Assessment of repeatability of a wireless, inertial sensor-based lameness evaluation system for horses.

PubMed

Keegan, Kevin G; Kramer, Joanne; Yonezawa, Yoshiharu; Maki, Hiromitchi; Pai, P Frank; Dent, Eric V; Kellerman, Thomas E; Wilson, David A; Reed, Shannon K

2011-09-01

To determine repeatability of a wireless, inertial sensor-based lameness evaluation system in horses. 236 horses. Horses were from 2 to 29 years of age and of various breeds and lameness disposition. All horses were instrumented with a wireless, inertial sensor-based motion analysis system on the head (accelerometer), pelvis (midline croup region [accelerometer]), and right forelimb (gyroscope) before evaluation in 2 consecutive trials, approximately 5 minutes apart, as the horse was trotted in a straight line. Signal-processing algorithms generated overall trial asymmetry measures for vertical head and pelvic movement and stride-by-stride differences in head and pelvic maximum and minimum positions between right and left sides of each stride. Repeatability was determined, and trial difference was determined for groups of horses with various numbers of strides for which data were collected per trial. Inertial sensor-based measures of torso movement asymmetry were repeatable. Repeatability for measures of torso asymmetry for determination of hind limb lameness was slightly greater than that for forelimb lameness. Collecting large numbers of strides degraded stride-to-stride repeatability but did not degrade intertrial repeatability. The inertial sensor system used to measure asymmetry of head and pelvic movement as an aid in the detection and evaluation of lameness in horses trotting in a straight line was sufficiently repeatable to investigate for clinical use.

Global Kalman filter approaches to estimate absolute angles of lower limb segments.

PubMed

Nogueira, Samuel L; Lambrecht, Stefan; Inoue, Roberto S; Bortole, Magdo; Montagnoli, Arlindo N; Moreno, Juan C; Rocon, Eduardo; Terra, Marco H; Siqueira, Adriano A G; Pons, Jose L

2017-05-16

In this paper we propose the use of global Kalman filters (KFs) to estimate absolute angles of lower limb segments. Standard approaches adopt KFs to improve the performance of inertial sensors based on individual link configurations. In consequence, for a multi-body system like a lower limb exoskeleton, the inertial measurements of one link (e.g., the shank) are not taken into account in other link angle estimations (e.g., foot). Global KF approaches, on the other hand, correlate the collective contribution of all signals from lower limb segments observed in the state-space model through the filtering process. We present a novel global KF (matricial global KF) relying only on inertial sensor data, and validate both this KF and a previously presented global KF (Markov Jump Linear Systems, MJLS-based KF), which fuses data from inertial sensors and encoders from an exoskeleton. We furthermore compare both methods to the commonly used local KF. The results indicate that the global KFs performed significantly better than the local KF, with an average root mean square error (RMSE) of respectively 0.942° for the MJLS-based KF, 1.167° for the matrical global KF, and 1.202° for the local KFs. Including the data from the exoskeleton encoders also resulted in a significant increase in performance. The results indicate that the current practice of using KFs based on local models is suboptimal. Both the presented KF based on inertial sensor data, as well our previously presented global approach fusing inertial sensor data with data from exoskeleton encoders, were superior to local KFs. We therefore recommend to use global KFs for gait analysis and exoskeleton control.

Automatic identification of inertial sensor placement on human body segments during walking

PubMed Central

2013-01-01

Background Current inertial motion capture systems are rarely used in biomedical applications. The attachment and connection of the sensors with cables is often a complex and time consuming task. Moreover, it is prone to errors, because each sensor has to be attached to a predefined body segment. By using wireless inertial sensors and automatic identification of their positions on the human body, the complexity of the set-up can be reduced and incorrect attachments are avoided. We present a novel method for the automatic identification of inertial sensors on human body segments during walking. This method allows the user to place (wireless) inertial sensors on arbitrary body segments. Next, the user walks for just a few seconds and the segment to which each sensor is attached is identified automatically. Methods Walking data was recorded from ten healthy subjects using an Xsens MVN Biomech system with full-body configuration (17 inertial sensors). Subjects were asked to walk for about 6 seconds at normal walking speed (about 5 km/h). After rotating the sensor data to a global coordinate frame with x-axis in walking direction, y-axis pointing left and z-axis vertical, RMS, mean, and correlation coefficient features were extracted from x-, y- and z-components and magnitudes of the accelerations, angular velocities and angular accelerations. As a classifier, a decision tree based on the C4.5 algorithm was developed using Weka (Waikato Environment for Knowledge Analysis). Results and conclusions After testing the algorithm with 10-fold cross-validation using 31 walking trials (involving 527 sensors), 514 sensors were correctly classified (97.5%). When a decision tree for a lower body plus trunk configuration (8 inertial sensors) was trained and tested using 10-fold cross-validation, 100% of the sensors were correctly identified. This decision tree was also tested on walking trials of 7 patients (17 walking trials) after anterior cruciate ligament reconstruction, which also resulted in 100% correct identification, thus illustrating the robustness of the method. PMID:23517757

Automatic identification of inertial sensor placement on human body segments during walking.

PubMed

Weenk, Dirk; van Beijnum, Bert-Jan F; Baten, Chris T M; Hermens, Hermie J; Veltink, Peter H

2013-03-21

Current inertial motion capture systems are rarely used in biomedical applications. The attachment and connection of the sensors with cables is often a complex and time consuming task. Moreover, it is prone to errors, because each sensor has to be attached to a predefined body segment. By using wireless inertial sensors and automatic identification of their positions on the human body, the complexity of the set-up can be reduced and incorrect attachments are avoided.We present a novel method for the automatic identification of inertial sensors on human body segments during walking. This method allows the user to place (wireless) inertial sensors on arbitrary body segments. Next, the user walks for just a few seconds and the segment to which each sensor is attached is identified automatically. Walking data was recorded from ten healthy subjects using an Xsens MVN Biomech system with full-body configuration (17 inertial sensors). Subjects were asked to walk for about 6 seconds at normal walking speed (about 5 km/h). After rotating the sensor data to a global coordinate frame with x-axis in walking direction, y-axis pointing left and z-axis vertical, RMS, mean, and correlation coefficient features were extracted from x-, y- and z-components and magnitudes of the accelerations, angular velocities and angular accelerations. As a classifier, a decision tree based on the C4.5 algorithm was developed using Weka (Waikato Environment for Knowledge Analysis). After testing the algorithm with 10-fold cross-validation using 31 walking trials (involving 527 sensors), 514 sensors were correctly classified (97.5%). When a decision tree for a lower body plus trunk configuration (8 inertial sensors) was trained and tested using 10-fold cross-validation, 100% of the sensors were correctly identified. This decision tree was also tested on walking trials of 7 patients (17 walking trials) after anterior cruciate ligament reconstruction, which also resulted in 100% correct identification, thus illustrating the robustness of the method.

Gyroscope-reduced inertial navigation system for flight vehicle motion estimation

NASA Astrophysics Data System (ADS)

Wang, Xin; Xiao, Lu

2017-01-01

In this paper, a novel configuration of strategically distributed accelerometer sensors with the aid of one gyro to infer a flight vehicle's angular motion is presented. The MEMS accelerometer and gyro sensors are integrated to form a gyroscope-reduced inertial measurement unit (GR-IMU). The motivation for gyro aided accelerometers array is to have direct measurements of angular rates, which is an improvement to the traditional gyroscope-free inertial system that employs only direct measurements of specific force. Some technical issues regarding error calibration in accelerometers and gyro in GR-IMU are put forward. The GR-IMU based inertial navigation system can be used to find a complete attitude solution for flight vehicle motion estimation. Results of numerical simulation are given to illustrate the effectiveness of the proposed configuration. The gyroscope-reduced inertial navigation system based on distributed accelerometer sensors can be developed into a cost effective solution for a fast reaction, MEMS based motion capture system. Future work will include the aid from external navigation references (e.g. GPS) to improve long time mission performance.

Deep data fusion method for missile-borne inertial/celestial system

NASA Astrophysics Data System (ADS)

Zhang, Chunxi; Chen, Xiaofei; Lu, Jiazhen; Zhang, Hao

2018-05-01

Strap-down inertial-celestial integrated navigation system has the advantages of autonomy and high precision and is very useful for ballistic missiles. The star sensor installation error and inertial measurement error have a great influence for the system performance. Based on deep data fusion, this paper establishes measurement equations including star sensor installation error and proposes the deep fusion filter method. Simulations including misalignment error, star sensor installation error, IMU error are analyzed. Simulation results indicate that the deep fusion method can estimate the star sensor installation error and IMU error. Meanwhile, the method can restrain the misalignment errors caused by instrument errors.

POF-IMU sensor system: A fusion between inertial measurement units and POF sensors for low-cost and highly reliable systems

NASA Astrophysics Data System (ADS)

Leal-Junior, Arnaldo G.; Vargas-Valencia, Laura; dos Santos, Wilian M.; Schneider, Felipe B. A.; Siqueira, Adriano A. G.; Pontes, Maria José; Frizera, Anselmo

2018-07-01

This paper presents a low cost and highly reliable system for angle measurement based on a sensor fusion between inertial and fiber optic sensors. The system consists of the sensor fusion through Kalman filter of two inertial measurement units (IMUs) and an intensity variation-based polymer optical fiber (POF) curvature sensor. In addition, the IMU was applied as a reference for a compensation technique of POF curvature sensor hysteresis. The proposed system was applied on the knee angle measurement of a lower limb exoskeleton in flexion/extension cycles and in gait analysis. Results show the accuracy of the system, where the Root Mean Square Error (RMSE) between the POF-IMU sensor system and the encoder was below 4° in the worst case and about 1° in the best case. Then, the POF-IMU sensor system was evaluated as a wearable sensor for knee joint angle assessment without the exoskeleton, where its suitability for this purpose was demonstrated. The results obtained in this paper pave the way for future applications of sensor fusion between electronic and fiber optic sensors in movement analysis.

Wearable Inertial Sensors Allow for Quantitative Assessment of Shoulder and Elbow Kinematics in a Cadaveric Knee Arthroscopy Model.

PubMed

Rose, Michael; Curtze, Carolin; O'Sullivan, Joseph; El-Gohary, Mahmoud; Crawford, Dennis; Friess, Darin; Brady, Jacqueline M

2017-12-01

To develop a model using wearable inertial sensors to assess the performance of orthopaedic residents while performing a diagnostic knee arthroscopy. Fourteen subjects performed a diagnostic arthroscopy on a cadaveric right knee. Participants were divided into novices (5 postgraduate year 3 residents), intermediates (5 postgraduate year 4 residents), and experts (4 faculty) based on experience. Arm movement data were collected by inertial measurement units (Opal sensors) by securing 2 sensors to each upper extremity (dorsal forearm and lateral arm) and 2 sensors to the trunk (sternum and lumbar spine). Kinematics of the elbow and shoulder joints were calculated from the inertial data by biomechanical modeling based on a sequence of links connected by joints. Range of motion required to complete the procedure was calculated for each group. Histograms were used to compare the distribution of joint positions for an expert, intermediate, and novice. For both the right and left upper extremities, skill level corresponded well with shoulder abduction-adduction and elbow prono-supination. Novices required on average 17.2° more motion in the right shoulder abduction-adduction plane than experts to complete the diagnostic arthroscopy (P = .03). For right elbow prono-supination (probe hand), novices required on average 23.7° more motion than experts to complete the procedure (P = .03). Histogram data showed novices had markedly more variability in shoulder abduction-adduction and elbow prono-supination compared with the other groups. Our data show wearable inertial sensors can measure joint kinematics during diagnostic knee arthroscopy. Range-of-motion data in the shoulder and elbow correlated inversely with arthroscopic experience. Motion pattern-based analysis shows promise as a metric of resident skill acquisition and development in arthroscopy. Wearable inertial sensors show promise as metrics of arthroscopic skill acquisition among residents. Copyright © 2017 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

A Personal Inertial Navigation System Based on Multiple Distributed, Nine-Degrees-Of-Freedom, Inertial Measurement Units

DTIC Science & Technology

2016-12-01

based complementary filter developed at the Naval Postgraduate School, is developed. The performance of a consumer-grade nine-degrees-of-freedom IMU...measurement unit, complementary filter , gait phase detection, zero velocity update, MEMS, IMU, AHRS, GPS denied, distributed sensor, virtual sensor...algorithm and quaternion-based complementary filter developed at the Naval Postgraduate School, is developed. The performance of a consumer-grade nine

Walking Distance Estimation Using Walking Canes with Inertial Sensors

PubMed Central

Suh, Young Soo

2018-01-01

A walking distance estimation algorithm for cane users is proposed using an inertial sensor unit attached to various positions on the cane. A standard inertial navigation algorithm using an indirect Kalman filter was applied to update the velocity and position of the cane during movement. For quadripod canes, a standard zero-velocity measurement-updating method is proposed. For standard canes, a velocity-updating method based on an inverted pendulum model is proposed. The proposed algorithms were verified by three walking experiments with two different types of canes and different positions of the sensor module. PMID:29342971

Modeling and experimental study on characterization of micromachined thermal gas inertial sensors.

PubMed

Zhu, Rong; Ding, Henggao; Su, Yan; Yang, Yongjun

2010-01-01

Micromachined thermal gas inertial sensors based on heat convection are novel devices that compared with conventional micromachined inertial sensors offer the advantages of simple structures, easy fabrication, high shock resistance and good reliability by virtue of using a gaseous medium instead of a mechanical proof mass as key moving and sensing elements. This paper presents an analytical modeling for a micromachined thermal gas gyroscope integrated with signal conditioning. A simplified spring-damping model is utilized to characterize the behavior of the sensor. The model relies on the use of the fluid mechanics and heat transfer fundamentals and is validated using experimental data obtained from a test-device and simulation. Furthermore, the nonideal issues of the sensor are addressed from both the theoretical and experimental points of view. The nonlinear behavior demonstrated in experimental measurements is analyzed based on the model. It is concluded that the sources of nonlinearity are mainly attributable to the variable stiffness of the sensor system and the structural asymmetry due to nonideal fabrication.

Gyroscopic sensing in the wings of the hawkmoth Manduca sexta: the role of sensor location and directional sensitivity.

PubMed

Hinson, Brian T; Morgansen, Kristi A

2015-10-06

The wings of the hawkmoth Manduca sexta are lined with mechanoreceptors called campaniform sensilla that encode wing deformations. During flight, the wings deform in response to a variety of stimuli, including inertial-elastic loads due to the wing flapping motion, aerodynamic loads, and exogenous inertial loads transmitted by disturbances. Because the wings are actuated, flexible structures, the strain-sensitive campaniform sensilla are capable of detecting inertial rotations and accelerations, allowing the wings to serve not only as a primary actuator, but also as a gyroscopic sensor for flight control. We study the gyroscopic sensing of the hawkmoth wings from a control theoretic perspective. Through the development of a low-order model of flexible wing flapping dynamics, and the use of nonlinear observability analysis, we show that the rotational acceleration inherent in wing flapping enables the wings to serve as gyroscopic sensors. We compute a measure of sensor fitness as a function of sensor location and directional sensitivity by using the simulation-based empirical observability Gramian. Our results indicate that gyroscopic information is encoded primarily through shear strain due to wing twisting, where inertial rotations cause detectable changes in pronation and supination timing and magnitude. We solve an observability-based optimal sensor placement problem to find the optimal configuration of strain sensor locations and directional sensitivities for detecting inertial rotations. The optimal sensor configuration shows parallels to the campaniform sensilla found on hawkmoth wings, with clusters of sensors near the wing root and wing tip. The optimal spatial distribution of strain directional sensitivity provides a hypothesis for how heterogeneity of campaniform sensilla may be distributed.

Assessing hopping developmental level in childhood using wearable inertial sensor devices.

PubMed

Masci, Ilaria; Vannozzi, Giuseppe; Getchell, Nancy; Cappozzo, Aurelio

2012-07-01

Assessing movement skills is a fundamental issue in motor development. Current process-oriented assessments, such as developmental sequences, are based on subjective judgments; if paired with quantitative assessments, a better understanding of movement performance and developmental change could be obtained. Our purpose was to examine the use of inertial sensors to evaluate developmental differences in hopping over distance. Forty children executed the task wearing the inertial sensor and relevant time durations and 3D accelerations were obtained. Subjects were also categorized in different developmental levels according to the hopping developmental sequence. Results indicated that some time and kinematic parameters changed with some developmental levels, possibly as a function of anthropometry and previous motor experience. We concluded that, since inertial sensors were suitable in describing hopping performance and sensitive to developmental changes, this technology is promising as an in-field and user-independent motor development assessment tool.

A systematic review of gait analysis methods based on inertial sensors and adaptive algorithms.

PubMed

Caldas, Rafael; Mundt, Marion; Potthast, Wolfgang; Buarque de Lima Neto, Fernando; Markert, Bernd

2017-09-01

The conventional methods to assess human gait are either expensive or complex to be applied regularly in clinical practice. To reduce the cost and simplify the evaluation, inertial sensors and adaptive algorithms have been utilized, respectively. This paper aims to summarize studies that applied adaptive also called artificial intelligence (AI) algorithms to gait analysis based on inertial sensor data, verifying if they can support the clinical evaluation. Articles were identified through searches of the main databases, which were encompassed from 1968 to October 2016. We have identified 22 studies that met the inclusion criteria. The included papers were analyzed due to their data acquisition and processing methods with specific questionnaires. Concerning the data acquisition, the mean score is 6.1±1.62, what implies that 13 of 22 papers failed to report relevant outcomes. The quality assessment of AI algorithms presents an above-average rating (8.2±1.84). Therefore, AI algorithms seem to be able to support gait analysis based on inertial sensor data. Further research, however, is necessary to enhance and standardize the application in patients, since most of the studies used distinct methods to evaluate healthy subjects. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative Assessment of Parkinsonian Tremor Based on an Inertial Measurement Unit

PubMed Central

Dai, Houde; Zhang, Pengyue; Lueth, Tim C.

2015-01-01

Quantitative assessment of parkinsonian tremor based on inertial sensors can provide reliable feedback on the effect of medication. In this regard, the features of parkinsonian tremor and its unique properties such as motor fluctuations and dyskinesia are taken into account. Least-square-estimation models are used to assess the severities of rest, postural, and action tremors. In addition, a time-frequency signal analysis algorithm for tremor state detection was also included in the tremor assessment method. This inertial sensor-based method was verified through comparison with an electromagnetic motion tracking system. Seven Parkinson’s disease (PD) patients were tested using this tremor assessment system. The measured tremor amplitudes correlated well with the judgments of a neurologist (r = 0.98). The systematic analysis of sensor-based tremor quantification and the corresponding experiments could be of great help in monitoring the severity of parkinsonian tremor. PMID:26426020

Dual-use micromechanical inertial sensors

NASA Astrophysics Data System (ADS)

Elwell, John M., Jr.

1995-03-01

A new industry, which will provide low-cost silicon-based inertial sensors to the commercial and military markets. is being created. Inertial measurement units are used extensively in military systems, and new versions are expected to find their way into commercial products, such as automobiles, as production costs fall as technology advances. An automotive inertial measurement unit can be expected to perform a complete range of control, diagnostic, and navigation functions. These functions are expected to provide significant active safety, performance, comfort, convenience, and fuel economy advantages to the automotive consumer. An inertial measurement unit applicable to the automobile industry would meet many of the performance requirements for the military in important areas, such as antenna and image stabilization, autopilot control, and the guidance of smart weapons. Such a new industrial base will significantly reduce the acquisition cost of many future tactical weapons systems. An alliance, consisting of the Charles Stark Draper Laboratory and Rockwell International, has been created to develop inertial products for this new industry.

A Dynamic Precision Evaluation Method for the Star Sensor in the Stellar-Inertial Navigation System.

PubMed

Lu, Jiazhen; Lei, Chaohua; Yang, Yanqiang

2017-06-28

Integrating the advantages of INS (inertial navigation system) and the star sensor, the stellar-inertial navigation system has been used for a wide variety of applications. The star sensor is a high-precision attitude measurement instrument; therefore, determining how to validate its accuracy is critical in guaranteeing its practical precision. The dynamic precision evaluation of the star sensor is more difficult than a static precision evaluation because of dynamic reference values and other impacts. This paper proposes a dynamic precision verification method of star sensor with the aid of inertial navigation device to realize real-time attitude accuracy measurement. Based on the gold-standard reference generated by the star simulator, the altitude and azimuth angle errors of the star sensor are calculated for evaluation criteria. With the goal of diminishing the impacts of factors such as the sensors' drift and devices, the innovative aspect of this method is to employ static accuracy for comparison. If the dynamic results are as good as the static results, which have accuracy comparable to the single star sensor's precision, the practical precision of the star sensor is sufficiently high to meet the requirements of the system specification. The experiments demonstrate the feasibility and effectiveness of the proposed method.

A novel redundant INS based on triple rotary inertial measurement units

NASA Astrophysics Data System (ADS)

Chen, Gang; Li, Kui; Wang, Wei; Li, Peng

2016-10-01

Accuracy and reliability are two key performances of inertial navigation system (INS). Rotation modulation (RM) can attenuate the bias of inertial sensors and make it possible for INS to achieve higher navigation accuracy with lower-class sensors. Therefore, the conflict between the accuracy and cost of INS can be eased. Traditional system redundancy and recently researched sensor redundancy are two primary means to improve the reliability of INS. However, how to make the best use of the redundant information from redundant sensors hasn’t been studied adequately, especially in rotational INS. This paper proposed a novel triple rotary unit strapdown inertial navigation system (TRUSINS), which combines RM and sensor redundancy design to enhance the accuracy and reliability of rotational INS. Each rotary unit independently rotates to modulate the errors of two gyros and two accelerometers. Three units can provide double sets of measurements along all three axes of body frame to constitute a couple of INSs which make TRUSINS redundant. Experiments and simulations based on a prototype which is made up of six fiber-optic gyros with drift stability of 0.05° h-1 show that TRUSINS can achieve positioning accuracy of about 0.256 n mile h-1, which is ten times better than that of a normal non-rotational INS with the same level inertial sensors. The theoretical analysis and the experimental results show that due to the advantage of the innovative structure, the designed fault detection and isolation (FDI) strategy can tolerate six sensor faults at most, and is proved to be effective and practical. Therefore, TRUSINS is particularly suitable and highly beneficial for the applications where high accuracy and high reliability is required.

