 11, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-11

Members of the Oregon State University Mars Rover Team prepare their robot to attempt the level one competition at the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Wednesday, June 11, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-11

The Stellar Automation Systems team poses for a picture with their robot after attempting the level one challenge during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Wednesday, June 11, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-12

The team Survey robot is seen as it conducts a demonstration of the level two challenge during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Thursday, June 12, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-11

All four of team KuuKulgur's robots are seen as they attempt the level one challenge during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Wednesday, June 11, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-12

Spectators watch as the team Survey robot conducts a demonstration of the level two challenge during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Thursday, June 12, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-11

Team Middleman's robot, Ro-Bear, is seen as it starts the level one challenge during the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Wednesday, June 11, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)

2014 NASA Centennial Challenges Sample Return Robot Challenge

NASA Image and Video Library

2014-06-14

The team Mountaineers robot is seen after picking up the sample during a rerun of the level one challenge at the 2014 NASA Centennial Challenges Sample Return Robot Challenge, Saturday, June 14, 2014, at the Worcester Polytechnic Institute (WPI) in Worcester, Mass. Eighteen teams are competing for a $1.5 million NASA prize purse. Teams will be required to demonstrate autonomous robots that can locate and collect samples from a wide and varied terrain, operating without human control. The objective of this NASA-WPI Centennial Challenge is to encourage innovations in autonomous navigation and robotics technologies. Innovations stemming from the challenge may improve NASA's capability to explore a variety of destinations in space, as well as enhance the nation's robotic technology for use in industries and applications on Earth. Photo Credit: (NASA/Joel Kowsky)