Research and Development of Electrostatic Accelerometers for Space Science Missions at HUST.

PubMed

Bai, Yanzheng; Li, Zhuxi; Hu, Ming; Liu, Li; Qu, Shaobo; Tan, Dingyin; Tu, Haibo; Wu, Shuchao; Yin, Hang; Li, Hongyin; Zhou, Zebing

2017-08-23

High-precision electrostatic accelerometers have achieved remarkable success in satellite Earth gravity field recovery missions. Ultralow-noise inertial sensors play important roles in space gravitational wave detection missions such as the Laser Interferometer Space Antenna (LISA) mission, and key technologies have been verified in the LISA Pathfinder mission. Meanwhile, at Huazhong University of Science and Technology (HUST, China), a space accelerometer and inertial sensor based on capacitive sensors and the electrostatic control technique have also been studied and developed independently for more than 16 years. In this paper, we review the operational principle, application, and requirements of the electrostatic accelerometer and inertial sensor in different space missions. The development and progress of a space electrostatic accelerometer at HUST, including ground investigation and space verification are presented.

Research and Development of Electrostatic Accelerometers for Space Science Missions at HUST

PubMed Central

Bai, Yanzheng; Li, Zhuxi; Hu, Ming; Liu, Li; Qu, Shaobo; Tan, Dingyin; Tu, Haibo; Wu, Shuchao; Yin, Hang; Li, Hongyin; Zhou, Zebing

2017-01-01

High-precision electrostatic accelerometers have achieved remarkable success in satellite Earth gravity field recovery missions. Ultralow-noise inertial sensors play important roles in space gravitational wave detection missions such as the Laser Interferometer Space Antenna (LISA) mission, and key technologies have been verified in the LISA Pathfinder mission. Meanwhile, at Huazhong University of Science and Technology (HUST, China), a space accelerometer and inertial sensor based on capacitive sensors and the electrostatic control technique have also been studied and developed independently for more than 16 years. In this paper, we review the operational principle, application, and requirements of the electrostatic accelerometer and inertial sensor in different space missions. The development and progress of a space electrostatic accelerometer at HUST, including ground investigation and space verification are presented. PMID:28832538

An Ambulatory Method of Identifying Anterior Cruciate Ligament Reconstructed Gait Patterns

PubMed Central

Patterson, Matthew R.; Delahunt, Eamonn; Sweeney, Kevin T.; Caulfield, Brian

2014-01-01

The use of inertial sensors to characterize pathological gait has traditionally been based on the calculation of temporal and spatial gait variables from inertial sensor data. This approach has proved successful in the identification of gait deviations in populations where substantial differences from normal gait patterns exist; such as in Parkinsonian gait. However, it is not currently clear if this approach could identify more subtle gait deviations, such as those associated with musculoskeletal injury. This study investigates whether additional analysis of inertial sensor data, based on quantification of gyroscope features of interest, would provide further discriminant capability in this regard. The tested cohort consisted of a group of anterior cruciate ligament reconstructed (ACL-R) females and a group of non-injured female controls, each performed ten walking trials. Gait performance was measured simultaneously using inertial sensors and an optoelectronic marker based system. The ACL-R group displayed kinematic and kinetic deviations from the control group, but no temporal or spatial deviations. This study demonstrates that quantification of gyroscope features can successfully identify changes associated with ACL-R gait, which was not possible using spatial or temporal variables. This finding may also have a role in other clinical applications where small gait deviations exist. PMID:24451464

Implementation and Performance of a GPS/INS Tightly Coupled Assisted PLL Architecture Using MEMS Inertial Sensors

PubMed Central

Tawk, Youssef; Tomé, Phillip; Botteron, Cyril; Stebler, Yannick; Farine, Pierre-André

2014-01-01

The use of global navigation satellite system receivers for navigation still presents many challenges in urban canyon and indoor environments, where satellite availability is typically reduced and received signals are attenuated. To improve the navigation performance in such environments, several enhancement methods can be implemented. For instance, external aid provided through coupling with other sensors has proven to contribute substantially to enhancing navigation performance and robustness. Within this context, coupling a very simple GPS receiver with an Inertial Navigation System (INS) based on low-cost micro-electro-mechanical systems (MEMS) inertial sensors is considered in this paper. In particular, we propose a GPS/INS Tightly Coupled Assisted PLL (TCAPLL) architecture, and present most of the associated challenges that need to be addressed when dealing with very-low-performance MEMS inertial sensors. In addition, we propose a data monitoring system in charge of checking the quality of the measurement flow in the architecture. The implementation of the TCAPLL is discussed in detail, and its performance under different scenarios is assessed. Finally, the architecture is evaluated through a test campaign using a vehicle that is driven in urban environments, with the purpose of highlighting the pros and cons of combining MEMS inertial sensors with GPS over GPS alone. PMID:24569773

Modification and fixed-point analysis of a Kalman filter for orientation estimation based on 9D inertial measurement unit data.

PubMed

Brückner, Hans-Peter; Spindeldreier, Christian; Blume, Holger

2013-01-01

A common approach for high accuracy sensor fusion based on 9D inertial measurement unit data is Kalman filtering. State of the art floating-point filter algorithms differ in their computational complexity nevertheless, real-time operation on a low-power microcontroller at high sampling rates is not possible. This work presents algorithmic modifications to reduce the computational demands of a two-step minimum order Kalman filter. Furthermore, the required bit-width of a fixed-point filter version is explored. For evaluation real-world data captured using an Xsens MTx inertial sensor is used. Changes in computational latency and orientation estimation accuracy due to the proposed algorithmic modifications and fixed-point number representation are evaluated in detail on a variety of processing platforms enabling on-board processing on wearable sensor platforms.

How Magnetic Disturbance Influences the Attitude and Heading in Magnetic and Inertial Sensor-Based Orientation Estimation.

PubMed

Fan, Bingfei; Li, Qingguo; Liu, Tao

2017-12-28

With the advancements in micro-electromechanical systems (MEMS) technologies, magnetic and inertial sensors are becoming more and more accurate, lightweight, smaller in size as well as low-cost, which in turn boosts their applications in human movement analysis. However, challenges still exist in the field of sensor orientation estimation, where magnetic disturbance represents one of the obstacles limiting their practical application. The objective of this paper is to systematically analyze exactly how magnetic disturbances affects the attitude and heading estimation for a magnetic and inertial sensor. First, we reviewed four major components dealing with magnetic disturbance, namely decoupling attitude estimation from magnetic reading, gyro bias estimation, adaptive strategies of compensating magnetic disturbance and sensor fusion algorithms. We review and analyze the features of existing methods of each component. Second, to understand each component in magnetic disturbance rejection, four representative sensor fusion methods were implemented, including gradient descent algorithms, improved explicit complementary filter, dual-linear Kalman filter and extended Kalman filter. Finally, a new standardized testing procedure has been developed to objectively assess the performance of each method against magnetic disturbance. Based upon the testing results, the strength and weakness of the existing sensor fusion methods were easily examined, and suggestions were presented for selecting a proper sensor fusion algorithm or developing new sensor fusion method.

Integrated rate isolation sensor

NASA Technical Reports Server (NTRS)

Brady, Tye (Inventor); Henderson, Timothy (Inventor); Phillips, Richard (Inventor); Zimpfer, Doug (Inventor); Crain, Tim (Inventor)

2012-01-01

In one embodiment, a system for providing fault-tolerant inertial measurement data includes a sensor for measuring an inertial parameter and a processor. The sensor has less accuracy than a typical inertial measurement unit (IMU). The processor detects whether a difference exists between a first data stream received from a first inertial measurement unit and a second data stream received from a second inertial measurement unit. Upon detecting a difference, the processor determines whether at least one of the first or second inertial measurement units has failed by comparing each of the first and second data streams to the inertial parameter.

Adaptive Monocular Visual-Inertial SLAM for Real-Time Augmented Reality Applications in Mobile Devices.

PubMed

Piao, Jin-Chun; Kim, Shin-Dug

2017-11-07

Simultaneous localization and mapping (SLAM) is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual-inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual-inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual-inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual-inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method.

Review of fall risk assessment in geriatric populations using inertial sensors

PubMed Central

2013-01-01

Background Falls are a prevalent issue in the geriatric population and can result in damaging physical and psychological consequences. Fall risk assessment can provide information to enable appropriate interventions for those at risk of falling. Wearable inertial-sensor-based systems can provide quantitative measures indicative of fall risk in the geriatric population. Methods Forty studies that used inertial sensors to evaluate geriatric fall risk were reviewed and pertinent methodological features were extracted; including, sensor placement, derived parameters used to assess fall risk, fall risk classification method, and fall risk classification model outcomes. Results Inertial sensors were placed only on the lower back in the majority of papers (65%). One hundred and thirty distinct variables were assessed, which were categorized as position and angle (7.7%), angular velocity (11.5%), linear acceleration (20%), spatial (3.8%), temporal (23.1%), energy (3.8%), frequency (15.4%), and other (14.6%). Fallers were classified using retrospective fall history (30%), prospective fall occurrence (15%), and clinical assessment (32.5%), with 22.5% using a combination of retrospective fall occurrence and clinical assessments. Half of the studies derived models for fall risk prediction, which reached high levels of accuracy (62-100%), specificity (35-100%), and sensitivity (55-99%). Conclusions Inertial sensors are promising sensors for fall risk assessment. Future studies should identify fallers using prospective techniques and focus on determining the most promising sensor sites, in conjunction with determination of optimally predictive variables. Further research should also attempt to link predictive variables to specific fall risk factors and investigate disease populations that are at high risk of falls. PMID:23927446

Quaternion-Based Unscented Kalman Filter for Accurate Indoor Heading Estimation Using Wearable Multi-Sensor System

PubMed Central

Yuan, Xuebing; Yu, Shuai; Zhang, Shengzhi; Wang, Guoping; Liu, Sheng

2015-01-01

Inertial navigation based on micro-electromechanical system (MEMS) inertial measurement units (IMUs) has attracted numerous researchers due to its high reliability and independence. The heading estimation, as one of the most important parts of inertial navigation, has been a research focus in this field. Heading estimation using magnetometers is perturbed by magnetic disturbances, such as indoor concrete structures and electronic equipment. The MEMS gyroscope is also used for heading estimation. However, the accuracy of gyroscope is unreliable with time. In this paper, a wearable multi-sensor system has been designed to obtain the high-accuracy indoor heading estimation, according to a quaternion-based unscented Kalman filter (UKF) algorithm. The proposed multi-sensor system including one three-axis accelerometer, three single-axis gyroscopes, one three-axis magnetometer and one microprocessor minimizes the size and cost. The wearable multi-sensor system was fixed on waist of pedestrian and the quadrotor unmanned aerial vehicle (UAV) for heading estimation experiments in our college building. The results show that the mean heading estimation errors are less 10° and 5° to multi-sensor system fixed on waist of pedestrian and the quadrotor UAV, respectively, compared to the reference path. PMID:25961384

The development and validation of using inertial sensors to monitor postural change in resistance exercise.

PubMed

Gleadhill, Sam; Lee, James Bruce; James, Daniel

2016-05-03

This research presented and validated a method of assessing postural changes during resistance exercise using inertial sensors. A simple lifting task was broken down to a series of well-defined tasks, which could be examined and measured in a controlled environment. The purpose of this research was to determine whether timing measures obtained from inertial sensor accelerometer outputs are able to provide accurate, quantifiable information of resistance exercise movement patterns. The aim was to complete a timing measure validation of inertial sensor outputs. Eleven participants completed five repetitions of 15 different deadlift variations. Participants were monitored with inertial sensors and an infrared three dimensional motion capture system. Validation was undertaken using a Will Hopkins Typical Error of the Estimate, with a Pearson׳s correlation and a Bland Altman Limits of Agreement analysis. Statistical validation measured the timing agreement during deadlifts, from inertial sensor outputs and the motion capture system. Timing validation results demonstrated a Pearson׳s correlation of 0.9997, with trivial standardised error (0.026) and standardised bias (0.002). Inertial sensors can now be used in practical settings with as much confidence as motion capture systems, for accelerometer timing measurements of resistance exercise. This research provides foundations for inertial sensors to be applied for qualitative activity recognition of resistance exercise and safe lifting practices. Copyright © 2016 Elsevier Ltd. All rights reserved.

Vision sensor and dual MEMS gyroscope integrated system for attitude determination on moving base

NASA Astrophysics Data System (ADS)

Guo, Xiaoting; Sun, Changku; Wang, Peng; Huang, Lu

2018-01-01

To determine the relative attitude between the objects on a moving base and the base reference system by a MEMS (Micro-Electro-Mechanical Systems) gyroscope, the motion information of the base is redundant, which must be removed from the gyroscope. Our strategy is to add an auxiliary gyroscope attached to the reference system. The master gyroscope is to sense the total motion, and the auxiliary gyroscope is to sense the motion of the moving base. By a generalized difference method, relative attitude in a non-inertial frame can be determined by dual gyroscopes. With the vision sensor suppressing accumulative drift of the MEMS gyroscope, the vision and dual MEMS gyroscope integration system is formed. Coordinate system definitions and spatial transform are executed in order to fuse inertial and visual data from different coordinate systems together. And a nonlinear filter algorithm, Cubature Kalman filter, is used to fuse slow visual data and fast inertial data together. A practical experimental setup is built up and used to validate feasibility and effectiveness of our proposed attitude determination system in the non-inertial frame on the moving base.

An Unobtrusive Fall Detection and Alerting System Based on Kalman Filter and Bayes Network Classifier.

PubMed

He, Jian; Bai, Shuang; Wang, Xiaoyi

2017-06-16

Falls are one of the main health risks among the elderly. A fall detection system based on inertial sensors can automatically detect fall event and alert a caregiver for immediate assistance, so as to reduce injuries causing by falls. Nevertheless, most inertial sensor-based fall detection technologies have focused on the accuracy of detection while neglecting quantization noise caused by inertial sensor. In this paper, an activity model based on tri-axial acceleration and gyroscope is proposed, and the difference between activities of daily living (ADLs) and falls is analyzed. Meanwhile, a Kalman filter is proposed to preprocess the raw data so as to reduce noise. A sliding window and Bayes network classifier are introduced to develop a wearable fall detection system, which is composed of a wearable motion sensor and a smart phone. The experiment shows that the proposed system distinguishes simulated falls from ADLs with a high accuracy of 95.67%, while sensitivity and specificity are 99.0% and 95.0%, respectively. Furthermore, the smart phone can issue an alarm to caregivers so as to provide timely and accurate help for the elderly, as soon as the system detects a fall.

How Magnetic Disturbance Influences the Attitude and Heading in Magnetic and Inertial Sensor-Based Orientation Estimation

PubMed Central

Li, Qingguo

2017-01-01

With the advancements in micro-electromechanical systems (MEMS) technologies, magnetic and inertial sensors are becoming more and more accurate, lightweight, smaller in size as well as low-cost, which in turn boosts their applications in human movement analysis. However, challenges still exist in the field of sensor orientation estimation, where magnetic disturbance represents one of the obstacles limiting their practical application. The objective of this paper is to systematically analyze exactly how magnetic disturbances affects the attitude and heading estimation for a magnetic and inertial sensor. First, we reviewed four major components dealing with magnetic disturbance, namely decoupling attitude estimation from magnetic reading, gyro bias estimation, adaptive strategies of compensating magnetic disturbance and sensor fusion algorithms. We review and analyze the features of existing methods of each component. Second, to understand each component in magnetic disturbance rejection, four representative sensor fusion methods were implemented, including gradient descent algorithms, improved explicit complementary filter, dual-linear Kalman filter and extended Kalman filter. Finally, a new standardized testing procedure has been developed to objectively assess the performance of each method against magnetic disturbance. Based upon the testing results, the strength and weakness of the existing sensor fusion methods were easily examined, and suggestions were presented for selecting a proper sensor fusion algorithm or developing new sensor fusion method. PMID:29283432

Inertial navigation system using three TDF gyroscopic sensors not jointly mounted on a stable platform

NASA Technical Reports Server (NTRS)

Stieler, B.

1971-01-01

An inertial navigation system is described and analyzed based on two two-degree-of-freedom Schuler-gyropendulums and one two-degree-of-freedom azimuth gyro. The three sensors, each base motion isolated about its two input axes, are mounted on a common base, strapped down to the vehicle. The up and down pointing spin vectors of the two properly tuned gyropendulums track the vertical and indicate physically their velocity with respect to inertial space. The spin vector of the azimuth gyro is pointing northerly parallel to the earth axis. The system can be made self-aligning on a stationary base. If external measurements for the north direction and the vertical are available, initial disturbance torques can be measured and easily biased out. The error analysis shows that the system is practicable with today's technology.

Applications of inertial-sensor high-inheritance instruments to DSN precision antenna pointing

NASA Technical Reports Server (NTRS)

Goddard, R. E.

1992-01-01

Laboratory test results of the initialization and tracking performance of an existing inertial-sensor-based instrument are given. The instrument, although not primarily designed for precision antenna pointing applications, demonstrated an on-average 10-hour tracking error of several millidegrees. The system-level instrument performance is shown by analysis to be sensor limited. Simulated instrument improvements show a tracking error of less than 1 mdeg, which would provide acceptable performance, i.e., low pointing loss, for the DSN 70-m antenna sub network, operating at Ka-band (1-cm wavelength).

Applications of inertial-sensor high-inheritance instruments to DSN precision antenna pointing

NASA Technical Reports Server (NTRS)

Goddard, R. E.

1992-01-01

Laboratory test results of the initialization and tracking performance of an existing inertial-sensor-based instrument are given. The instrument, although not primarily designed for precision antenna pointing applications, demonstrated an on-average 10-hour tracking error of several millidegrees. The system-level instrument performance is shown by analysis to be sensor limited. Simulated instrument improvements show a tracking error of less than 1 mdeg, which would provide acceptable performance, i.e., low pointing loss, for the Deep Space Network 70-m antenna subnetwork, operating at Ka-band (1-cm wavelength).

MEMS inertial sensors with integral rotation means.

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

Kohler, Stewart M.

The state-of-the-art of inertial micro-sensors (gyroscopes and accelerometers) has advanced to the point where they are displacing the more traditional sensors in many size, power, and/or cost-sensitive applications. A factor limiting the range of application of inertial micro-sensors has been their relatively poor bias stability. The incorporation of an integral sensitive axis rotation capability would enable bias mitigation through proven techniques such as indexing, and foster the use of inertial micro-sensors in more accuracy-sensitive applications. Fabricating the integral rotation mechanism in MEMS technology would minimize the penalties associated with incorporation of this capability, and preserve the inherent advantages of inertialmore » micro-sensors.« less

Inertial Sensor Assisted Acquisition, Tracking, and Pointing for High Data Rate Free Space Optical Communications

NASA Technical Reports Server (NTRS)

Lee, Shinhak; Ortiz, Gerry G.

2003-01-01

We discuss use of inertial sensors to facilitate deep space optical communications. Implementation of this concept requires accurate and wide bandwidth inertial sensors. In this presentation, the principal concept and algorithm using linear accelerometers will be given along with the simulation and experimental results.

Adaptive Monocular Visual–Inertial SLAM for Real-Time Augmented Reality Applications in Mobile Devices

PubMed Central

Piao, Jin-Chun; Kim, Shin-Dug

2017-01-01

Simultaneous localization and mapping (SLAM) is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual–inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual–inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual–inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual–inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method. PMID:29112143

INS/GNSS Integration for Aerobatic Flight Applications and Aircraft Motion Surveying.

PubMed

V Hinüber, Edgar L; Reimer, Christian; Schneider, Tim; Stock, Michael

2017-04-26

This paper presents field tests of challenging flight applications obtained with a new family of lightweight low-power INS/GNSS ( inertial navigation system/global satellite navigation system ) solutions based on MEMS ( micro-electro-mechanical- sensor ) machined sensors, being used for UAV ( unmanned aerial vehicle ) navigation and control as well as for aircraft motion dynamics analysis and trajectory surveying. One key is a 42+ state extended Kalman-filter-based powerful data fusion, which also allows the estimation and correction of parameters that are typically affected by sensor aging, especially when applying MEMS-based inertial sensors, and which is not yet deeply considered in the literature. The paper presents the general system architecture, which allows iMAR Navigation the integration of all classes of inertial sensors and GNSS ( global navigation satellite system ) receivers from very-low-cost MEMS and high performance MEMS over FOG ( fiber optical gyro ) and RLG ( ring laser gyro ) up to HRG ( hemispherical resonator gyro ) technology, and presents detailed flight test results obtained under extreme flight conditions. As a real-world example, the aerobatic maneuvers of the World Champion 2016 (Red Bull Air Race) are presented. Short consideration is also given to surveying applications, where the ultimate performance of the same data fusion, but applied on gravimetric surveying, is discussed.

Drift-Free Position Estimation of Periodic or Quasi-Periodic Motion Using Inertial Sensors

PubMed Central

Latt, Win Tun; Veluvolu, Kalyana Chakravarthy; Ang, Wei Tech

2011-01-01

Position sensing with inertial sensors such as accelerometers and gyroscopes usually requires other aided sensors or prior knowledge of motion characteristics to remove position drift resulting from integration of acceleration or velocity so as to obtain accurate position estimation. A method based on analytical integration has previously been developed to obtain accurate position estimate of periodic or quasi-periodic motion from inertial sensors using prior knowledge of the motion but without using aided sensors. In this paper, a new method is proposed which employs linear filtering stage coupled with adaptive filtering stage to remove drift and attenuation. The prior knowledge of the motion the proposed method requires is only approximate band of frequencies of the motion. Existing adaptive filtering methods based on Fourier series such as weighted-frequency Fourier linear combiner (WFLC), and band-limited multiple Fourier linear combiner (BMFLC) are modified to combine with the proposed method. To validate and compare the performance of the proposed method with the method based on analytical integration, simulation study is performed using periodic signals as well as real physiological tremor data, and real-time experiments are conducted using an ADXL-203 accelerometer. Results demonstrate that the performance of the proposed method outperforms the existing analytical integration method. PMID:22163935

INS/GNSS Integration for Aerobatic Flight Applications and Aircraft Motion Surveying

PubMed Central

v. Hinüber, Edgar L.; Reimer, Christian; Schneider, Tim; Stock, Michael

2017-01-01

This paper presents field tests of challenging flight applications obtained with a new family of lightweight low-power INS/GNSS (inertial navigation system/global satellite navigation system) solutions based on MEMS (micro-electro-mechanical- sensor) machined sensors, being used for UAV (unmanned aerial vehicle) navigation and control as well as for aircraft motion dynamics analysis and trajectory surveying. One key is a 42+ state extended Kalman-filter-based powerful data fusion, which also allows the estimation and correction of parameters that are typically affected by sensor aging, especially when applying MEMS-based inertial sensors, and which is not yet deeply considered in the literature. The paper presents the general system architecture, which allows iMAR Navigation the integration of all classes of inertial sensors and GNSS (global navigation satellite system) receivers from very-low-cost MEMS and high performance MEMS over FOG (fiber optical gyro) and RLG (ring laser gyro) up to HRG (hemispherical resonator gyro) technology, and presents detailed flight test results obtained under extreme flight conditions. As a real-world example, the aerobatic maneuvers of the World Champion 2016 (Red Bull Air Race) are presented. Short consideration is also given to surveying applications, where the ultimate performance of the same data fusion, but applied on gravimetric surveying, is discussed. PMID:28445417

Research on the optimal structure configuration of dither RLG used in skewed redundant INS

NASA Astrophysics Data System (ADS)

Gao, Chunfeng; Wang, Qi; Wei, Guo; Long, Xingwu

2016-05-01

The actual combat effectiveness of weapon equipment is restricted by the performance of Inertial Navigation System (INS), especially in high reliability required situations such as fighter, satellite and submarine. Through the use of skewed sensor geometries, redundant technique has been applied to reduce the cost and improve the reliability of the INS. In this paper, the structure configuration and the inertial sensor characteristics of Skewed Redundant Strapdown Inertial Navigation System (SRSINS) using dithered Ring Laser Gyroscope (RLG) are analyzed. For the dither coupling effects of the dither gyro, the system measurement errors can be amplified either the individual gyro dither frequency is near one another or the structure of the SRSINS is unreasonable. Based on the characteristics of RLG, the research on coupled vibration of dithered RLG in SRSINS is carried out. On the principle of optimal navigation performance, optimal reliability and optimal cost-effectiveness, the comprehensive evaluation scheme of the inertial sensor configuration of SRINS is given.

Inertial navigation sensor integrated motion analysis for autonomous vehicle navigation

NASA Technical Reports Server (NTRS)

Roberts, Barry; Bhanu, Bir

1992-01-01

Recent work on INS integrated motion analysis is described. Results were obtained with a maximally passive system of obstacle detection (OD) for ground-based vehicles and rotorcraft. The OD approach involves motion analysis of imagery acquired by a passive sensor in the course of vehicle travel to generate range measurements to world points within the sensor FOV. INS data and scene analysis results are used to enhance interest point selection, the matching of the interest points, and the subsequent motion-based computations, tracking, and OD. The most important lesson learned from the research described here is that the incorporation of inertial data into the motion analysis program greatly improves the analysis and makes the process more robust.

Human Body Parts Tracking and Kinematic Features Assessment Based on RSSI and Inertial Sensor Measurements

PubMed Central

Blumrosen, Gaddi; Luttwak, Ami

2013-01-01

Acquisition of patient kinematics in different environments plays an important role in the detection of risk situations such as fall detection in elderly patients, in rehabilitation of patients with injuries, and in the design of treatment plans for patients with neurological diseases. Received Signal Strength Indicator (RSSI) measurements in a Body Area Network (BAN), capture the signal power on a radio link. The main aim of this paper is to demonstrate the potential of utilizing RSSI measurements in assessment of human kinematic features, and to give methods to determine these features. RSSI measurements can be used for tracking different body parts' displacements on scales of a few centimeters, for classifying motion and gait patterns instead of inertial sensors, and to serve as an additional reference to other sensors, in particular inertial sensors. Criteria and analytical methods for body part tracking, kinematic motion feature extraction, and a Kalman filter model for aggregation of RSSI and inertial sensor were derived. The methods were verified by a set of experiments performed in an indoor environment. In the future, the use of RSSI measurements can help in continuous assessment of various kinematic features of patients during their daily life activities and enhance medical diagnosis accuracy with lower costs. PMID:23979481

Human body parts tracking and kinematic features assessment based on RSSI and inertial sensor measurements.

PubMed

Blumrosen, Gaddi; Luttwak, Ami

2013-08-23

Acquisition of patient kinematics in different environments plays an important role in the detection of risk situations such as fall detection in elderly patients, in rehabilitation of patients with injuries, and in the design of treatment plans for patients with neurological diseases. Received Signal Strength Indicator (RSSI) measurements in a Body Area Network (BAN), capture the signal power on a radio link. The main aim of this paper is to demonstrate the potential of utilizing RSSI measurements in assessment of human kinematic features, and to give methods to determine these features. RSSI measurements can be used for tracking different body parts' displacements on scales of a few centimeters, for classifying motion and gait patterns instead of inertial sensors, and to serve as an additional reference to other sensors, in particular inertial sensors. Criteria and analytical methods for body part tracking, kinematic motion feature extraction, and a Kalman filter model for aggregation of RSSI and inertial sensor were derived. The methods were verified by a set of experiments performed in an indoor environment. In the future, the use of RSSI measurements can help in continuous assessment of various kinematic features of patients during their daily life activities and enhance medical diagnosis accuracy with lower costs.

A Robust Method to Detect Zero Velocity for Improved 3D Personal Navigation Using Inertial Sensors

PubMed Central

Xu, Zhengyi; Wei, Jianming; Zhang, Bo; Yang, Weijun

2015-01-01

This paper proposes a robust zero velocity (ZV) detector algorithm to accurately calculate stationary periods in a gait cycle. The proposed algorithm adopts an effective gait cycle segmentation method and introduces a Bayesian network (BN) model based on the measurements of inertial sensors and kinesiology knowledge to infer the ZV period. During the detected ZV period, an Extended Kalman Filter (EKF) is used to estimate the error states and calibrate the position error. The experiments reveal that the removal rate of ZV false detections by the proposed method increases 80% compared with traditional method at high walking speed. Furthermore, based on the detected ZV, the Personal Inertial Navigation System (PINS) algorithm aided by EKF performs better, especially in the altitude aspect. PMID:25831086

A vector-based failure detection and isolation algorithm for a dual fail-operational redundant strapdown inertial measurement unit

NASA Technical Reports Server (NTRS)

Morrell, Frederick R.; Bailey, Melvin L.

1987-01-01

A vector-based failure detection and isolation technique for a skewed array of two degree-of-freedom inertial sensors is developed. Failure detection is based on comparison of parity equations with a threshold, and isolation is based on comparison of logic variables which are keyed to pass/fail results of the parity test. A multi-level approach to failure detection is used to ensure adequate coverage for the flight control, display, and navigation avionics functions. Sensor error models are introduced to expose the susceptibility of the parity equations to sensor errors and physical separation effects. The algorithm is evaluated in a simulation of a commercial transport operating in a range of light to severe turbulence environments. A bias-jump failure level of 0.2 deg/hr was detected and isolated properly in the light and moderate turbulence environments, but not detected in the extreme turbulence environment. An accelerometer bias-jump failure level of 1.5 milli-g was detected over all turbulence environments. For both types of inertial sensor, hard-over, and null type failures were detected in all environments without incident. The algorithm functioned without false alarm or isolation over all turbulence environments for the runs tested.

On the Design of Attitude-Heading Reference Systems Using the Allan Variance.

PubMed

Hidalgo-Carrió, Javier; Arnold, Sascha; Poulakis, Pantelis

2016-04-01

The Allan variance is a method to characterize stochastic random processes. The technique was originally developed to characterize the stability of atomic clocks and has also been successfully applied to the characterization of inertial sensors. Inertial navigation systems (INS) can provide accurate results in a short time, which tend to rapidly degrade in longer time intervals. During the last decade, the performance of inertial sensors has significantly improved, particularly in terms of signal stability, mechanical robustness, and power consumption. The mass and volume of inertial sensors have also been significantly reduced, offering system-level design and accommodation advantages. This paper presents a complete methodology for the characterization and modeling of inertial sensors using the Allan variance, with direct application to navigation systems. Although the concept of sensor fusion is relatively straightforward, accurate characterization and sensor-information filtering is not a trivial task, yet they are essential for good performance. A complete and reproducible methodology utilizing the Allan variance, including all the intermediate steps, is described. An end-to-end (E2E) process for sensor-error characterization and modeling up to the final integration in the sensor-fusion scheme is explained in detail. The strength of this approach is demonstrated with representative tests on novel, high-grade inertial sensors. Experimental navigation results are presented from two distinct robotic applications: a planetary exploration rover prototype and an autonomous underwater vehicle (AUV).

Analysis and Compensation of Modulation Angular Rate Error Based on Missile-Borne Rotation Semi-Strapdown Inertial Navigation System.

PubMed

Zhang, Jiayu; Li, Jie; Zhang, Xi; Che, Xiaorui; Huang, Yugang; Feng, Kaiqiang

2018-05-04

The Semi-Strapdown Inertial Navigation System (SSINS) provides a new solution to attitude measurement of a high-speed rotating missile. However, micro-electro-mechanical-systems (MEMS) inertial measurement unit (MIMU) outputs are corrupted by significant sensor errors. In order to improve the navigation precision, a rotation modulation technology method called Rotation Semi-Strapdown Inertial Navigation System (RSSINS) is introduced into SINS. In fact, the stability of the modulation angular rate is difficult to achieve in a high-speed rotation environment. The changing rotary angular rate has an impact on the inertial sensor error self-compensation. In this paper, the influence of modulation angular rate error, including acceleration-deceleration process, and instability of the angular rate on the navigation accuracy of RSSINS is deduced and the error characteristics of the reciprocating rotation scheme are analyzed. A new compensation method is proposed to remove or reduce sensor errors so as to make it possible to maintain high precision autonomous navigation performance by MIMU when there is no external aid. Experiments have been carried out to validate the performance of the method. In addition, the proposed method is applicable for modulation angular rate error compensation under various dynamic conditions.

Space Shuttle Earth Observation sensors pointing and stabilization requirements study

NASA Technical Reports Server (NTRS)

1976-01-01

The shuttle orbiter inertial measurement unit (IMU), located in the orbiter cabin, is used to supply inertial attitude reference signals; and, in conjunction with the onboard navigation system, can provide a pointing capability of the navigation base accurate to within plus or minus 0.5 deg for earth viewing missions. This pointing accuracy can degrade to approximately plus or minus 2.0 deg for payloads located in the aft bay due to structural flexure of the shuttle vehicle, payload structural and mounting misalignments, and calibration errors with respect to the navigation base. Drawbacks to obtaining pointing accuracy by using the orbiter RCS jets are discussed. Supplemental electromechanical pointing systems are developed to provide independent pointing for individual sensors, or sensor groupings. The missions considered and the sensors required for these missions and the parameters of each sensor are described. Assumptions made to derive pointing and stabilization requirements are delineated.

Differential GNSS and Vision-Based Tracking to Improve Navigation Performance in Cooperative Multi-UAV Systems.

PubMed

Vetrella, Amedeo Rodi; Fasano, Giancarmine; Accardo, Domenico; Moccia, Antonio

2016-12-17

Autonomous navigation of micro-UAVs is typically based on the integration of low cost Global Navigation Satellite System (GNSS) receivers and Micro-Electro-Mechanical Systems (MEMS)-based inertial and magnetic sensors to stabilize and control the flight. The resulting navigation performance in terms of position and attitude accuracy may not suffice for other mission needs, such as the ones relevant to fine sensor pointing. In this framework, this paper presents a cooperative UAV navigation algorithm that allows a chief vehicle, equipped with inertial and magnetic sensors, a Global Positioning System (GPS) receiver, and a vision system, to improve its navigation performance (in real time or in the post processing phase) exploiting formation flying deputy vehicles equipped with GPS receivers. The focus is set on outdoor environments and the key concept is to exploit differential GPS among vehicles and vision-based tracking (DGPS/Vision) to build a virtual additional navigation sensor whose information is then integrated in a sensor fusion algorithm based on an Extended Kalman Filter. The developed concept and processing architecture are described, with a focus on DGPS/Vision attitude determination algorithm. Performance assessment is carried out on the basis of both numerical simulations and flight tests. In the latter ones, navigation estimates derived from the DGPS/Vision approach are compared with those provided by the onboard autopilot system of a customized quadrotor. The analysis shows the potential of the developed approach, mainly deriving from the possibility to exploit magnetic- and inertial-independent accurate attitude information.

Measuring upper limb function in children with hemiparesis with 3D inertial sensors.

PubMed

Newman, Christopher J; Bruchez, Roselyn; Roches, Sylvie; Jequier Gygax, Marine; Duc, Cyntia; Dadashi, Farzin; Massé, Fabien; Aminian, Kamiar

2017-12-01

Upper limb assessments in children with hemiparesis rely on clinical measurements, which despite standardization are prone to error. Recently, 3D movement analysis using optoelectronic setups has been used to measure upper limb movement, but generalization is hindered by time and cost. Body worn inertial sensors may provide a simple, cost-effective alternative. We instrumented a subset of 30 participants in a mirror therapy clinical trial at baseline, post-treatment, and follow-up clinical assessments, with wireless inertial sensors positioned on the arms and trunk to monitor motion during reaching tasks. Inertial sensor measurements distinguished paretic and non-paretic limbs with significant differences (P < 0.01) in movement duration, power, range of angular velocity, elevation, and smoothness (normalized jerk index and spectral arc length). Inertial sensor measurements correlated with functional clinical tests (Melbourne Assessment 2); movement duration and complexity (Higuchi fractal dimension) showed moderate to strong negative correlations with clinical measures of amplitude, accuracy, and fluency. Inertial sensor measurements reliably identify paresis and correlate with clinical measurements; they can therefore provide a complementary dimension of assessment in clinical practice and during clinical trials aimed at improving upper limb function.

Passive Sensor Integration for Vehicle Self-Localization in Urban Traffic Environment †

PubMed Central

Gu, Yanlei; Hsu, Li-Ta; Kamijo, Shunsuke

2015-01-01

This research proposes an accurate vehicular positioning system which can achieve lane-level performance in urban canyons. Multiple passive sensors, which include Global Navigation Satellite System (GNSS) receivers, onboard cameras and inertial sensors, are integrated in the proposed system. As the main source for the localization, the GNSS technique suffers from Non-Line-Of-Sight (NLOS) propagation and multipath effects in urban canyons. This paper proposes to employ a novel GNSS positioning technique in the integration. The employed GNSS technique reduces the multipath and NLOS effects by using the 3D building map. In addition, the inertial sensor can describe the vehicle motion, but has a drift problem as time increases. This paper develops vision-based lane detection, which is firstly used for controlling the drift of the inertial sensor. Moreover, the lane keeping and changing behaviors are extracted from the lane detection function, and further reduce the lateral positioning error in the proposed localization system. We evaluate the integrated localization system in the challenging city urban scenario. The experiments demonstrate the proposed method has sub-meter accuracy with respect to mean positioning error. PMID:26633420

A novel optimal configuration form redundant MEMS inertial sensors based on the orthogonal rotation method.

PubMed

Cheng, Jianhua; Dong, Jinlu; Landry, Rene; Chen, Daidai

2014-07-29

In order to improve the accuracy and reliability of micro-electro mechanical systems (MEMS) navigation systems, an orthogonal rotation method-based nine-gyro redundant MEMS configuration is presented. By analyzing the accuracy and reliability characteristics of an inertial navigation system (INS), criteria for redundant configuration design are introduced. Then the orthogonal rotation configuration is formed through a two-rotation of a set of orthogonal inertial sensors around a space vector. A feasible installation method is given for the real engineering realization of this proposed configuration. The performances of the novel configuration and another six configurations are comprehensively compared and analyzed. Simulation and experimentation are also conducted, and the results show that the orthogonal rotation configuration has the best reliability, accuracy and fault detection and isolation (FDI) performance when the number of gyros is nine.

Comparison of quantitative evaluation between cutaneous and transosseous inertial sensors in anterior cruciate ligament deficient knee: A cadaveric study.

PubMed

Murase, Atsunori; Nozaki, Masahiro; Kobayashi, Masaaki; Goto, Hideyuki; Yoshida, Masahito; Yasuma, Sanshiro; Takenaga, Tetsuya; Nagaya, Yuko; Mizutani, Jun; Okamoto, Hideki; Iguchi, Hirotaka; Otsuka, Takanobu

2017-09-01

Recently several authors have reported on the quantitative evaluation of the pivot-shift test using cutaneous fixation of inertial sensors. Before utilizing this sensor for clinical studies, it is necessary to evaluate the accuracy of cutaneous sensor in assessing rotational knee instability. To evaluate the accuracy of inertial sensors, we compared cutaneous and transosseous sensors in the quantitative assessment of rotational knee instability in a cadaveric setting, in order to demonstrate their clinical applicability. Eight freshly frozen human cadaveric knees were used in this study. Inertial sensors were fixed on the tibial tuberosity and directly fixed to the distal tibia bone. A single examiner performed the pivot shift test from flexion to extension on the intact knees and ACL deficient knees. The peak overall magnitude of acceleration and the maximum rotational angular velocity in the tibial superoinferior axis was repeatedly measured with the inertial sensor during the pivot shift test. Correlations between cutaneous and transosseous inertial sensors were evaluated, as well as statistical analysis for differences between ACL intact and ACL deficient knees. Acceleration and angular velocity measured with the cutaneous sensor demonstrated a strong positive correlation with the transosseous sensor (r = 0.86 and r = 0.83). Comparison between cutaneous and transosseous sensor indicated significant difference for the peak overall magnitude of acceleration (cutaneous: 10.3 ± 5.2 m/s 2 , transosseous: 14.3 ± 7.6 m/s 2 , P < 0.01) and for the maximum internal rotation angular velocity (cutaneous: 189.5 ± 99.6 deg/s, transosseous: 225.1 ± 103.3 deg/s, P < 0.05), but no significant difference for the maximum external rotation angular velocity (cutaneous: 176.1 ± 87.3 deg/s, transosseous: 195.9 ± 106.2 deg/s, N.S). There is a positive correlation between cutaneous and transosseous inertial sensors. Therefore, this study indicated that the cutaneous inertial sensors could be used clinically for quantifying rotational knee instability, irrespective of the location of utilization. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Study of the motion artefacts of skin-mounted inertial sensors under different attachment conditions.

PubMed

Forner-Cordero, A; Mateu-Arce, M; Forner-Cordero, I; Alcántara, E; Moreno, J C; Pons, J L

2008-04-01

A common problem shared by accelerometers, inertial sensors and any motion measurement method based on skin-mounted sensors is the movement of the soft tissues covering the bones. The aim of this work is to propose a method for the validation of the attachment of skin-mounted sensors. A second-order (mass-spring-damper) model was proposed to characterize the behaviour of the soft tissue between the bone and the sensor. Three sets of experiments were performed. In the first one, different procedures to excite the system were evaluated to select an adequate excitation stimulus. In the second one, the selected stimulus was applied under varying attachment conditions while the third experiment was used to test the model. The heel drop was chosen as the excitation method because it showed lower variability and could discriminate between different attachment conditions. There was, in agreement with the model, a trend to increase the natural frequency of the system with decreasing accelerometer mass. An important result is the development of a standard procedure to test the bandwidth of skin-mounted inertial sensors, such as accelerometers mounted on the skin or markers heavier than a few grams.

Ambulatory position and orientation tracking fusing magnetic and inertial sensing.

PubMed

Roetenberg, Daniel; Slycke, Per J; Veltink, Peter H

2007-05-01

This paper presents the design and testing of a portable magnetic system combined with miniature inertial sensors for ambulatory 6 degrees of freedom (DOF) human motion tracking. The magnetic system consists of three orthogonal coils, the source, fixed to the body and 3-D magnetic sensors, fixed to remote body segments, which measure the fields generated by the source. Based on the measured signals, a processor calculates the relative positions and orientations between source and sensor. Magnetic actuation requires a substantial amount of energy which limits the update rate with a set of batteries. Moreover, the magnetic field can easily be disturbed by ferromagnetic materials or other sources. Inertial sensors can be sampled at high rates, require only little energy and do not suffer from magnetic interferences. However, accelerometers and gyroscopes can only measure changes in position and orientation and suffer from integration drift. By combing measurements from both systems in a complementary Kalman filter structure, an optimal solution for position and orientation estimates is obtained. The magnetic system provides 6 DOF measurements at a relatively low update rate while the inertial sensors track the changes position and orientation in between the magnetic updates. The implemented system is tested against a lab-bound camera tracking system for several functional body movements. The accuracy was about 5 mm for position and 3 degrees for orientation measurements. Errors were higher during movements with high velocities due to relative movement between source and sensor within one cycle of magnetic actuation.

Detecting inertial effects with airborne matter-wave interferometry

PubMed Central

Geiger, R.; Ménoret, V.; Stern, G.; Zahzam, N.; Cheinet, P.; Battelier, B.; Villing, A.; Moron, F.; Lours, M.; Bidel, Y.; Bresson, A.; Landragin, A.; Bouyer, P.

2011-01-01

Inertial sensors relying on atom interferometry offer a breakthrough advance in a variety of applications, such as inertial navigation, gravimetry or ground- and space-based tests of fundamental physics. These instruments require a quiet environment to reach their performance and using them outside the laboratory remains a challenge. Here we report the first operation of an airborne matter-wave accelerometer set up aboard a 0g plane and operating during the standard gravity (1g) and microgravity (0g) phases of the flight. At 1g, the sensor can detect inertial effects more than 300 times weaker than the typical acceleration fluctuations of the aircraft. We describe the improvement of the interferometer sensitivity in 0g, which reaches 2 x 10-4 ms-2 / √Hz with our current setup. We finally discuss the extension of our method to airborne and spaceborne tests of the Universality of free fall with matter waves. PMID:21934658

Improving activity recognition using a wearable barometric pressure sensor in mobility-impaired stroke patients.

PubMed

Massé, Fabien; Gonzenbach, Roman R; Arami, Arash; Paraschiv-Ionescu, Anisoara; Luft, Andreas R; Aminian, Kamiar

2015-08-25

Stroke survivors often suffer from mobility deficits. Current clinical evaluation methods, including questionnaires and motor function tests, cannot provide an objective measure of the patients' mobility in daily life. Physical activity performance in daily-life can be assessed using unobtrusive monitoring, for example with a single sensor module fixed on the trunk. Existing approaches based on inertial sensors have limited performance, particularly in detecting transitions between different activities and postures, due to the inherent inter-patient variability of kinematic patterns. To overcome these limitations, one possibility is to use additional information from a barometric pressure (BP) sensor. Our study aims at integrating BP and inertial sensor data into an activity classifier in order to improve the activity (sitting, standing, walking, lying) recognition and the corresponding body elevation (during climbing stairs or when taking an elevator). Taking into account the trunk elevation changes during postural transitions (sit-to-stand, stand-to-sit), we devised an event-driven activity classifier based on fuzzy-logic. Data were acquired from 12 stroke patients with impaired mobility, using a trunk-worn inertial and BP sensor. Events, including walking and lying periods and potential postural transitions, were first extracted. These events were then fed into a double-stage hierarchical Fuzzy Inference System (H-FIS). The first stage processed the events to infer activities and the second stage improved activity recognition by applying behavioral constraints. Finally, the body elevation was estimated using a pattern-enhancing algorithm applied on BP. The patients were videotaped for reference. The performance of the algorithm was estimated using the Correct Classification Rate (CCR) and F-score. The BP-based classification approach was benchmarked against a previously-published fuzzy-logic classifier (FIS-IMU) and a conventional epoch-based classifier (EPOCH). The algorithm performance for posture/activity detection, in terms of CCR was 90.4 %, with 3.3 % and 5.6 % improvements against FIS-IMU and EPOCH, respectively. The proposed classifier essentially benefits from a better recognition of standing activity (70.3 % versus 61.5 % [FIS-IMU] and 42.5 % [EPOCH]) with 98.2 % CCR for body elevation estimation. The monitoring and recognition of daily activities in mobility-impaired stoke patients can be significantly improved using a trunk-fixed sensor that integrates BP, inertial sensors, and an event-based activity classifier.

A sensor fusion method for tracking vertical velocity and height based on inertial and barometric altimeter measurements.

PubMed

Sabatini, Angelo Maria; Genovese, Vincenzo

2014-07-24

A sensor fusion method was developed for vertical channel stabilization by fusing inertial measurements from an Inertial Measurement Unit (IMU) and pressure altitude measurements from a barometric altimeter integrated in the same device (baro-IMU). An Extended Kalman Filter (EKF) estimated the quaternion from the sensor frame to the navigation frame; the sensed specific force was rotated into the navigation frame and compensated for gravity, yielding the vertical linear acceleration; finally, a complementary filter driven by the vertical linear acceleration and the measured pressure altitude produced estimates of height and vertical velocity. A method was also developed to condition the measured pressure altitude using a whitening filter, which helped to remove the short-term correlation due to environment-dependent pressure changes from raw pressure altitude. The sensor fusion method was implemented to work on-line using data from a wireless baro-IMU and tested for the capability of tracking low-frequency small-amplitude vertical human-like motions that can be critical for stand-alone inertial sensor measurements. Validation tests were performed in different experimental conditions, namely no motion, free-fall motion, forced circular motion and squatting. Accurate on-line tracking of height and vertical velocity was achieved, giving confidence to the use of the sensor fusion method for tracking typical vertical human motions: velocity Root Mean Square Error (RMSE) was in the range 0.04-0.24 m/s; height RMSE was in the range 5-68 cm, with statistically significant performance gains when the whitening filter was used by the sensor fusion method to track relatively high-frequency vertical motions.

Analysis and Compensation of Modulation Angular Rate Error Based on Missile-Borne Rotation Semi-Strapdown Inertial Navigation System

PubMed Central

Zhang, Jiayu; Li, Jie; Zhang, Xi; Che, Xiaorui; Huang, Yugang; Feng, Kaiqiang

2018-01-01

The Semi-Strapdown Inertial Navigation System (SSINS) provides a new solution to attitude measurement of a high-speed rotating missile. However, micro-electro-mechanical-systems (MEMS) inertial measurement unit (MIMU) outputs are corrupted by significant sensor errors. In order to improve the navigation precision, a rotation modulation technology method called Rotation Semi-Strapdown Inertial Navigation System (RSSINS) is introduced into SINS. In fact, the stability of the modulation angular rate is difficult to achieve in a high-speed rotation environment. The changing rotary angular rate has an impact on the inertial sensor error self-compensation. In this paper, the influence of modulation angular rate error, including acceleration-deceleration process, and instability of the angular rate on the navigation accuracy of RSSINS is deduced and the error characteristics of the reciprocating rotation scheme are analyzed. A new compensation method is proposed to remove or reduce sensor errors so as to make it possible to maintain high precision autonomous navigation performance by MIMU when there is no external aid. Experiments have been carried out to validate the performance of the method. In addition, the proposed method is applicable for modulation angular rate error compensation under various dynamic conditions. PMID:29734707

Differential GNSS and Vision-Based Tracking to Improve Navigation Performance in Cooperative Multi-UAV Systems

PubMed Central

Vetrella, Amedeo Rodi; Fasano, Giancarmine; Accardo, Domenico; Moccia, Antonio

2016-01-01

Autonomous navigation of micro-UAVs is typically based on the integration of low cost Global Navigation Satellite System (GNSS) receivers and Micro-Electro-Mechanical Systems (MEMS)-based inertial and magnetic sensors to stabilize and control the flight. The resulting navigation performance in terms of position and attitude accuracy may not suffice for other mission needs, such as the ones relevant to fine sensor pointing. In this framework, this paper presents a cooperative UAV navigation algorithm that allows a chief vehicle, equipped with inertial and magnetic sensors, a Global Positioning System (GPS) receiver, and a vision system, to improve its navigation performance (in real time or in the post processing phase) exploiting formation flying deputy vehicles equipped with GPS receivers. The focus is set on outdoor environments and the key concept is to exploit differential GPS among vehicles and vision-based tracking (DGPS/Vision) to build a virtual additional navigation sensor whose information is then integrated in a sensor fusion algorithm based on an Extended Kalman Filter. The developed concept and processing architecture are described, with a focus on DGPS/Vision attitude determination algorithm. Performance assessment is carried out on the basis of both numerical simulations and flight tests. In the latter ones, navigation estimates derived from the DGPS/Vision approach are compared with those provided by the onboard autopilot system of a customized quadrotor. The analysis shows the potential of the developed approach, mainly deriving from the possibility to exploit magnetic- and inertial-independent accurate attitude information. PMID:27999318

Vision and dual IMU integrated attitude measurement system

NASA Astrophysics Data System (ADS)

Guo, Xiaoting; Sun, Changku; Wang, Peng; Lu, Huang

2018-01-01

To determination relative attitude between two space objects on a rocking base, an integrated system based on vision and dual IMU (inertial determination unit) is built up. The determination system fuses the attitude information of vision with the angular determinations of dual IMU by extended Kalman filter (EKF) to obtain the relative attitude. One IMU (master) is attached to the measured motion object and the other (slave) to the rocking base. As the determination output of inertial sensor is relative to inertial frame, thus angular rate of the master IMU includes not only motion of the measured object relative to inertial frame but also the rocking base relative to inertial frame, where the latter can be seen as redundant harmful movement information for relative attitude determination between the measured object and the rocking base. The slave IMU here assists to remove the motion information of rocking base relative to inertial frame from the master IMU. The proposed integrated attitude determination system is tested on practical experimental platform. And experiment results with superior precision and reliability show the feasibility and effectiveness of the proposed attitude determination system.

Inertial sensor self-calibration in a visually-aided navigation approach for a micro-AUV.

PubMed

Bonin-Font, Francisco; Massot-Campos, Miquel; Negre-Carrasco, Pep Lluis; Oliver-Codina, Gabriel; Beltran, Joan P

2015-01-16

This paper presents a new solution for underwater observation, image recording, mapping and 3D reconstruction in shallow waters. The platform, designed as a research and testing tool, is based on a small underwater robot equipped with a MEMS-based IMU, two stereo cameras and a pressure sensor. The data given by the sensors are fused, adjusted and corrected in a multiplicative error state Kalman filter (MESKF), which returns a single vector with the pose and twist of the vehicle and the biases of the inertial sensors (the accelerometer and the gyroscope). The inclusion of these biases in the state vector permits their self-calibration and stabilization, improving the estimates of the robot orientation. Experiments in controlled underwater scenarios and in the sea have demonstrated a satisfactory performance and the capacity of the vehicle to operate in real environments and in real time.

Inertial Sensor Self-Calibration in a Visually-Aided Navigation Approach for a Micro-AUV

PubMed Central

Bonin-Font, Francisco; Massot-Campos, Miquel; Negre-Carrasco, Pep Lluis; Oliver-Codina, Gabriel; Beltran, Joan P.

2015-01-01

This paper presents a new solution for underwater observation, image recording, mapping and 3D reconstruction in shallow waters. The platform, designed as a research and testing tool, is based on a small underwater robot equipped with a MEMS-based IMU, two stereo cameras and a pressure sensor. The data given by the sensors are fused, adjusted and corrected in a multiplicative error state Kalman filter (MESKF), which returns a single vector with the pose and twist of the vehicle and the biases of the inertial sensors (the accelerometer and the gyroscope). The inclusion of these biases in the state vector permits their self-calibration and stabilization, improving the estimates of the robot orientation. Experiments in controlled underwater scenarios and in the sea have demonstrated a satisfactory performance and the capacity of the vehicle to operate in real environments and in real time. PMID:25602263

The limb movement analysis of rehabilitation exercises using wearable inertial sensors.

PubMed

Bingquan Huang; Giggins, Oonagh; Kechadi, Tahar; Caulfield, Brian

2016-08-01

Due to no supervision of a therapist in home based exercise programs, inertial sensor based feedback systems which can accurately assess movement repetitions are urgently required. The synchronicity and the degrees of freedom both show that one movement might resemble another movement signal which is mixed in with another not precisely defined movement. Therefore, the data and feature selections are important for movement analysis. This paper explores the data and feature selection for the limb movement analysis of rehabilitation exercises. The results highlight that the classification accuracy is very sensitive to the mount location of the sensors. The results show that the use of 2 or 3 sensor units, the combination of acceleration and gyroscope data, and the feature sets combined by the statistical feature set with another type of feature, can significantly improve the classification accuracy rates. The results illustrate that acceleration data is more effective than gyroscope data for most of the movement analysis.

Enhancing Positioning Accuracy in Urban Terrain by Fusing Data from a GPS Receiver, Inertial Sensors, Stereo-Camera and Digital Maps for Pedestrian Navigation

PubMed Central

Przemyslaw, Baranski; Pawel, Strumillo

2012-01-01

The paper presents an algorithm for estimating a pedestrian location in an urban environment. The algorithm is based on the particle filter and uses different data sources: a GPS receiver, inertial sensors, probability maps and a stereo camera. Inertial sensors are used to estimate a relative displacement of a pedestrian. A gyroscope estimates a change in the heading direction. An accelerometer is used to count a pedestrian's steps and their lengths. The so-called probability maps help to limit GPS inaccuracy by imposing constraints on pedestrian kinematics, e.g., it is assumed that a pedestrian cannot cross buildings, fences etc. This limits position inaccuracy to ca. 10 m. Incorporation of depth estimates derived from a stereo camera that are compared to the 3D model of an environment has enabled further reduction of positioning errors. As a result, for 90% of the time, the algorithm is able to estimate a pedestrian location with an error smaller than 2 m, compared to an error of 6.5 m for a navigation based solely on GPS. PMID:22969321

Flight test results of the Strapdown hexad Inertial Reference Unit (SIRU). Volume 1: Flight test summary

NASA Technical Reports Server (NTRS)

Hruby, R. J.; Bjorkman, W. S.

1977-01-01

Flight test results of the strapdown inertial reference unit (SIRU) navigation system are presented. The fault-tolerant SIRU navigation system features a redundant inertial sensor unit and dual computers. System software provides for detection and isolation of inertial sensor failures and continued operation in the event of failures. Flight test results include assessments of the system's navigational performance and fault tolerance.

Observability Analysis of a Matrix Kalman Filter-Based Navigation System Using Visual/Inertial/Magnetic Sensors

PubMed Central

Feng, Guohu; Wu, Wenqi; Wang, Jinling

2012-01-01

A matrix Kalman filter (MKF) has been implemented for an integrated navigation system using visual/inertial/magnetic sensors. The MKF rearranges the original nonlinear process model in a pseudo-linear process model. We employ the observability rank criterion based on Lie derivatives to verify the conditions under which the nonlinear system is observable. It has been proved that such observability conditions are: (a) at least one degree of rotational freedom is excited, and (b) at least two linearly independent horizontal lines and one vertical line are observed. Experimental results have validated the correctness of these observability conditions. PMID:23012523

Estimating Three-Dimensional Orientation of Human Body Parts by Inertial/Magnetic Sensing

PubMed Central

Sabatini, Angelo Maria

2011-01-01

User-worn sensing units composed of inertial and magnetic sensors are becoming increasingly popular in various domains, including biomedical engineering, robotics, virtual reality, where they can also be applied for real-time tracking of the orientation of human body parts in the three-dimensional (3D) space. Although they are a promising choice as wearable sensors under many respects, the inertial and magnetic sensors currently in use offer measuring performance that are critical in order to achieve and maintain accurate 3D-orientation estimates, anytime and anywhere. This paper reviews the main sensor fusion and filtering techniques proposed for accurate inertial/magnetic orientation tracking of human body parts; it also gives useful recipes for their actual implementation. PMID:22319365

Estimating three-dimensional orientation of human body parts by inertial/magnetic sensing.

PubMed

Sabatini, Angelo Maria

2011-01-01

User-worn sensing units composed of inertial and magnetic sensors are becoming increasingly popular in various domains, including biomedical engineering, robotics, virtual reality, where they can also be applied for real-time tracking of the orientation of human body parts in the three-dimensional (3D) space. Although they are a promising choice as wearable sensors under many respects, the inertial and magnetic sensors currently in use offer measuring performance that are critical in order to achieve and maintain accurate 3D-orientation estimates, anytime and anywhere. This paper reviews the main sensor fusion and filtering techniques proposed for accurate inertial/magnetic orientation tracking of human body parts; it also gives useful recipes for their actual implementation.

Design of a Wireless Sensor Module for Monitoring Conductor Galloping of Transmission Lines.

PubMed

Huang, Xinbo; Zhao, Long; Chen, Guimin

2016-10-09

Conductor galloping may cause flashovers and even tower collapses. The available conductor galloping monitoring methods often employ acceleration sensors to measure the conductor translations without considering the conductor twist. In this paper, a new sensor for monitoring conductor galloping of transmission lines based on an inertial measurement unit and wireless communication is proposed. An inertial measurement unit is used for collecting the accelerations and angular rates of a conductor, which are further transformed into the corresponding geographic coordinate frame using a quaternion transformation to reconstruct the galloping of the conductor. Both the hardware design and the software design are described in details. The corresponding test platforms are established, and the experiments show the feasibility and accuracy of the proposed monitoring sensor. The field operation of the proposed sensor in a conductor spanning 734 m also shows its effectiveness.

A Personal Navigation System Based on Inertial and Magnetic Field Measurements

DTIC Science & Technology

2010-09-01

MATLAB IMPLEMENTATION.................................................................74 G. A MODEL FOR PENDULUM MOTION SENSOR DATA...76 1. Pendulum Model for MATLAB Simulation....................................76 2. Sensor Data Generated with the Pendulum Model... PENDULUM ..................................................................................................88 I. FILTER PERFORMANCE WITH REAL PENDULUM DATA

Flight test results of the strapdown hexad inertial reference unit (SIRU). Volume 2: Test report

NASA Technical Reports Server (NTRS)

Hruby, R. J.; Bjorkman, W. S.

1977-01-01

Results of flight tests of the Strapdown Inertial Reference Unit (SIRU) navigation system are presented. The fault tolerant SIRU navigation system features a redundant inertial sensor unit and dual computers. System software provides for detection and isolation of inertial sensor failures and continued operation in the event of failures. Flight test results include assessments of the system's navigational performance and fault tolerance. Performance shortcomings are analyzed.

Distributed Autonomous Control Action Based on Sensor and Mission Fusion

DTIC Science & Technology

2005-09-01

programmable control algorithm driven by the readings of two pressure switch sensors located on either side of the valve unit. Thus, a micro-controller...and Characterization The process of leak detection and characterization must be accomplished with a set of pressure switch sensors. This sensor...economically supplementing existing widely used pressure switch type sensors which are characterized by prohibitively long inertial lag responses

Self-Alignment MEMS IMU Method Based on the Rotation Modulation Technique on a Swing Base

PubMed Central

Chen, Zhiyong; Yang, Haotian; Wang, Chengbin; Lin, Zhihui; Guo, Meifeng

2018-01-01

The micro-electro-mechanical-system (MEMS) inertial measurement unit (IMU) has been widely used in the field of inertial navigation due to its small size, low cost, and light weight, but aligning MEMS IMUs remains a challenge for researchers. MEMS IMUs have been conventionally aligned on a static base, requiring other sensors, such as magnetometers or satellites, to provide auxiliary information, which limits its application range to some extent. Therefore, improving the alignment accuracy of MEMS IMU as much as possible under swing conditions is of considerable value. This paper proposes an alignment method based on the rotation modulation technique (RMT), which is completely self-aligned, unlike the existing alignment techniques. The effect of the inertial sensor errors is mitigated by rotating the IMU. Then, inertial frame-based alignment using the rotation modulation technique (RMT-IFBA) achieved coarse alignment on the swing base. The strong tracking filter (STF) further improved the alignment accuracy. The performance of the proposed method was validated with a physical experiment, and the results of the alignment showed that the standard deviations of pitch, roll, and heading angle were 0.0140°, 0.0097°, and 0.91°, respectively, which verified the practicality and efficacy of the proposed method for the self-alignment of the MEMS IMU on a swing base. PMID:29649150

A Sensor Fusion Method for Tracking Vertical Velocity and Height Based on Inertial and Barometric Altimeter Measurements

PubMed Central

Sabatini, Angelo Maria; Genovese, Vincenzo

2014-01-01

A sensor fusion method was developed for vertical channel stabilization by fusing inertial measurements from an Inertial Measurement Unit (IMU) and pressure altitude measurements from a barometric altimeter integrated in the same device (baro-IMU). An Extended Kalman Filter (EKF) estimated the quaternion from the sensor frame to the navigation frame; the sensed specific force was rotated into the navigation frame and compensated for gravity, yielding the vertical linear acceleration; finally, a complementary filter driven by the vertical linear acceleration and the measured pressure altitude produced estimates of height and vertical velocity. A method was also developed to condition the measured pressure altitude using a whitening filter, which helped to remove the short-term correlation due to environment-dependent pressure changes from raw pressure altitude. The sensor fusion method was implemented to work on-line using data from a wireless baro-IMU and tested for the capability of tracking low-frequency small-amplitude vertical human-like motions that can be critical for stand-alone inertial sensor measurements. Validation tests were performed in different experimental conditions, namely no motion, free-fall motion, forced circular motion and squatting. Accurate on-line tracking of height and vertical velocity was achieved, giving confidence to the use of the sensor fusion method for tracking typical vertical human motions: velocity Root Mean Square Error (RMSE) was in the range 0.04–0.24 m/s; height RMSE was in the range 5–68 cm, with statistically significant performance gains when the whitening filter was used by the sensor fusion method to track relatively high-frequency vertical motions. PMID:25061835

Performance Thresholds for Application of MEMS Inertial Sensors in Space

NASA Technical Reports Server (NTRS)

Smit, Geoffrey N.

1995-01-01

We review types of inertial sensors available and current usage of inertial sensors in space and the performance requirements for these applications. We then assess the performance available from micro-electro-mechanical systems (MEMS) devices, both in the near and far term. Opportunities for the application of these devices are identified. A key point is that although the performance available from MEMS inertial sensors is significantly lower than that achieved by existing macroscopic devices (at least in the near term), the low cost, low size, and power of the MEMS devices opens up a number of applications. In particular, we show that there are substantial benefits to using MEMS devices to provide vibration, and for some missions, attitude sensing. In addition, augmentation for global positioning system (GPS) navigation systems holds much promise.

Inertial Measurements for Aero-assisted Navigation (IMAN)

NASA Technical Reports Server (NTRS)

Jah, Moriba; Lisano, Michael; Hockney, George

2007-01-01

IMAN is a Python tool that provides inertial sensor-based estimates of spacecraft trajectories within an atmospheric influence. It provides Kalman filter-derived spacecraft state estimates based upon data collected onboard, and is shown to perform at a level comparable to the conventional methods of spacecraft navigation in terms of accuracy and at a higher level with regard to the availability of results immediately after completion of an atmospheric drag pass.

Auto detection and segmentation of physical activities during a Timed-Up-and-Go (TUG) task in healthy older adults using multiple inertial sensors.

PubMed

Nguyen, Hung P; Ayachi, Fouaz; Lavigne-Pelletier, Catherine; Blamoutier, Margaux; Rahimi, Fariborz; Boissy, Patrick; Jog, Mandar; Duval, Christian

2015-04-11

Recently, much attention has been given to the use of inertial sensors for remote monitoring of individuals with limited mobility. However, the focus has been mostly on the detection of symptoms, not specific activities. The objective of the present study was to develop an automated recognition and segmentation algorithm based on inertial sensor data to identify common gross motor patterns during activity of daily living. A modified Time-Up-And-Go (TUG) task was used since it is comprised of four common daily living activities; Standing, Walking, Turning, and Sitting, all performed in a continuous fashion resulting in six different segments during the task. Sixteen healthy older adults performed two trials of a 5 and 10 meter TUG task. They were outfitted with 17 inertial motion sensors covering each body segment. Data from the 10 meter TUG were used to identify pertinent sensors on the trunk, head, hip, knee, and thigh that provided suitable data for detecting and segmenting activities associated with the TUG. Raw data from sensors were detrended to remove sensor drift, normalized, and band pass filtered with optimal frequencies to reveal kinematic peaks that corresponded to different activities. Segmentation was accomplished by identifying the time stamps of the first minimum or maximum to the right and the left of these peaks. Segmentation time stamps were compared to results from two examiners visually segmenting the activities of the TUG. We were able to detect these activities in a TUG with 100% sensitivity and specificity (n = 192) during the 10 meter TUG. The rate of success was subsequently confirmed in the 5 meter TUG (n = 192) without altering the parameters of the algorithm. When applying the segmentation algorithms to the 10 meter TUG, we were able to parse 100% of the transition points (n = 224) between different segments that were as reliable and less variable than visual segmentation performed by two independent examiners. The present study lays the foundation for the development of a comprehensive algorithm to detect and segment naturalistic activities using inertial sensors, in hope of evaluating automatically motor performance within the detected tasks.

Development and Flight Test of a Robust Optical-Inertial Navigation System Using Low-Cost Sensors

DTIC Science & Technology

2008-03-01

for this test. Though, marketed as a GPS/INS, it was in fact used simply as an IMU for this test. The raw inertial measurement data (from the...Performance Evaluation of Low Cost MEMS-Based IMU Integrated With GPS for Land Vehicle Navigation Application. MS Thesis, UCGE Reports Number

Inertial Gait Phase Detection for control of a drop foot stimulator Inertial sensing for gait phase detection.

PubMed

Kotiadis, D; Hermens, H J; Veltink, P H

2010-05-01

An Inertial Gait Phase Detection system was developed to replace heel switches and footswitches currently being used for the triggering of drop foot stimulators. A series of four algorithms utilising accelerometers and gyroscopes individually and in combination were tested and initial results are shown. Sensors were positioned on the outside of the upper shank. Tests were performed on data gathered from a subject, sufferer of stroke, implanted with a drop foot stimulator and triggered with the current trigger, the heel switch. Data tested includes a variety of activities representing everyday life. Flat surface walking, rough terrain and carpet walking show 100% detection and the ability of the algorithms to ignore non-gait events such as weight shifts. Timing analysis is performed against the current triggering method, the heel switch. After evaluating the heel switch timing against a reference system, namely the Vicon 370 marker and force plates system. Initial results show a close correlation between the current trigger detection and the inertial sensor based triggering algorithms. Algorithms were tested for stairs up and stairs down. Best results are observed for algorithms using gyroscope data. Algorithms were designed using threshold techniques for lowest possible computational load and with least possible sensor components to minimize power requirements and to allow for potential future implantation of sensor system.

Actuation stability test of the LISA pathfinder inertial sensor front-end electronics

NASA Astrophysics Data System (ADS)

Mance, Davor; Gan, Li; Weber, Bill; Weber, Franz; Zweifel, Peter

In order to limit the residual stray forces on the inertial sensor test mass in LISA pathfinder, √ it is required that the fluctuation of the test mass actuation voltage is within 2ppm/ Hz. The actuation voltage stability test on the flight hardware of the inertial sensor front-end electronics (IS FEE) is presented in this paper. This test is completed during the inertial sensor integration at EADS Astrium Friedrichshafen, Germany. The standard measurement method using voltmeter is not sufficient for verification, since the instrument low frequency √ fluctuation is higher than the 2ppm/ Hz requirement. In this test, by using the differential measurement method and the lock-in amplifier, the actuation stability performance is verified and the quality of the IS FEE hardware is confirmed by the test results.

Image deblurring in smartphone devices using built-in inertial measurement sensors

NASA Astrophysics Data System (ADS)

Šindelář, Ondřej; Šroubek, Filip

2013-01-01

Long-exposure handheld photography is degraded with blur, which is difficult to remove without prior information about the camera motion. In this work, we utilize inertial sensors (accelerometers and gyroscopes) in modern smartphones to detect exact motion trajectory of the smartphone camera during exposure and remove blur from the resulting photography based on the recorded motion data. The whole system is implemented on the Android platform and embedded in the smartphone device, resulting in a close-to-real-time deblurring algorithm. The performance of the proposed system is demonstrated in real-life scenarios.

Miniature Inertial and Augmentation Sensors for Integrated Inertial/GPS Based Navigation Applications

DTIC Science & Technology

2010-03-01

in this paper. Velocity sensing can be accomplished in the optical domain with laser Doppler radar (i.e. LIDAR ), through RF band or ultrasonic... Doppler radar. Reference [34] discusses an example of a LIDAR based velocimeter, used to furnish landing speed information for spacecraft terminal descent...in military (and commercial) capabilities: the Ring Laser Gyro (since ~1975), Fiber Optic Gyros (since ~1985), and MEMS (since ~1995). RLGs enabled

Overcoming urban GPS navigation challenges through the use of MEMS inertial sensors and proper verification of navigation system performance

NASA Astrophysics Data System (ADS)

Vinande, Eric T.

This research proposes several means to overcome challenges in the urban environment to ground vehicle global positioning system (GPS) receiver navigation performance through the integration of external sensor information. The effects of narrowband radio frequency interference and signal attenuation, both common in the urban environment, are examined with respect to receiver signal tracking processes. Low-cost microelectromechanical systems (MEMS) inertial sensors, suitable for the consumer market, are the focus of receiver augmentation as they provide an independent measure of motion and are independent of vehicle systems. A method for estimating the mounting angles of an inertial sensor cluster utilizing typical urban driving maneuvers is developed and is able to provide angular measurements within two degrees of truth. The integration of GPS and MEMS inertial sensors is developed utilizing a full state navigation filter. Appropriate statistical methods are developed to evaluate the urban environment navigation improvement due to the addition of MEMS inertial sensors. A receiver evaluation metric that combines accuracy, availability, and maximum error measurements is presented and evaluated over several drive tests. Following a description of proper drive test techniques, record and playback systems are evaluated as the optimal way of testing multiple receivers and/or integrated navigation systems in the urban environment as they simplify vehicle testing requirements.

A Robust Nonlinear Observer for Real-Time Attitude Estimation Using Low-Cost MEMS Inertial Sensors

PubMed Central

Guerrero-Castellanos, José Fermi; Madrigal-Sastre, Heberto; Durand, Sylvain; Torres, Lizeth; Muñoz-Hernández, German Ardul

2013-01-01

This paper deals with the attitude estimation of a rigid body equipped with angular velocity sensors and reference vector sensors. A quaternion-based nonlinear observer is proposed in order to fuse all information sources and to obtain an accurate estimation of the attitude. It is shown that the observer error dynamics can be separated into two passive subsystems connected in “feedback”. Then, this property is used to show that the error dynamics is input-to-state stable when the measurement disturbance is seen as an input and the error as the state. These results allow one to affirm that the observer is “robustly stable”. The proposed observer is evaluated in real-time with the design and implementation of an Attitude and Heading Reference System (AHRS) based on low-cost MEMS (Micro-Electro-Mechanical Systems) Inertial Measure Unit (IMU) and magnetic sensors and a 16-bit microcontroller. The resulting estimates are compared with a high precision motion system to demonstrate its performance. PMID:24201316

78 FR 22529 - Notice of Availability of Government-Owned Inventions; Available for Licensing

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-16

.... 101875: INERTIAL SENSORS USING SLIDING PLANE ELECTRON TUNNELING PROXIMITY SWITCHES//Navy Case No. 102181... TRIGGER FOR USE IN TIME-DOMAIN MEMS INERTIAL SENSORS. FOR FURTHER INFORMATION CONTACT: Brian Suh, Office...

Inertial Sensor Technology for Elite Swimming Performance Analysis: A Systematic Review

PubMed Central

Mooney, Robert; Corley, Gavin; Godfrey, Alan; Quinlan, Leo R; ÓLaighin, Gearóid

2015-01-01

Technical evaluation of swimming performance is an essential factor of elite athletic preparation. Novel methods of analysis, incorporating body worn inertial sensors (i.e., Microelectromechanical systems, or MEMS, accelerometers and gyroscopes), have received much attention recently from both research and commercial communities as an alternative to video-based approaches. This technology may allow for improved analysis of stroke mechanics, race performance and energy expenditure, as well as real-time feedback to the coach, potentially enabling more efficient, competitive and quantitative coaching. The aim of this paper is to provide a systematic review of the literature related to the use of inertial sensors for the technical analysis of swimming performance. This paper focuses on providing an evaluation of the accuracy of different feature detection algorithms described in the literature for the analysis of different phases of swimming, specifically starts, turns and free-swimming. The consequences associated with different sensor attachment locations are also considered for both single and multiple sensor configurations. Additional information such as this should help practitioners to select the most appropriate systems and methods for extracting the key performance related parameters that are important to them for analysing their swimmers’ performance and may serve to inform both applied and research practices. PMID:26712760

Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning

NASA Astrophysics Data System (ADS)

Evennou, Frédéric; Marx, François

2006-12-01

This paper presents an aided dead-reckoning navigation structure and signal processing algorithms for self localization of an autonomous mobile device by fusing pedestrian dead reckoning and WiFi signal strength measurements. WiFi and inertial navigation systems (INS) are used for positioning and attitude determination in a wide range of applications. Over the last few years, a number of low-cost inertial sensors have become available. Although they exhibit large errors, WiFi measurements can be used to correct the drift weakening the navigation based on this technology. On the other hand, INS sensors can interact with the WiFi positioning system as they provide high-accuracy real-time navigation. A structure based on a Kalman filter and a particle filter is proposed. It fuses the heterogeneous information coming from those two independent technologies. Finally, the benefits of the proposed architecture are evaluated and compared with the pure WiFi and INS positioning systems.

Inertial sensor-based smoother for gait analysis.

PubMed

Suh, Young Soo

2014-12-17

An off-line smoother algorithm is proposed to estimate foot motion using an inertial sensor unit (three-axis gyroscopes and accelerometers) attached to a shoe. The smoother gives more accurate foot motion estimation than filter-based algorithms by using all of the sensor data instead of using the current sensor data. The algorithm consists of two parts. In the first part, a Kalman filter is used to obtain initial foot motion estimation. In the second part, the error in the initial estimation is compensated using a smoother, where the problem is formulated in the quadratic optimization problem. An efficient solution of the quadratic optimization problem is given using the sparse structure. Through experiments, it is shown that the proposed algorithm can estimate foot motion more accurately than a filter-based algorithm with reasonable computation time. In particular, there is significant improvement in the foot motion estimation when the foot is moving off the floor: the z-axis position error squared sum (total time: 3.47 s) when the foot is in the air is 0.0807 m2 (Kalman filter) and 0.0020 m2 (the proposed smoother).

An Inertial and Optical Sensor Fusion Approach for Six Degree-of-Freedom Pose Estimation

PubMed Central

He, Changyu; Kazanzides, Peter; Sen, Hasan Tutkun; Kim, Sungmin; Liu, Yue

2015-01-01

Optical tracking provides relatively high accuracy over a large workspace but requires line-of-sight between the camera and the markers, which may be difficult to maintain in actual applications. In contrast, inertial sensing does not require line-of-sight but is subject to drift, which may cause large cumulative errors, especially during the measurement of position. To handle cases where some or all of the markers are occluded, this paper proposes an inertial and optical sensor fusion approach in which the bias of the inertial sensors is estimated when the optical tracker provides full six degree-of-freedom (6-DOF) pose information. As long as the position of at least one marker can be tracked by the optical system, the 3-DOF position can be combined with the orientation estimated from the inertial measurements to recover the full 6-DOF pose information. When all the markers are occluded, the position tracking relies on the inertial sensors that are bias-corrected by the optical tracking system. Experiments are performed with an augmented reality head-mounted display (ARHMD) that integrates an optical tracking system (OTS) and inertial measurement unit (IMU). Experimental results show that under partial occlusion conditions, the root mean square errors (RMSE) of orientation and position are 0.04° and 0.134 mm, and under total occlusion conditions for 1 s, the orientation and position RMSE are 0.022° and 0.22 mm, respectively. Thus, the proposed sensor fusion approach can provide reliable 6-DOF pose under long-term partial occlusion and short-term total occlusion conditions. PMID:26184191

An Inertial and Optical Sensor Fusion Approach for Six Degree-of-Freedom Pose Estimation.

PubMed

He, Changyu; Kazanzides, Peter; Sen, Hasan Tutkun; Kim, Sungmin; Liu, Yue

2015-07-08

Optical tracking provides relatively high accuracy over a large workspace but requires line-of-sight between the camera and the markers, which may be difficult to maintain in actual applications. In contrast, inertial sensing does not require line-of-sight but is subject to drift, which may cause large cumulative errors, especially during the measurement of position. To handle cases where some or all of the markers are occluded, this paper proposes an inertial and optical sensor fusion approach in which the bias of the inertial sensors is estimated when the optical tracker provides full six degree-of-freedom (6-DOF) pose information. As long as the position of at least one marker can be tracked by the optical system, the 3-DOF position can be combined with the orientation estimated from the inertial measurements to recover the full 6-DOF pose information. When all the markers are occluded, the position tracking relies on the inertial sensors that are bias-corrected by the optical tracking system. Experiments are performed with an augmented reality head-mounted display (ARHMD) that integrates an optical tracking system (OTS) and inertial measurement unit (IMU). Experimental results show that under partial occlusion conditions, the root mean square errors (RMSE) of orientation and position are 0.04° and 0.134 mm, and under total occlusion conditions for 1 s, the orientation and position RMSE are 0.022° and 0.22 mm, respectively. Thus, the proposed sensor fusion approach can provide reliable 6-DOF pose under long-term partial occlusion and short-term total occlusion conditions.

Measuring joint kinematics of treadmill walking and running: Comparison between an inertial sensor based system and a camera-based system.

PubMed

Nüesch, Corina; Roos, Elena; Pagenstert, Geert; Mündermann, Annegret

2017-05-24

Inertial sensor systems are becoming increasingly popular for gait analysis because their use is simple and time efficient. This study aimed to compare joint kinematics measured by the inertial sensor system RehaGait® with those of an optoelectronic system (Vicon®) for treadmill walking and running. Additionally, the test re-test repeatability of kinematic waveforms and discrete parameters for the RehaGait® was investigated. Twenty healthy runners participated in this study. Inertial sensors and reflective markers (PlugIn Gait) were attached according to respective guidelines. The two systems were started manually at the same time. Twenty consecutive strides for walking and running were recorded and each software calculated sagittal plane ankle, knee and hip kinematics. Measurements were repeated after 20min. Ensemble means were analyzed calculating coefficients of multiple correlation for waveforms and root mean square errors (RMSE) for waveforms and discrete parameters. After correcting the offset between waveforms, the two systems/models showed good agreement with coefficients of multiple correlation above 0.950 for walking and running. RMSE of the waveforms were below 5° for walking and below 8° for running. RMSE for ranges of motion were between 4° and 9° for walking and running. Repeatability analysis of waveforms showed very good to excellent coefficients of multiple correlation (>0.937) and RMSE of 3° for walking and 3-7° for running. These results indicate that in healthy subjects sagittal plane joint kinematics measured with the RehaGait® are comparable to those using a Vicon® system/model and that the measured kinematics have a good repeatability, especially for walking. Copyright © 2017 Elsevier Ltd. All rights reserved.

Strapdown cost trend study and forecast

NASA Technical Reports Server (NTRS)

Eberlein, A. J.; Savage, P. G.

1975-01-01

The potential cost advantages offered by advanced strapdown inertial technology in future commercial short-haul aircraft are summarized. The initial procurement cost and six year cost-of-ownership, which includes spares and direct maintenance cost were calculated for kinematic and inertial navigation systems such that traditional and strapdown mechanization costs could be compared. Cost results for the inertial navigation systems showed that initial costs and the cost of ownership for traditional triple redundant gimbaled inertial navigators are three times the cost of the equivalent skewed redundant strapdown inertial navigator. The net cost advantage for the strapdown kinematic system is directly attributable to the reduction in sensor count for strapdown. The strapdown kinematic system has the added advantage of providing a fail-operational inertial navigation capability for no additional cost due to the use of inertial grade sensors and attitude reference computers.

Turbulence Measurements from Compliant Moorings. Part II: Motion Correction

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

Kilcher, Levi F.; Thomson, Jim; Harding, Samuel

2017-06-01

Acoustic Doppler velocimeters (ADVs) are a valuable tool for making highprecision measurements of turbulence, and moorings are a convenient and ubiquitous platform for making many kinds of measurements in the ocean. However—because of concerns that mooring motion can contaminate turbulence measurements and acoustic Doppler profilers are relatively easy to deploy—ADVs are not frequently deployed from moorings. This work details a method for measuring turbulence using moored ADVs that corrects for mooring motion using measurements from inertial motion sensors. Three distinct mooring platforms were deployed in a tidal channel with inertial motion-sensor-equipped ADVs. In each case, the motion correction based onmore » the inertial measurements dramatically reduced contamination from mooring motion. The spectra from these measurements have a shape that is consistent with other measurements in tidal channels, and have a f^(5/3) slope at high frequencies—consistent with Kolmogorov’s theory of isotropic turbulence. Motion correction also improves estimates of cross-spectra and Reynold’s stresses. Comparison of turbulence dissipation with flow speed and turbulence production indicates a bottom boundary layer production-dissipation balance during ebb and flood that is consistent with the strong tidal forcing at the site. These results indicate that inertial-motion-sensor-equipped ADVs are a valuable new tool for measuring turbulence from moorings.« less

Assessing the Performance of Sensor Fusion Methods: Application to Magnetic-Inertial-Based Human Body Tracking.

PubMed

Ligorio, Gabriele; Bergamini, Elena; Pasciuto, Ilaria; Vannozzi, Giuseppe; Cappozzo, Aurelio; Sabatini, Angelo Maria

2016-01-26

Information from complementary and redundant sensors are often combined within sensor fusion algorithms to obtain a single accurate observation of the system at hand. However, measurements from each sensor are characterized by uncertainties. When multiple data are fused, it is often unclear how all these uncertainties interact and influence the overall performance of the sensor fusion algorithm. To address this issue, a benchmarking procedure is presented, where simulated and real data are combined in different scenarios in order to quantify how each sensor's uncertainties influence the accuracy of the final result. The proposed procedure was applied to the estimation of the pelvis orientation using a waist-worn magnetic-inertial measurement unit. Ground-truth data were obtained from a stereophotogrammetric system and used to obtain simulated data. Two Kalman-based sensor fusion algorithms were submitted to the proposed benchmarking procedure. For the considered application, gyroscope uncertainties proved to be the main error source in orientation estimation accuracy for both tested algorithms. Moreover, although different performances were obtained using simulated data, these differences became negligible when real data were considered. The outcome of this evaluation may be useful both to improve the design of new sensor fusion methods and to drive the algorithm tuning process.

General test plan redundant sensor strapdown IMU evaluation program

NASA Technical Reports Server (NTRS)

Hartwell, T.; Irwin, H. A.; Miyatake, Y.; Wedekind, D. E.

1971-01-01

The general test plan for a redundant sensor strapdown inertial measuring unit evaluation program is presented. The inertial unit contains six gyros and three orthogonal accelerometers. The software incorporates failure detection and correction logic and a land vehicle navigation program. The principal objective of the test is a demonstration of the practicability, reliability, and performance of the inertial measuring unit with failure detection and correction in operational environments.

Avatar - a multi-sensory system for real time body position monitoring.

PubMed

Jovanov, E; Hanish, N; Courson, V; Stidham, J; Stinson, H; Webb, C; Denny, K

2009-01-01

Virtual reality and computer assisted physical rehabilitation applications require an unobtrusive and inexpensive real time monitoring systems. Existing systems are usually complex and expensive and based on infrared monitoring. In this paper we propose Avatar, a hybrid system consisting of off-the-shelf components and sensors. Absolute positioning of a few reference points is determined using infrared diode on subject's body and a set of Wii Remotes as optical sensors. Individual body segments are monitored by intelligent inertial sensor nodes iSense. A network of inertial nodes is controlled by a master node that serves as a gateway for communication with a capture device. Each sensor features a 3D accelerometer and a 2 axis gyroscope. Avatar system is used for control of avatars in Virtual Reality applications, but could be used in a variety of augmented reality, gaming, and computer assisted physical rehabilitation applications.

Indoor localization using pedestrian dead reckoning updated with RFID-based fiducials.

PubMed

House, Samuel; Connell, Sean; Milligan, Ian; Austin, Daniel; Hayes, Tamara L; Chiang, Patrick

2011-01-01

We describe a low-cost wearable system that tracks the location of individuals indoors using commonly available inertial navigation sensors fused with radio frequency identification (RFID) tags placed around the smart environment. While conventional pedestrian dead reckoning (PDR) calculated with an inertial measurement unit (IMU) is susceptible to sensor drift inaccuracies, the proposed wearable prototype fuses the drift-sensitive IMU with a RFID tag reader. Passive RFID tags placed throughout the smart-building then act as fiducial markers that update the physical locations of each user, thereby correcting positional errors and sensor inaccuracy. Experimental measurements taken for a 55 m × 20 m 2D floor space indicate an over 1200% improvement in average error rate of the proposed RFID-fused system over dead reckoning alone.

Effectiveness of Variable-Gain Kalman Filter Based on Angle Error Calculated from Acceleration Signals in Lower Limb Angle Measurement with Inertial Sensors

PubMed Central

Watanabe, Takashi

2013-01-01

The wearable sensor system developed by our group, which measured lower limb angles using Kalman-filtering-based method, was suggested to be useful in evaluation of gait function for rehabilitation support. However, it was expected to reduce variations of measurement errors. In this paper, a variable-Kalman-gain method based on angle error that was calculated from acceleration signals was proposed to improve measurement accuracy. The proposed method was tested comparing to fixed-gain Kalman filter and a variable-Kalman-gain method that was based on acceleration magnitude used in previous studies. First, in angle measurement in treadmill walking, the proposed method measured lower limb angles with the highest measurement accuracy and improved significantly foot inclination angle measurement, while it improved slightly shank and thigh inclination angles. The variable-gain method based on acceleration magnitude was not effective for our Kalman filter system. Then, in angle measurement of a rigid body model, it was shown that the proposed method had measurement accuracy similar to or higher than results seen in other studies that used markers of camera-based motion measurement system fixing on a rigid plate together with a sensor or on the sensor directly. The proposed method was found to be effective in angle measurement with inertial sensors. PMID:24282442

Assessing the Performance of Sensor Fusion Methods: Application to Magnetic-Inertial-Based Human Body Tracking

PubMed Central

Ligorio, Gabriele; Bergamini, Elena; Pasciuto, Ilaria; Vannozzi, Giuseppe; Cappozzo, Aurelio; Sabatini, Angelo Maria

2016-01-01

Information from complementary and redundant sensors are often combined within sensor fusion algorithms to obtain a single accurate observation of the system at hand. However, measurements from each sensor are characterized by uncertainties. When multiple data are fused, it is often unclear how all these uncertainties interact and influence the overall performance of the sensor fusion algorithm. To address this issue, a benchmarking procedure is presented, where simulated and real data are combined in different scenarios in order to quantify how each sensor’s uncertainties influence the accuracy of the final result. The proposed procedure was applied to the estimation of the pelvis orientation using a waist-worn magnetic-inertial measurement unit. Ground-truth data were obtained from a stereophotogrammetric system and used to obtain simulated data. Two Kalman-based sensor fusion algorithms were submitted to the proposed benchmarking procedure. For the considered application, gyroscope uncertainties proved to be the main error source in orientation estimation accuracy for both tested algorithms. Moreover, although different performances were obtained using simulated data, these differences became negligible when real data were considered. The outcome of this evaluation may be useful both to improve the design of new sensor fusion methods and to drive the algorithm tuning process. PMID:26821027

Flying over uneven moving terrain based on optic-flow cues without any need for reference frames or accelerometers.

PubMed

Expert, Fabien; Ruffier, Franck

2015-02-26

Two bio-inspired guidance principles involving no reference frame are presented here and were implemented in a rotorcraft, which was equipped with panoramic optic flow (OF) sensors but (as in flying insects) no accelerometer. To test these two guidance principles, we built a tethered tandem rotorcraft called BeeRotor (80 grams), which was tested flying along a high-roofed tunnel. The aerial robot adjusts its pitch and hence its speed, hugs the ground and lands safely without any need for an inertial reference frame. The rotorcraft's altitude and forward speed are adjusted via two OF regulators piloting the lift and the pitch angle on the basis of the common-mode and differential rotor speeds, respectively. The robot equipped with two wide-field OF sensors was tested in order to assess the performances of the following two systems of guidance involving no inertial reference frame: (i) a system with a fixed eye orientation based on the curved artificial compound eye (CurvACE) sensor, and (ii) an active system of reorientation based on a quasi-panoramic eye which constantly realigns its gaze, keeping it parallel to the nearest surface followed. Safe automatic terrain following and landing were obtained with CurvACE under dim light to daylight conditions and the active eye-reorientation system over rugged, changing terrain, without any need for an inertial reference frame.

Ground Based Investigation of Electrostatic Accelerometer in HUST

NASA Astrophysics Data System (ADS)

Bai, Y.; Zhou, Z.

2013-12-01

High-precision electrostatic accelerometers with six degrees of freedom (DOF) acceleration measurement were successfully used in CHAMP, GRACE and GOCE missions which to measure the Earth's gravity field. In our group, space inertial sensor based on the capacitance transducer and electrostatic control technique has been investigated for test of equivalence principle (TEPO), searching non-Newtonian force in micrometer range, and satellite Earth's field recovery. The significant techniques of capacitive position sensor with the noise level at 2×10-7pF/Hz1/2 and the μV/Hz1/2 level electrostatic actuator are carried out and all the six servo loop controls by using a discrete PID algorithm are realized in a FPGA device. For testing on ground, in order to compensate one g earth's gravity, the fiber torsion pendulum facility is adopt to measure the parameters of the electrostatic controlled inertial sensor such as the resolution, and the electrostatic stiffness, the cross couple between different DOFs. A short distance and a simple double capsule equipment the valid duration about 0.5 second is set up in our lab for the free fall tests of the engineering model which can directly verify the function of six DOF control. Meanwhile, high voltage suspension method is also realized and preliminary results show that the horizontal axis of acceleration noise is about 10-8m/s2/Hz1/2 level which limited mainly by the seismic noise. Reference: [1] Fen Gao, Ze-Bing Zhou, Jun Luo, Feasibility for Testing the Equivalence Principle with Optical Readout in Space, Chin. Phys. Lett. 28(8) (2011) 080401. [2] Z. Zhu, Z. B. Zhou, L. Cai, Y. Z. Bai, J. Luo, Electrostatic gravity gradiometer design for the advanced GOCE mission, Adv. Sp. Res. 51 (2013) 2269-2276. [3] Z B Zhou, L Liu, H B Tu, Y Z Bai, J Luo, Seismic noise limit for ground-based performance measurements of an inertial sensor using a torsion balance, Class. Quantum Grav. 27 (2010) 175012. [4] H B Tu, Y Z Bai, Z B Zhou, L Liu, L Cai, and J Luo, Performance measurements of an inertial sensor with a two-stage controlled torsion pendulum, Class Quantum. Grav. 27 (2010) 205016.

Autonomous Quality Control of Joint Orientation Measured with Inertial Sensors.

PubMed

Lebel, Karina; Boissy, Patrick; Nguyen, Hung; Duval, Christian

2016-07-05

Clinical mobility assessment is traditionally performed in laboratories using complex and expensive equipment. The low accessibility to such equipment, combined with the emerging trend to assess mobility in a free-living environment, creates a need for body-worn sensors (e.g., inertial measurement units-IMUs) that are capable of measuring the complexity in motor performance using meaningful measurements, such as joint orientation. However, accuracy of joint orientation estimates using IMUs may be affected by environment, the joint tracked, type of motion performed and velocity. This study investigates a quality control (QC) process to assess the quality of orientation data based on features extracted from the raw inertial sensors' signals. Joint orientation (trunk, hip, knee, ankle) of twenty participants was acquired by an optical motion capture system and IMUs during a variety of tasks (sit, sit-to-stand transition, walking, turning) performed under varying conditions (speed, environment). An artificial neural network was used to classify good and bad sequences of joint orientation with a sensitivity and a specificity above 83%. This study confirms the possibility to perform QC on IMU joint orientation data based on raw signal features. This innovative QC approach may be of particular interest in a big data context, such as for remote-monitoring of patients' mobility.

Wearable inertial sensors in swimming motion analysis: a systematic review.

PubMed

de Magalhaes, Fabricio Anicio; Vannozzi, Giuseppe; Gatta, Giorgio; Fantozzi, Silvia

2015-01-01

The use of contemporary technology is widely recognised as a key tool for enhancing competitive performance in swimming. Video analysis is traditionally used by coaches to acquire reliable biomechanical data about swimming performance; however, this approach requires a huge computational effort, thus introducing a delay in providing quantitative information. Inertial and magnetic sensors, including accelerometers, gyroscopes and magnetometers, have been recently introduced to assess the biomechanics of swimming performance. Research in this field has attracted a great deal of interest in the last decade due to the gradual improvement of the performance of sensors and the decreasing cost of miniaturised wearable devices. With the aim of describing the state of the art of current developments in this area, a systematic review of the existing methods was performed using the following databases: PubMed, ISI Web of Knowledge, IEEE Xplore, Google Scholar, Scopus and Science Direct. Twenty-seven articles published in indexed journals and conference proceedings, focusing on the biomechanical analysis of swimming by means of inertial sensors were reviewed. The articles were categorised according to sensor's specification, anatomical sites where the sensors were attached, experimental design and applications for the analysis of swimming performance. Results indicate that inertial sensors are reliable tools for swimming biomechanical analyses.

Sampling and Control Circuit Board for an Inertial Measurement Unit

NASA Technical Reports Server (NTRS)

Chelmins, David T (Inventor); Sands, Obed (Inventor); Powis, Richard T., Jr. (Inventor)

2016-01-01

A circuit board that serves as a control and sampling interface to an inertial measurement unit ("IMU") is provided. The circuit board is also configured to interface with a local oscillator and an external trigger pulse. The circuit board is further configured to receive the external trigger pulse from an external source that time aligns the local oscillator and initiates sampling of the inertial measurement device for data at precise time intervals based on pulses from the local oscillator. The sampled data may be synchronized by the circuit board with other sensors of a navigation system via the trigger pulse.

Design and flight test of a differential GPS/inertial navigation system for approach/landing guidance

NASA Technical Reports Server (NTRS)

Vallot, Lawrence; Snyder, Scott; Schipper, Brian; Parker, Nigel; Spitzer, Cary

1991-01-01

NASA-Langley has conducted a flight test program evaluating a differential GPS/inertial navigation system's (DGPS/INS) utility as an approach/landing aid. The DGPS/INS airborne and ground components are based on off-the-shelf transport aircraft avionics, namely a global positioning/inertial reference unit (GPIRU) and two GPS sensor units (GPSSUs). Systematic GPS errors are measured by the ground GPSSU and transmitted to the aircraft GPIRU, allowing the errors to be eliminated or greatly reduced in the airborne equipment. Over 120 landings were flown; 36 of these were fully automatic DGPS/INS landings.

Investigating the Effects of Magnetic Variations on Inertial/Magnetic Orientation Sensors

DTIC Science & Technology

2007-09-01

caused by test objects, a track was constructed using nonferrous materials and set so that the orientation of an inertial/magnetic sensor module...states ◆ metal filing cabinet ◆ mobile robot, unpowered, powered, and motor engaged. The MicroStrain 3DM-G sensor module is factory calibrated and...triad of the sensor module approached a large metal filing cabinet. The deviations for this test object are the largest of any observed in the

The instantaneous linear motion information measurement method based on inertial sensors for ships

NASA Astrophysics Data System (ADS)

Yang, Xu; Huang, Jing; Gao, Chen; Quan, Wei; Li, Ming; Zhang, Yanshun

2018-05-01

Ship instantaneous line motion information is the important foundation for ship control, which needs to be measured accurately. For this purpose, an instantaneous line motion measurement method based on inertial sensors is put forward for ships. By introducing a half-fixed coordinate system to realize the separation between instantaneous line motion and ship master movement, the instantaneous line motion acceleration of ships can be obtained with higher accuracy. Then, the digital high-pass filter is applied to suppress the velocity error caused by the low frequency signal such as schuler period. Finally, the instantaneous linear motion displacement of ships can be measured accurately. Simulation experimental results show that the method is reliable and effective, and can realize the precise measurement of velocity and displacement of instantaneous line motion for ships.

Lumbar joint torque estimation based on simplified motion measurement using multiple inertial sensors.

PubMed

Miyajima, Saori; Tanaka, Takayuki; Imamura, Yumeko; Kusaka, Takashi

2015-01-01

We estimate lumbar torque based on motion measurement using only three inertial sensors. First, human motion is measured by a 6-axis motion tracking device that combines a 3-axis accelerometer and a 3-axis gyroscope placed on the shank, thigh, and back. Next, the lumbar joint torque during the motion is estimated by kinematic musculoskeletal simulation. The conventional method for estimating joint torque uses full body motion data measured by an optical motion capture system. However, in this research, joint torque is estimated by using only three link angles of the body, thigh, and shank. The utility of our method was verified by experiments. We measured motion of bendung knee and waist simultaneously. As the result, we were able to estimate the lumbar joint torque from measured motion.

Keeping a Good Attitude: A Quaternion-Based Orientation Filter for IMUs and MARGs

PubMed Central

Valenti, Roberto G.; Dryanovski, Ivan; Xiao, Jizhong

2015-01-01

Orientation estimation using low cost sensors is an important task for Micro Aerial Vehicles (MAVs) in order to obtain a good feedback for the attitude controller. The challenges come from the low accuracy and noisy data of the MicroElectroMechanical System (MEMS) technology, which is the basis of modern, miniaturized inertial sensors. In this article, we describe a novel approach to obtain an estimation of the orientation in quaternion form from the observations of gravity and magnetic field. Our approach provides a quaternion estimation as the algebraic solution of a system from inertial/magnetic observations. We separate the problems of finding the “tilt” quaternion and the heading quaternion in two sub-parts of our system. This procedure is the key for avoiding the impact of the magnetic disturbances on the roll and pitch components of the orientation when the sensor is surrounded by unwanted magnetic flux. We demonstrate the validity of our method first analytically and then empirically using simulated data. We propose a novel complementary filter for MAVs that fuses together gyroscope data with accelerometer and magnetic field readings. The correction part of the filter is based on the method described above and works for both IMU (Inertial Measurement Unit) and MARG (Magnetic, Angular Rate, and Gravity) sensors. We evaluate the effectiveness of the filter and show that it significantly outperforms other common methods, using publicly available datasets with ground-truth data recorded during a real flight experiment of a micro quadrotor helicopter. PMID:26258778

Keeping a Good Attitude: A Quaternion-Based Orientation Filter for IMUs and MARGs.

PubMed

Valenti, Roberto G; Dryanovski, Ivan; Xiao, Jizhong

2015-08-06

Orientation estimation using low cost sensors is an important task for Micro Aerial Vehicles (MAVs) in order to obtain a good feedback for the attitude controller. The challenges come from the low accuracy and noisy data of the MicroElectroMechanical System (MEMS) technology, which is the basis of modern, miniaturized inertial sensors. In this article, we describe a novel approach to obtain an estimation of the orientation in quaternion form from the observations of gravity and magnetic field. Our approach provides a quaternion estimation as the algebraic solution of a system from inertial/magnetic observations. We separate the problems of finding the "tilt" quaternion and the heading quaternion in two sub-parts of our system. This procedure is the key for avoiding the impact of the magnetic disturbances on the roll and pitch components of the orientation when the sensor is surrounded by unwanted magnetic flux. We demonstrate the validity of our method first analytically and then empirically using simulated data. We propose a novel complementary filter for MAVs that fuses together gyroscope data with accelerometer and magnetic field readings. The correction part of the filter is based on the method described above and works for both IMU (Inertial Measurement Unit) and MARG (Magnetic, Angular Rate, and Gravity) sensors. We evaluate the effectiveness of the filter and show that it significantly outperforms other common methods, using publicly available datasets with ground-truth data recorded during a real flight experiment of a micro quadrotor helicopter.

A new calibration methodology for thorax and upper limbs motion capture in children using magneto and inertial sensors.

PubMed

Ricci, Luca; Formica, Domenico; Sparaci, Laura; Lasorsa, Francesca Romana; Taffoni, Fabrizio; Tamilia, Eleonora; Guglielmelli, Eugenio

2014-01-09

Recent advances in wearable sensor technologies for motion capture have produced devices, mainly based on magneto and inertial measurement units (M-IMU), that are now suitable for out-of-the-lab use with children. In fact, the reduced size, weight and the wireless connectivity meet the requirement of minimum obtrusivity and give scientists the possibility to analyze children's motion in daily life contexts. Typical use of magneto and inertial measurement units (M-IMU) motion capture systems is based on attaching a sensing unit to each body segment of interest. The correct use of this setup requires a specific calibration methodology that allows mapping measurements from the sensors' frames of reference into useful kinematic information in the human limbs' frames of reference. The present work addresses this specific issue, presenting a calibration protocol to capture the kinematics of the upper limbs and thorax in typically developing (TD) children. The proposed method allows the construction, on each body segment, of a meaningful system of coordinates that are representative of real physiological motions and that are referred to as functional frames (FFs). We will also present a novel cost function for the Levenberg-Marquardt algorithm, to retrieve the rotation matrices between each sensor frame (SF) and the corresponding FF. Reported results on a group of 40 children suggest that the method is repeatable and reliable, opening the way to the extensive use of this technology for out-of-the-lab motion capture in children.

PDR with a Foot-Mounted IMU and Ramp Detection

PubMed Central

Jiménez, Antonio R.; Seco, Fernando; Zampella, Francisco; Prieto, José C.; Guevara, Jorge

2011-01-01

The localization of persons in indoor environments is nowadays an open problem. There are partial solutions based on the deployment of a network of sensors (Local Positioning Systems or LPS). Other solutions only require the installation of an inertial sensor on the person’s body (Pedestrian Dead-Reckoning or PDR). PDR solutions integrate the signals coming from an Inertial Measurement Unit (IMU), which usually contains 3 accelerometers and 3 gyroscopes. The main problem of PDR is the accumulation of positioning errors due to the drift caused by the noise in the sensors. This paper presents a PDR solution that incorporates a drift correction method based on detecting the access ramps usually found in buildings. The ramp correction method is implemented over a PDR framework that uses an Inertial Navigation algorithm (INS) and an IMU attached to the person’s foot. Unlike other approaches that use external sensors to correct the drift error, we only use one IMU on the foot. To detect a ramp, the slope of the terrain on which the user is walking, and the change in height sensed when moving forward, are estimated from the IMU. After detection, the ramp is checked for association with one of the existing in a database. For each associated ramp, a position correction is fed into the Kalman Filter in order to refine the INS-PDR solution. Drift-free localization is achieved with positioning errors below 2 meters for 1,000-meter-long routes in a building with a few ramps. PMID:22163701

An Investigation of the Dynamic Response of a Seismically Stable Platform

DTIC Science & Technology

1982-08-01

PAD. The controls on the -9system are of two types. A low frequency tilt control, with a 10 arc second sensitivity, 2-axis tiltmeter as sensor ...Inertial Sensors Structural Analysis Holloman AFB, NiM. Support to this effort includes structural analyses toward active servo frequency band. This report...controlled to maintain a null position of a sensitive height sensor . The 6-degree-of- freedom high frequency controls are based on seismometers as sensors

Design issues for LISA inertial sensors

NASA Astrophysics Data System (ADS)

Vitale, Stefano; Speake, Clive

1998-12-01

In this paper we discuss a few design issues of the inertial sensor for LISA. These issues include the role of the stiffness and the losses that are introduced by the readout and by other parasitic sources. A possible plan for testing those effects on ground is also discussed.

Disability and Fatigue Can Be Objectively Measured in Multiple Sclerosis.

PubMed

Motta, Caterina; Palermo, Eduardo; Studer, Valeria; Germanotta, Marco; Germani, Giorgio; Centonze, Diego; Cappa, Paolo; Rossi, Silvia; Rossi, Stefano

2016-01-01

The available clinical outcome measures of disability in multiple sclerosis are not adequately responsive or sensitive. To investigate the feasibility of inertial sensor-based gait analysis in multiple sclerosis. A cross-sectional study of 80 multiple sclerosis patients and 50 healthy controls was performed. Lower-limb kinematics was evaluated by using a commercially available magnetic inertial measurement unit system. Mean and standard deviation of range of motion (mROM, sROM) for each joint of lower limbs were calculated in one minute walking test. A motor performance index (E) defined as the sum of sROMs was proposed. We established two novel observer-independent measures of disability. Hip mROM was extremely sensitive in measuring lower limb motor impairment, being correlated with muscle strength and also altered in patients without clinically detectable disability. On the other hand, E index discriminated patients according to disability, being altered only in patients with moderate and severe disability, regardless of walking speed. It was strongly correlated with fatigue and patient-perceived health status. Inertial sensor-based gait analysis is feasible and can detect clinical and subclinical disability in multiple sclerosis.

Use of a wireless, inertial sensor-based system to objectively evaluate flexion tests in the horse.

PubMed

Marshall, J F; Lund, D G; Voute, L C

2012-12-01

A wireless, inertial sensor-based system has previously been validated for evaluation of equine lameness. However, threshold values have not been determined for the assessment of responses to flexion tests. The aim of this investigation was to evaluate a sensor-based system for objective assessment of the response to flexion. Healthy adult horses (n = 17) in work were recruited prospectively. Horses were instrumented with sensors on the head (accelerometer), pelvis (accelerometer) and right forelimb (gyroscope), before trotting in a straight line (minimum 25 strides) for 2 consecutive trials. Sensors measured 1) vertical pelvic movement asymmetry (PMA) for both right and left hindlimb strides and 2) average difference in maximum and minimum pelvic height (PDMax and PDMin) between right and left hindlimb strides in millimetres. A hindlimb was randomly selected for proximal flexion (60 s), after which the horse trotted a minimum of 10 strides. Response to flexion was blindly assessed as negative or positive by an experienced observer. Changes in PMA, PDMax and PDMin between baseline and flexion examinations were calculated for each test. Statistical analysis consisted of a Pearson's product moment test and linear regression on baseline trials, Mann-Whitney rank sum test for effect of flexion and receiver operator curve (ROC) analysis of test parameters. There was a strong correlation between trials for PMA, PDMin and PDMax measurements (P < 0.001). A positive flexion test resulted in a significant increase in PMA (P = 0.021) and PDMax (P = 0.05) only. Receiver-operator curve analysis established cut-off values for change in PMA and PDMax of 0.068 and 4.47 mm, respectively (sensitivity = 0.71, specificity = 0.65) to indicate a positive response to flexion. A positive response to flexion resulted in significant changes to objective measurements of pelvic symmetry. Findings support the use of inertial sensor systems to objectively assess response to flexion tests. Further investigation is warranted to establish cut-off values for objective assessment of other diagnostic procedures.

Balance Improvement Effects of Biofeedback Systems with State-of-the-Art Wearable Sensors: A Systematic Review.

PubMed

Ma, Christina Zong-Hao; Wong, Duo Wai-Chi; Lam, Wing Kai; Wan, Anson Hong-Ping; Lee, Winson Chiu-Chun

2016-03-25

Falls and fall-induced injuries are major global public health problems. Balance and gait disorders have been the second leading cause of falls. Inertial motion sensors and force sensors have been widely used to monitor both static and dynamic balance performance. Based on the detected performance, instant visual, auditory, electrotactile and vibrotactile biofeedback could be provided to augment the somatosensory input and enhance balance control. This review aims to synthesize the research examining the effect of biofeedback systems, with wearable inertial motion sensors and force sensors, on balance performance. Randomized and non-randomized clinical trials were included in this review. All studies were evaluated based on the methodological quality. Sample characteristics, device design and study characteristics were summarized. Most previous studies suggested that biofeedback devices were effective in enhancing static and dynamic balance in healthy young and older adults, and patients with balance and gait disorders. Attention should be paid to the choice of appropriate types of sensors and biofeedback for different intended purposes. Maximizing the computing capacity of the micro-processer, while minimizing the size of the electronic components, appears to be the future direction of optimizing the devices. Wearable balance-improving devices have their potential of serving as balance aids in daily life, which can be used indoors and outdoors.

Balance Improvement Effects of Biofeedback Systems with State-of-the-Art Wearable Sensors: A Systematic Review

PubMed Central

Ma, Christina Zong-Hao; Wong, Duo Wai-Chi; Lam, Wing Kai; Wan, Anson Hong-Ping; Lee, Winson Chiu-Chun

2016-01-01

Falls and fall-induced injuries are major global public health problems. Balance and gait disorders have been the second leading cause of falls. Inertial motion sensors and force sensors have been widely used to monitor both static and dynamic balance performance. Based on the detected performance, instant visual, auditory, electrotactile and vibrotactile biofeedback could be provided to augment the somatosensory input and enhance balance control. This review aims to synthesize the research examining the effect of biofeedback systems, with wearable inertial motion sensors and force sensors, on balance performance. Randomized and non-randomized clinical trials were included in this review. All studies were evaluated based on the methodological quality. Sample characteristics, device design and study characteristics were summarized. Most previous studies suggested that biofeedback devices were effective in enhancing static and dynamic balance in healthy young and older adults, and patients with balance and gait disorders. Attention should be paid to the choice of appropriate types of sensors and biofeedback for different intended purposes. Maximizing the computing capacity of the micro-processer, while minimizing the size of the electronic components, appears to be the future direction of optimizing the devices. Wearable balance-improving devices have their potential of serving as balance aids in daily life, which can be used indoors and outdoors. PMID:27023558

Design of an Inertial-Sensor-Based Data Glove for Hand Function Evaluation.

PubMed

Lin, Bor-Shing; Lee, I-Jung; Yang, Shu-Yu; Lo, Yi-Chiang; Lee, Junghsi; Chen, Jean-Lon

2018-05-13

Capturing hand motions for hand function evaluations is essential in the medical field. Various data gloves have been developed for rehabilitation and manual dexterity assessments. This study proposed a modular data glove with 9-axis inertial measurement units (IMUs) to obtain static and dynamic parameters during hand function evaluation. A sensor fusion algorithm is used to calculate the range of motion of joints. The data glove is designed to have low cost, easy wearability, and high reliability. Owing to the modular design, the IMU board is independent and extensible and can be used with various microcontrollers to realize more medical applications. This design greatly enhances the stability and maintainability of the glove.

Fusion of Low-Cost Imaging and Inertial Sensors for Navigation

DTIC Science & Technology

2007-01-01

an Integrated GPS/MEMS Inertial Navigation Pack- age. In Proceedings of ION GNSS 2004, pp. 825–832, September 2004. [3] R. G. Brown and P. Y. Hwang ...track- ing, with no a priori knowledge is provided in [13]. An on- line (Extended Kalman Filter-based) method for calculat- ing a trajectory by tracking...transformation, effectively constraining the resulting correspondence search space. The algorithm was incorporated into an extended Kalman filter and

Inertial Survey Application to Civil Works,

DTIC Science & Technology

1983-01-01

closer together the ZUPTS must be performed. ZUPTS are used by the system to provide external information to the error control system used (Kalman...the best estimate of the system states. Accuracy of the system is increased when the sensor information from the inertial platform is compared with the...building a new version of its Auto-Surveyor System to be known as LASS II. This version will be based on the production model of the PADS presently

Estimation of end point foot clearance points from inertial sensor data.

PubMed

Santhiranayagam, Braveena K; Lai, Daniel T H; Begg, Rezaul K; Palaniswami, Marimuthu

2011-01-01

Foot clearance parameters provide useful insight into tripping risks during walking. This paper proposes a technique for the estimate of key foot clearance parameters using inertial sensor (accelerometers and gyroscopes) data. Fifteen features were extracted from raw inertial sensor measurements, and a regression model was used to estimate two key foot clearance parameters: First maximum vertical clearance (m x 1) after toe-off and the Minimum Toe Clearance (MTC) of the swing foot. Comparisons are made against measurements obtained using an optoelectronic motion capture system (Optotrak), at 4 different walking speeds. General Regression Neural Networks (GRNN) were used to estimate the desired parameters from the sensor features. Eight subjects foot clearance data were examined and a Leave-one-subject-out (LOSO) method was used to select the best model. The best average Root Mean Square Errors (RMSE) across all subjects obtained using all sensor features at the maximum speed for m x 1 was 5.32 mm and for MTC was 4.04 mm. Further application of a hill-climbing feature selection technique resulted in 0.54-21.93% improvement in RMSE and required fewer input features. The results demonstrated that using raw inertial sensor data with regression models and feature selection could accurately estimate key foot clearance parameters.

Development of a Locomotion Interface for Portable Virtual Environment Systems Using an Inertial/Magnetic Sensor-Based System and a Ranging Measurement System

DTIC Science & Technology

2014-03-01

56 1. Motivation ...83 1. Motivation ...........................................................................................83 2. Environment Requirements...ENVIRONMENT SYSTEMS ......................................................97 A. BACKGROUND AND MOTIVATION

Inertial Sensor-Based Motion Analysis of Lower Limbs for Rehabilitation Treatments

PubMed Central

Sun, Tongyang; Duan, Lihong; Wang, Yulong

2017-01-01

The hemiplegic rehabilitation state diagnosing performed by therapists can be biased due to their subjective experience, which may deteriorate the rehabilitation effect. In order to improve this situation, a quantitative evaluation is proposed. Though many motion analysis systems are available, they are too complicated for practical application by therapists. In this paper, a method for detecting the motion of human lower limbs including all degrees of freedom (DOFs) via the inertial sensors is proposed, which permits analyzing the patient's motion ability. This method is applicable to arbitrary walking directions and tracks of persons under study, and its results are unbiased, as compared to therapist qualitative estimations. Using the simplified mathematical model of a human body, the rotation angles for each lower limb joint are calculated from the input signals acquired by the inertial sensors. Finally, the rotation angle versus joint displacement curves are constructed, and the estimated values of joint motion angle and motion ability are obtained. The experimental verification of the proposed motion detection and analysis method was performed, which proved that it can efficiently detect the differences between motion behaviors of disabled and healthy persons and provide a reliable quantitative evaluation of the rehabilitation state. PMID:29065575

Investigation of Electrostatic Accelerometer in HUST for Space Science Missions

NASA Astrophysics Data System (ADS)

Bai, Yanzheng; Hu, Ming; Li, Gui; Liu, Li; Qu, Shaobo; Wu, Shuchao; Zhou, Zebing

2014-05-01

High-precision electrostatic accelerometers are significant payload in CHAMP, GRACE and GOCE gravity missions to measure the non-gravitational forces. In our group, space electrostatic accelerometer and inertial sensor based on the capacitive sensors and electrostatic control technique has been investigated for space science research in China such as testing of equivalence principle (TEPO), searching non-Newtonian force in micrometer range, satellite Earth's field recovery and so on. In our group, a capacitive position sensor with a resolution of 10-7pF/Hz1/2 and the μV/Hz1/2 level electrostatic actuator are developed. The fiber torsion pendulum facility is adopt to measure the parameters of the electrostatic controlled inertial sensor such as the resolution, and the electrostatic stiffness, the cross couple between different DOFs. Meanwhile, high voltage suspension and free fall methods are applied to verify the function of electrostatic accelerometer. Last, the engineering model of electrostatic accelerometer has been developed and tested successfully in space and preliminary results are present.

High accuracy navigation information estimation for inertial system using the multi-model EKF fusing adams explicit formula applied to underwater gliders.

PubMed

Huang, Haoqian; Chen, Xiyuan; Zhang, Bo; Wang, Jian

2017-01-01

The underwater navigation system, mainly consisting of MEMS inertial sensors, is a key technology for the wide application of underwater gliders and plays an important role in achieving high accuracy navigation and positioning for a long time of period. However, the navigation errors will accumulate over time because of the inherent errors of inertial sensors, especially for MEMS grade IMU (Inertial Measurement Unit) generally used in gliders. The dead reckoning module is added to compensate the errors. In the complicated underwater environment, the performance of MEMS sensors is degraded sharply and the errors will become much larger. It is difficult to establish the accurate and fixed error model for the inertial sensor. Therefore, it is very hard to improve the accuracy of navigation information calculated by sensors. In order to solve the problem mentioned, the more suitable filter which integrates the multi-model method with an EKF approach can be designed according to different error models to give the optimal estimation for the state. The key parameters of error models can be used to determine the corresponding filter. The Adams explicit formula which has an advantage of high precision prediction is simultaneously fused into the above filter to achieve the much more improvement in attitudes estimation accuracy. The proposed algorithm has been proved through theory analyses and has been tested by both vehicle experiments and lake trials. Results show that the proposed method has better accuracy and effectiveness in terms of attitudes estimation compared with other methods mentioned in the paper for inertial navigation applied to underwater gliders. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

An enhanced inertial navigation system based on a low-cost IMU and laser scanner

NASA Astrophysics Data System (ADS)

Kim, Hyung-Soon; Baeg, Seung-Ho; Yang, Kwang-Woong; Cho, Kuk; Park, Sangdeok

2012-06-01

This paper describes an enhanced fusion method for an Inertial Navigation System (INS) based on a 3-axis accelerometer sensor, a 3-axis gyroscope sensor and a laser scanner. In GPS-denied environments, indoor or dense forests, a pure INS odometry is available for estimating the trajectory of a human or robot. However it has a critical implementation problem: a drift error of velocity, position and heading angles. Commonly the problem can be solved by fusing visual landmarks, a magnetometer or radio beacons. These methods are not robust in diverse environments: darkness, fog or sunlight, an unstable magnetic field and an environmental obstacle. We propose to overcome the drift problem using an Iterative Closest Point (ICP) scan matching algorithm with a laser scanner. This system consists of three parts. The first is the INS. It estimates attitude, velocity, position based on a 6-axis Inertial Measurement Unit (IMU) with both 'Heuristic Reduction of Gyro Drift' (HRGD) and 'Heuristic Reduction of Velocity Drift' (HRVD) methods. A frame-to-frame ICP matching algorithm for estimating position and attitude by laser scan data is the second. The third is an extended kalman filter method for multi-sensor data fusing: INS and Laser Range Finder (LRF). The proposed method is simple and robust in diverse environments, so we could reduce the drift error efficiently. We confirm the result comparing an odometry of the experimental result with ICP and LRF aided-INS in a long corridor.

Impact of Sensor Misplacement on Dynamic Time Warping Based Human Activity Recognition using Wearable Computers.

PubMed

Kale, Nimish; Lee, Jaeseong; Lotfian, Reza; Jafari, Roozbeh

2012-10-01

Daily living activity monitoring is important for early detection of the onset of many diseases and for improving quality of life especially in elderly. A wireless wearable network of inertial sensor nodes can be used to observe daily motions. Continuous stream of data generated by these sensor networks can be used to recognize the movements of interest. Dynamic Time Warping (DTW) is a widely used signal processing method for time-series pattern matching because of its robustness to variations in time and speed as opposed to other template matching methods. Despite this flexibility, for the application of activity recognition, DTW can only find the similarity between the template of a movement and the incoming samples, when the location and orientation of the sensor remains unchanged. Due to this restriction, small sensor misplacements can lead to a decrease in the classification accuracy. In this work, we adopt DTW distance as a feature for real-time detection of human daily activities like sit to stand in the presence of sensor misplacement. To measure this performance of DTW, we need to create a large number of sensor configurations while the sensors are rotated or misplaced. Creating a large number of closely spaced sensors is impractical. To address this problem, we use the marker based optical motion capture system and generate simulated inertial sensor data for different locations and orientations on the body. We study the performance of the DTW under these conditions to determine the worst-case sensor location variations that the algorithm can accommodate.

An Experimental Study in Determining Energy Expenditure from Treadmill Walking using Hip-Worn Inertial Sensors

PubMed Central

Vathsangam, Harshvardhan; Emken, Adar; Schroeder, E. Todd; Spruijt-Metz, Donna; Sukhatme, Gaurav S.

2011-01-01

This paper describes an experimental study in estimating energy expenditure from treadmill walking using a single hip-mounted triaxial inertial sensor comprised of a triaxial accelerometer and a triaxial gyroscope. Typical physical activity characterization using accelerometer generated counts suffers from two drawbacks - imprecison (due to proprietary counts) and incompleteness (due to incomplete movement description). We address these problems in the context of steady state walking by directly estimating energy expenditure with data from a hip-mounted inertial sensor. We represent the cyclic nature of walking with a Fourier transform of sensor streams and show how one can map this representation to energy expenditure (as measured by V O2 consumption, mL/min) using three regression techniques - Least Squares Regression (LSR), Bayesian Linear Regression (BLR) and Gaussian Process Regression (GPR). We perform a comparative analysis of the accuracy of sensor streams in predicting energy expenditure (measured by RMS prediction accuracy). Triaxial information is more accurate than uniaxial information. LSR based approaches are prone to outlier sensitivity and overfitting. Gyroscopic information showed equivalent if not better prediction accuracy as compared to accelerometers. Combining accelerometer and gyroscopic information provided better accuracy than using either sensor alone. We also analyze the best algorithmic approach among linear and nonlinear methods as measured by RMS prediction accuracy and run time. Nonlinear regression methods showed better prediction accuracy but required an order of magnitude of run time. This paper emphasizes the role of probabilistic techniques in conjunction with joint modeling of triaxial accelerations and rotational rates to improve energy expenditure prediction for steady-state treadmill walking. PMID:21690001

Uncertainty Analysis of Inertial Model Attitude Sensor Calibration and Application with a Recommended New Calibration Method

NASA Technical Reports Server (NTRS)

Tripp, John S.; Tcheng, Ping

1999-01-01

Statistical tools, previously developed for nonlinear least-squares estimation of multivariate sensor calibration parameters and the associated calibration uncertainty analysis, have been applied to single- and multiple-axis inertial model attitude sensors used in wind tunnel testing to measure angle of attack and roll angle. The analysis provides confidence and prediction intervals of calibrated sensor measurement uncertainty as functions of applied input pitch and roll angles. A comparative performance study of various experimental designs for inertial sensor calibration is presented along with corroborating experimental data. The importance of replicated calibrations over extended time periods has been emphasized; replication provides independent estimates of calibration precision and bias uncertainties, statistical tests for calibration or modeling bias uncertainty, and statistical tests for sensor parameter drift over time. A set of recommendations for a new standardized model attitude sensor calibration method and usage procedures is included. The statistical information provided by these procedures is necessary for the uncertainty analysis of aerospace test results now required by users of industrial wind tunnel test facilities.

Design of an intelligent flight instrumentation unit using embedded RTOS

NASA Astrophysics Data System (ADS)

Estrada-Marmolejo, R.; García-Torales, G.; Torres-Ortega, H. H.; Flores, J. L.

2011-09-01

Micro Unmanned Aerial Vehicles (MUAV) must calculate its spatial position to control the flight dynamics, which is done by Inertial Measurement Units (IMUs). MEMS Inertial sensors have made possible to reduce the size and power consumption of such units. Commonly the flight instrumentation operates independently of the main processor. This work presents an instrumentation block design, which reduces size and power consumption of the complete system of a MUAV. This is done by coupling the inertial sensors to the main processor without considering any intermediate level of processing aside. Using Real Time Operating Systems (RTOS) reduces the number of intermediate components, increasing MUAV reliability. One advantage is the possibility to control several different sensors with a single communication bus. This feature of the MEMS sensors makes a smaller and less complex MUAV design possible.

A novel angle computation and calibration algorithm of bio-inspired sky-light polarization navigation sensor.

PubMed

Xian, Zhiwen; Hu, Xiaoping; Lian, Junxiang; Zhang, Lilian; Cao, Juliang; Wang, Yujie; Ma, Tao

2014-09-15

Navigation plays a vital role in our daily life. As traditional and commonly used navigation technologies, Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) can provide accurate location information, but suffer from the accumulative error of inertial sensors and cannot be used in a satellite denied environment. The remarkable navigation ability of animals shows that the pattern of the polarization sky can be used for navigation. A bio-inspired POLarization Navigation Sensor (POLNS) is constructed to detect the polarization of skylight. Contrary to the previous approach, we utilize all the outputs of POLNS to compute input polarization angle, based on Least Squares, which provides optimal angle estimation. In addition, a new sensor calibration algorithm is presented, in which the installation angle errors and sensor biases are taken into consideration. Derivation and implementation of our calibration algorithm are discussed in detail. To evaluate the performance of our algorithms, simulation and real data test are done to compare our algorithms with several exiting algorithms. Comparison results indicate that our algorithms are superior to the others and are more feasible and effective in practice.

Validity and Reliability of a Wearable Inertial Sensor to Measure Velocity and Power in the Back Squat and Bench Press.

PubMed

Orange, Samuel T; Metcalfe, James W; Liefeith, Andreas; Marshall, Phil; Madden, Leigh A; Fewster, Connor R; Vince, Rebecca V

2018-05-08

Orange, ST, Metcalfe, JW, Liefeith, A, Marshall, P, Madden, LA, Fewster, CR, and Vince, RV. Validity and reliability of a wearable inertial sensor to measure velocity and power in the back squat and bench press. J Strength Cond Res XX(X): 000-000, 2018-This study examined the validity and reliability of a wearable inertial sensor to measure velocity and power in the free-weight back squat and bench press. Twenty-nine youth rugby league players (18 ± 1 years) completed 2 test-retest sessions for the back squat followed by 2 test-retest sessions for the bench press. Repetitions were performed at 20, 40, 60, 80, and 90% of 1 repetition maximum (1RM) with mean velocity, peak velocity, mean power (MP), and peak power (PP) simultaneously measured using an inertial sensor (PUSH) and a linear position transducer (GymAware PowerTool). The PUSH demonstrated good validity (Pearson's product-moment correlation coefficient [r]) and reliability (intraclass correlation coefficient [ICC]) only for measurements of MP (r = 0.91; ICC = 0.83) and PP (r = 0.90; ICC = 0.80) at 20% of 1RM in the back squat. However, it may be more appropriate for athletes to jump off the ground with this load to optimize power output. Further research should therefore evaluate the usability of inertial sensors in the jump squat exercise. In the bench press, good validity and reliability were evident only for the measurement of MP at 40% of 1RM (r = 0.89; ICC = 0.83). The PUSH was unable to provide a valid and reliable estimate of any other criterion variable in either exercise. Practitioners must be cognizant of the measurement error when using inertial sensor technology to quantify velocity and power during resistance training, particularly with loads other than 20% of 1RM in the back squat and 40% of 1RM in the bench press.

Inertial navigation sensor integrated obstacle detection system

NASA Technical Reports Server (NTRS)

Bhanu, Bir (Inventor); Roberts, Barry A. (Inventor)

1992-01-01

A system that incorporates inertial sensor information into optical flow computations to detect obstacles and to provide alternative navigational paths free from obstacles. The system is a maximally passive obstacle detection system that makes selective use of an active sensor. The active detection typically utilizes a laser. Passive sensor suite includes binocular stereo, motion stereo and variable fields-of-view. Optical flow computations involve extraction, derotation and matching of interest points from sequential frames of imagery, for range interpolation of the sensed scene, which in turn provides obstacle information for purposes of safe navigation.

Method of producing an integral resonator sensor and case

NASA Technical Reports Server (NTRS)

Challoner, A. Dorian (Inventor); Yee, Karl Y. (Inventor); Shcheglov, Kirill V. (Inventor); Hayworth, Ken J. (Inventor); Wiberg, Dean V. (Inventor)

2005-01-01

The present invention discloses an inertial sensor having an integral resonator. A typical sensor comprises a planar mechanical resonator for sensing motion of the inertial sensor and a case for housing the resonator. The resonator and a wall of the case are defined through an etching process. A typical method of producing the resonator includes etching a baseplate, bonding a wafer to the etched baseplate, through etching the wafer to form a planar mechanical resonator and the wall of the case and bonding an end cap wafer to the wall to complete the case.

Tightly coupled low cost 3D RISS/GPS integration using a mixture particle filter for vehicular navigation.

PubMed

Georgy, Jacques; Noureldin, Aboelmagd

2011-01-01

Satellite navigation systems such as the global positioning system (GPS) are currently the most common technique used for land vehicle positioning. However, in GPS-denied environments, there is an interruption in the positioning information. Low-cost micro-electro mechanical system (MEMS)-based inertial sensors can be integrated with GPS and enhance the performance in denied GPS environments. The traditional technique for this integration problem is Kalman filtering (KF). Due to the inherent errors of low-cost MEMS inertial sensors and their large stochastic drifts, KF, with its linearized models, has limited capabilities in providing accurate positioning. Particle filtering (PF) was recently suggested as a nonlinear filtering technique to accommodate for arbitrary inertial sensor characteristics, motion dynamics and noise distributions. An enhanced version of PF called the Mixture PF is utilized in this study to perform tightly coupled integration of a three dimensional (3D) reduced inertial sensors system (RISS) with GPS. In this work, the RISS consists of one single-axis gyroscope and a two-axis accelerometer used together with the vehicle's odometer to obtain 3D navigation states. These sensors are then integrated with GPS in a tightly coupled scheme. In loosely-coupled integration, at least four satellites are needed to provide acceptable GPS position and velocity updates for the integration filter. The advantage of the tightly-coupled integration is that it can provide GPS measurement update(s) even when the number of visible satellites is three or lower, thereby improving the operation of the navigation system in environments with partial blockages by providing continuous aiding to the inertial sensors even during limited GPS satellite availability. To effectively exploit the capabilities of PF, advanced modeling for the stochastic drift of the vertically aligned gyroscope is used. In order to benefit from measurement updates for such drift, which are loosely-coupled updates, a hybrid loosely/tightly coupled solution is proposed. This solution is suitable for downtown environments because of the long natural outages or degradation of GPS. The performance of the proposed 3D Navigation solution using Mixture PF for 3D RISS/GPS integration is examined by road test trajectories in a land vehicle and compared to the KF counterpart.

Tightly Coupled Low Cost 3D RISS/GPS Integration Using a Mixture Particle Filter for Vehicular Navigation

PubMed Central

Georgy, Jacques; Noureldin, Aboelmagd

2011-01-01

Satellite navigation systems such as the global positioning system (GPS) are currently the most common technique used for land vehicle positioning. However, in GPS-denied environments, there is an interruption in the positioning information. Low-cost micro-electro mechanical system (MEMS)-based inertial sensors can be integrated with GPS and enhance the performance in denied GPS environments. The traditional technique for this integration problem is Kalman filtering (KF). Due to the inherent errors of low-cost MEMS inertial sensors and their large stochastic drifts, KF, with its linearized models, has limited capabilities in providing accurate positioning. Particle filtering (PF) was recently suggested as a nonlinear filtering technique to accommodate for arbitrary inertial sensor characteristics, motion dynamics and noise distributions. An enhanced version of PF called the Mixture PF is utilized in this study to perform tightly coupled integration of a three dimensional (3D) reduced inertial sensors system (RISS) with GPS. In this work, the RISS consists of one single-axis gyroscope and a two-axis accelerometer used together with the vehicle’s odometer to obtain 3D navigation states. These sensors are then integrated with GPS in a tightly coupled scheme. In loosely-coupled integration, at least four satellites are needed to provide acceptable GPS position and velocity updates for the integration filter. The advantage of the tightly-coupled integration is that it can provide GPS measurement update(s) even when the number of visible satellites is three or lower, thereby improving the operation of the navigation system in environments with partial blockages by providing continuous aiding to the inertial sensors even during limited GPS satellite availability. To effectively exploit the capabilities of PF, advanced modeling for the stochastic drift of the vertically aligned gyroscope is used. In order to benefit from measurement updates for such drift, which are loosely-coupled updates, a hybrid loosely/tightly coupled solution is proposed. This solution is suitable for downtown environments because of the long natural outages or degradation of GPS. The performance of the proposed 3D Navigation solution using Mixture PF for 3D RISS/GPS integration is examined by road test trajectories in a land vehicle and compared to the KF counterpart. PMID:22163846

Inertial Motion Capture Costume Design Study

PubMed Central

Szczęsna, Agnieszka; Skurowski, Przemysław; Lach, Ewa; Pruszowski, Przemysław; Pęszor, Damian; Paszkuta, Marcin; Słupik, Janusz; Lebek, Kamil; Janiak, Mateusz; Polański, Andrzej; Wojciechowski, Konrad

2017-01-01

The paper describes a scalable, wearable multi-sensor system for motion capture based on inertial measurement units (IMUs). Such a unit is composed of accelerometer, gyroscope and magnetometer. The final quality of an obtained motion arises from all the individual parts of the described system. The proposed system is a sequence of the following stages: sensor data acquisition, sensor orientation estimation, system calibration, pose estimation and data visualisation. The construction of the system’s architecture with the dataflow programming paradigm makes it easy to add, remove and replace the data processing steps. The modular architecture of the system allows an effortless introduction of a new sensor orientation estimation algorithms. The original contribution of the paper is the design study of the individual components used in the motion capture system. The two key steps of the system design are explored in this paper: the evaluation of sensors and algorithms for the orientation estimation. The three chosen algorithms have been implemented and investigated as part of the experiment. Due to the fact that the selection of the sensor has a significant impact on the final result, the sensor evaluation process is also explained and tested. The experimental results confirmed that the choice of sensor and orientation estimation algorithm affect the quality of the final results. PMID:28304337

A Highly Reliable and Cost-Efficient Multi-Sensor System for Land Vehicle Positioning.

PubMed

Li, Xu; Xu, Qimin; Li, Bin; Song, Xianghui

2016-05-25

In this paper, we propose a novel positioning solution for land vehicles which is highly reliable and cost-efficient. The proposed positioning system fuses information from the MEMS-based reduced inertial sensor system (RISS) which consists of one vertical gyroscope and two horizontal accelerometers, low-cost GPS, and supplementary sensors and sources. First, pitch and roll angle are accurately estimated based on a vehicle kinematic model. Meanwhile, the negative effect of the uncertain nonlinear drift of MEMS inertial sensors is eliminated by an H∞ filter. Further, a distributed-dual-H∞ filtering (DDHF) mechanism is adopted to address the uncertain nonlinear drift of the MEMS-RISS and make full use of the supplementary sensors and sources. The DDHF is composed of a main H∞ filter (MHF) and an auxiliary H∞ filter (AHF). Finally, a generalized regression neural network (GRNN) module with good approximation capability is specially designed for the MEMS-RISS. A hybrid methodology which combines the GRNN module and the AHF is utilized to compensate for RISS position errors during GPS outages. To verify the effectiveness of the proposed solution, road-test experiments with various scenarios were performed. The experimental results illustrate that the proposed system can achieve accurate and reliable positioning for land vehicles.

Shoe-Insole Technology for Injury Prevention in Walking

PubMed Central

Nagano, Hanatsu

2018-01-01

Impaired walking increases injury risk during locomotion, including falls-related acute injuries and overuse damage to lower limb joints. Gait impairments seriously restrict voluntary, habitual engagement in injury prevention activities, such as recreational walking and exercise. There is, therefore, an urgent need for technology-based interventions for gait disorders that are cost effective, willingly taken-up, and provide immediate positive effects on walking. Gait control using shoe-insoles has potential as an effective population-based intervention, and new sensor technologies will enhance the effectiveness of these devices. Shoe-insole modifications include: (i) ankle joint support for falls prevention; (ii) shock absorption by utilising lower-resilience materials at the heel; (iii) improving reaction speed by stimulating cutaneous receptors; and (iv) preserving dynamic balance via foot centre of pressure control. Using sensor technology, such as in-shoe pressure measurement and motion capture systems, gait can be precisely monitored, allowing us to visualise how shoe-insoles change walking patterns. In addition, in-shoe systems, such as pressure monitoring and inertial sensors, can be incorporated into the insole to monitor gait in real-time. Inertial sensors coupled with in-shoe foot pressure sensors and global positioning systems (GPS) could be used to monitor spatiotemporal parameters in real-time. Real-time, online data management will enable ‘big-data’ applications to everyday gait control characteristics. PMID:29738486

A Highly Reliable and Cost-Efficient Multi-Sensor System for Land Vehicle Positioning

PubMed Central

Li, Xu; Xu, Qimin; Li, Bin; Song, Xianghui

2016-01-01

In this paper, we propose a novel positioning solution for land vehicles which is highly reliable and cost-efficient. The proposed positioning system fuses information from the MEMS-based reduced inertial sensor system (RISS) which consists of one vertical gyroscope and two horizontal accelerometers, low-cost GPS, and supplementary sensors and sources. First, pitch and roll angle are accurately estimated based on a vehicle kinematic model. Meanwhile, the negative effect of the uncertain nonlinear drift of MEMS inertial sensors is eliminated by an H∞ filter. Further, a distributed-dual-H∞ filtering (DDHF) mechanism is adopted to address the uncertain nonlinear drift of the MEMS-RISS and make full use of the supplementary sensors and sources. The DDHF is composed of a main H∞ filter (MHF) and an auxiliary H∞ filter (AHF). Finally, a generalized regression neural network (GRNN) module with good approximation capability is specially designed for the MEMS-RISS. A hybrid methodology which combines the GRNN module and the AHF is utilized to compensate for RISS position errors during GPS outages. To verify the effectiveness of the proposed solution, road-test experiments with various scenarios were performed. The experimental results illustrate that the proposed system can achieve accurate and reliable positioning for land vehicles. PMID:27231917

Quantifying Variation in Gait Features from Wearable Inertial Sensors Using Mixed Effects Models

PubMed Central

Cresswell, Kellen Garrison; Shin, Yongyun; Chen, Shanshan

2017-01-01

The emerging technology of wearable inertial sensors has shown its advantages in collecting continuous longitudinal gait data outside laboratories. This freedom also presents challenges in collecting high-fidelity gait data. In the free-living environment, without constant supervision from researchers, sensor-based gait features are susceptible to variation from confounding factors such as gait speed and mounting uncertainty, which are challenging to control or estimate. This paper is one of the first attempts in the field to tackle such challenges using statistical modeling. By accepting the uncertainties and variation associated with wearable sensor-based gait data, we shift our efforts from detecting and correcting those variations to modeling them statistically. From gait data collected on one healthy, non-elderly subject during 48 full-factorial trials, we identified four major sources of variation, and quantified their impact on one gait outcome—range per cycle—using a random effects model and a fixed effects model. The methodology developed in this paper lays the groundwork for a statistical framework to account for sources of variation in wearable gait data, thus facilitating informative statistical inference for free-living gait analysis. PMID:28245602

Measurement of transmission of vibration through the human spine using skin-mounted inertial sensors.

PubMed

Morgado Ramírez, Dafne Z; Strike, Siobhan; Lee, Raymond Y W

2013-05-01

The purpose of this study was to examine the feasibility of measuring the transmission of vibration using skin mounted inertial sensors and to assess the dynamic properties of the human spine during activities of daily living. Two inertial sensors were attached to skin overlying the first thoracic vertebra (T1) and another one over the first sacral vertebra (S1) with double sided adhesive tape. Subjects walked along a straight line, and up and down stairs at a self selected, comfortable speed. Transmissibility of vertical vibration was calculated as the ratio of the power spectral density of the acceleration signal at T1 over that at S1, over the frequency range of 0.5-12Hz. Cross correlation and coherence of the acceleration signals between the two T1 sensors were performed to evaluate the similarity of the data after correction. Cross correlation of signals between trials was also performed to examine the repeatability of the signals. Cross correlation coefficients were found to be very high (>0.9). Inter-trial consistency of the signals of all sensors was also high (>0.9). It is concluded that skin measurement of transmission of vertical vibration is feasible with the inertial sensors and correction method presented. Different physical activities seem to elicit different frequency characteristics of vibration. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

Inertial Navigation Sensors

DTIC Science & Technology

2010-03-01

Characterization Solutions Enabled by Laser Doppler Vibrometer Measurements, Proc. SPIE, Fifth International Conference on Vibration Measurements by Laser ...commercial capabilities: Ring Laser Gyros, Fiber Optic Gyros, and Micro-Electro-Mechanical Systems (MEMS) gyros and accelerometers. RLGs and FOGs are now...augmentation sensors have been tied into the inertial systems; e.g., GPS, velocity meters, seekers, star trackers, magnetometers, lidar , etc. The

Cloud Absorption Radiometer Autonomous Navigation System - CANS

NASA Technical Reports Server (NTRS)

Kahle, Duncan; Gatebe, Charles; McCune, Bill; Hellwig, Dustan

2013-01-01

CAR (cloud absorption radiometer) acquires spatial reference data from host aircraft navigation systems. This poses various problems during CAR data reduction, including navigation data format, accuracy of position data, accuracy of airframe inertial data, and navigation data rate. Incorporating its own navigation system, which included GPS (Global Positioning System), roll axis inertia and rates, and three axis acceleration, CANS expedites data reduction and increases the accuracy of the CAR end data product. CANS provides a self-contained navigation system for the CAR, using inertial reference and GPS positional information. The intent of the software application was to correct the sensor with respect to aircraft roll in real time based upon inputs from a precision navigation sensor. In addition, the navigation information (including GPS position), attitude data, and sensor position details are all streamed to a remote system for recording and later analysis. CANS comprises a commercially available inertial navigation system with integral GPS capability (Attitude Heading Reference System AHRS) integrated into the CAR support structure and data system. The unit is attached to the bottom of the tripod support structure. The related GPS antenna is located on the P-3 radome immediately above the CAR. The AHRS unit provides a RS-232 data stream containing global position and inertial attitude and velocity data to the CAR, which is recorded concurrently with the CAR data. This independence from aircraft navigation input provides for position and inertial state data that accounts for very small changes in aircraft attitude and position, sensed at the CAR location as opposed to aircraft state sensors typically installed close to the aircraft center of gravity. More accurate positional data enables quicker CAR data reduction with better resolution. The CANS software operates in two modes: initialization/calibration and operational. In the initialization/calibration mode, the software aligns the precision navigation sensors and initializes the communications interfaces with the sensor and the remote computing system. It also monitors the navigation data state for quality and ensures that the system maintains the required fidelity for attitude and positional information. In the operational mode, the software runs at 12.5 Hz and gathers the required navigation/attitude data, computes the required sensor correction values, and then commands the sensor to the required roll correction. In this manner, the sensor will stay very near to vertical at all times, greatly improving the resulting collected data and imagery. CANS greatly improves quality of resulting imagery and data collected. In addition, the software component of the system outputs a concisely formatted, high-speed data stream that can be used for further science data processing. This precision, time-stamped data also can benefit other instruments on the same aircraft platform by providing extra information from the mission flight.

Swarm Optimization-Based Magnetometer Calibration for Personal Handheld Devices

PubMed Central

Ali, Abdelrahman; Siddharth, Siddharth; Syed, Zainab; El-Sheimy, Naser

2012-01-01

Inertial Navigation Systems (INS) consist of accelerometers, gyroscopes and a processor that generates position and orientation solutions by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the user heading based on Earth's magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are usually corrupted by several errors, including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO)-based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometers. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. Furthermore, the proposed algorithm can help in the development of Pedestrian Navigation Devices (PNDs) when combined with inertial sensors and GPS/Wi-Fi for indoor navigation and Location Based Services (LBS) applications.

A Low-Power ASIC Signal Processor for a Vestibular Prosthesis.

PubMed

Töreyin, Hakan; Bhatti, Pamela T

2016-06-01

A low-power ASIC signal processor for a vestibular prosthesis (VP) is reported. Fabricated with TI 0.35 μm CMOS technology and designed to interface with implanted inertial sensors, the digitally assisted analog signal processor operates extensively in the CMOS subthreshold region. During its operation the ASIC encodes head motion signals captured by the inertial sensors as electrical pulses ultimately targeted for in-vivo stimulation of vestibular nerve fibers. To achieve this, the ASIC implements a coordinate system transformation to correct for misalignment between natural sensors and implanted inertial sensors. It also mimics the frequency response characteristics and frequency encoding mappings of angular and linear head motions observed at the peripheral sense organs, semicircular canals and otolith. Overall the design occupies an area of 6.22 mm (2) and consumes 1.24 mW when supplied with ± 1.6 V.

A Low-Power ASIC Signal Processor for a Vestibular Prosthesis

PubMed Central

Töreyin, Hakan; Bhatti, Pamela T.

2017-01-01

A low-power ASIC signal processor for a vestibular prosthesis (VP) is reported. Fabricated with TI 0.35 μm CMOS technology and designed to interface with implanted inertial sensors, the digitally assisted analog signal processor operates extensively in the CMOS subthreshold region. During its operation the ASIC encodes head motion signals captured by the inertial sensors as electrical pulses ultimately targeted for in-vivo stimulation of vestibular nerve fibers. To achieve this, the ASIC implements a coordinate system transformation to correct for misalignment between natural sensors and implanted inertial sensors. It also mimics the frequency response characteristics and frequency encoding mappings of angular and linear head motions observed at the peripheral sense organs, semicircular canals and otolith. Overall the design occupies an area of 6.22 mm2 and consumes 1.24 mW when supplied with ± 1.6 V. PMID:26800546

Disability and Fatigue Can Be Objectively Measured in Multiple Sclerosis

PubMed Central

Motta, Caterina; Palermo, Eduardo; Studer, Valeria; Germanotta, Marco; Germani, Giorgio; Centonze, Diego; Cappa, Paolo

2016-01-01

Background The available clinical outcome measures of disability in multiple sclerosis are not adequately responsive or sensitive. Objective To investigate the feasibility of inertial sensor-based gait analysis in multiple sclerosis. Methods A cross-sectional study of 80 multiple sclerosis patients and 50 healthy controls was performed. Lower-limb kinematics was evaluated by using a commercially available magnetic inertial measurement unit system. Mean and standard deviation of range of motion (mROM, sROM) for each joint of lower limbs were calculated in one minute walking test. A motor performance index (E) defined as the sum of sROMs was proposed. Results We established two novel observer-independent measures of disability. Hip mROM was extremely sensitive in measuring lower limb motor impairment, being correlated with muscle strength and also altered in patients without clinically detectable disability. On the other hand, E index discriminated patients according to disability, being altered only in patients with moderate and severe disability, regardless of walking speed. It was strongly correlated with fatigue and patient-perceived health status. Conclusions Inertial sensor-based gait analysis is feasible and can detect clinical and subclinical disability in multiple sclerosis. PMID:26863109

Laboratory measurements of grain-bedrock interactions using inertial sensors.

NASA Astrophysics Data System (ADS)

Maniatis, Georgios; Hoey, Trevor; Hodge, Rebecca; Valyrakis, Manousos; Drysdale, Tim

2016-04-01

Sediment transport in steep mountain streams is characterized by the movement of coarse particles (diameter c.100 mm) over beds that are not fully sediment-covered. Under such conditions, individual grain dynamics become important for the prediction of sediment movement and subsequently for understanding grain-bedrock interaction. Technological advances in micro-mechanical-electrical systems now provide opportunities to measure individual grain dynamics and impact forces from inside the sediments (grain inertial frame of reference) instead of trying to infer them indirectly from water flow dynamics. We previously presented a new prototype sensor specifically developed for monitoring sediment transport [Maniatis et al. EGU 2014], and have shown how the definition of the physics of the grain using the inertial frame and subsequent derived measurements which have the potential to enhance the prediction of sediment entrainment [Maniatis et al. 2015]. Here we present the latest version of this sensor and we focus on beginning of the cessation of grain motion: the initial interaction with the bed after the translation phase. The sensor is housed in a spherical case, diameter 80mm, and is constructed using solid aluminum (density = 2.7 kg.m-3) after detailed 3D-CAD modelling. A complete Inertial Measurement Unit (a combination of micro- accelerometer, gyroscope and compass) was placed at the center of the mass of the assembly, with measurement ranges of 400g for acceleration, and 1200 rads/sec for angular velocity. In a 0.9m wide laboratory flume, bed slope = 0.02, the entrainment threshold of the sensor was measured, and the water flow was then set to this value. The sensor was then rolled freely from a static cylindrical bar positioned exactly on the surface of the flowing water. As the sensor enters the flow we record a very short period of transport (1-1.5 sec) followed by the impact on the channel bed. The measured Total Kinetic Energy (Joules) includes the translational energy component of transport (defined as a function of 3-dimensional translational velocity) as well as the rotational component (a function of the 3-axis angular velocity measurements from the gyroscope) which is neglected in the majority of contemporary saltation models. The results suggest that, for this grain scale, the magnitude of the impact of mobile grains on the bed is primarily controlled by their inertia. References Maniatis et al. 2014 EGU General assembly http://meetingorganizer.copernicus.org/EGU2014/EGU2014-12829.pdf Maniatis et. al 2015: "CALCULATION OF EXPLICIT PROBABILITY OF ENTRAINMENT BASED ON INERTIAL ACCELERATION MEASUREMENTS" J. Hydraulic Engineering, Under review.

Hand Pose Estimation by Fusion of Inertial and Magnetic Sensing Aided by a Permanent Magnet.

PubMed

Kortier, Henk G; Antonsson, Jacob; Schepers, H Martin; Gustafsson, Fredrik; Veltink, Peter H

2015-09-01

Tracking human body motions using inertial sensors has become a well-accepted method in ambulatory applications since the subject is not confined to a lab-bounded volume. However, a major drawback is the inability to estimate relative body positions over time because inertial sensor information only allows position tracking through strapdown integration, but does not provide any information about relative positions. In addition, strapdown integration inherently results in drift of the estimated position over time. We propose a novel method in which a permanent magnet combined with 3-D magnetometers and 3-D inertial sensors are used to estimate the global trunk orientation and relative pose of the hand with respect to the trunk. An Extended Kalman Filter is presented to fuse estimates obtained from inertial sensors with magnetic updates such that the position and orientation between the human hand and trunk as well as the global trunk orientation can be estimated robustly. This has been demonstrated in multiple experiments in which various hand tasks were performed. The most complex task in which simultaneous movements of both trunk and hand were performed resulted in an average rms position difference with an optical reference system of 19.7±2.2 mm whereas the relative trunk-hand and global trunk orientation error was 2.3±0.9 and 8.6±8.7 deg respectively.

Predicting Functional Independence Measure Scores During Rehabilitation with Wearable Inertial Sensors

PubMed Central

Sprint, Gina; Cook, Diane J.; Weeks, Douglas L.; Borisov, Vladimir

2016-01-01

Evaluating patient progress and making discharge decisions regarding inpatient medical rehabilitation rely upon standard clinical assessments administered by trained clinicians. Wearable inertial sensors can offer more objective measures of patient movement and progress. We undertook a study to investigate the contribution of wearable sensor data to predict discharge functional independence measure (FIM) scores for 20 patients at an inpatient rehabilitation facility. The FIM utilizes a 7-point ordinal scale to measure patient independence while performing several activities of daily living, such as walking, grooming, and bathing. Wearable inertial sensor data were collected from ecological ambulatory tasks at two time points mid-stay during inpatient rehabilitation. Machine learning algorithms were trained with sensor-derived features and clinical information obtained from medical records at admission to the inpatient facility. While models trained only with clinical features predicted discharge scores well, we were able to achieve an even higher level of prediction accuracy when also including the wearable sensor-derived features. Correlations as high as 0.97 for leave-one-out cross validation predicting discharge FIM motor scores are reported. PMID:27054054

Enhanced Pedestrian Navigation Based on Course Angle Error Estimation Using Cascaded Kalman Filters

PubMed Central

Park, Chan Gook

2018-01-01

An enhanced pedestrian dead reckoning (PDR) based navigation algorithm, which uses two cascaded Kalman filters (TCKF) for the estimation of course angle and navigation errors, is proposed. The proposed algorithm uses a foot-mounted inertial measurement unit (IMU), waist-mounted magnetic sensors, and a zero velocity update (ZUPT) based inertial navigation technique with TCKF. The first stage filter estimates the course angle error of a human, which is closely related to the heading error of the IMU. In order to obtain the course measurements, the filter uses magnetic sensors and a position-trace based course angle. For preventing magnetic disturbance from contaminating the estimation, the magnetic sensors are attached to the waistband. Because the course angle error is mainly due to the heading error of the IMU, and the characteristic error of the heading angle is highly dependent on that of the course angle, the estimated course angle error is used as a measurement for estimating the heading error in the second stage filter. At the second stage, an inertial navigation system-extended Kalman filter-ZUPT (INS-EKF-ZUPT) method is adopted. As the heading error is estimated directly by using course-angle error measurements, the estimation accuracy for the heading and yaw gyro bias can be enhanced, compared with the ZUPT-only case, which eventually enhances the position accuracy more efficiently. The performance enhancements are verified via experiments, and the way-point position error for the proposed method is compared with those for the ZUPT-only case and with other cases that use ZUPT and various types of magnetic heading measurements. The results show that the position errors are reduced by a maximum of 90% compared with the conventional ZUPT based PDR algorithms. PMID:29690539

Vibration Noise Modeling for Measurement While Drilling System Based on FOGs.

PubMed

Zhang, Chunxi; Wang, Lu; Gao, Shuang; Lin, Tie; Li, Xianmu

2017-10-17

Aiming to improve survey accuracy of Measurement While Drilling (MWD) based on Fiber Optic Gyroscopes (FOGs) in the long period, the external aiding sources are fused into the inertial navigation by the Kalman filter (KF) method. The KF method needs to model the inertial sensors' noise as the system noise model. The system noise is modeled as white Gaussian noise conventionally. However, because of the vibration while drilling, the noise in gyros isn't white Gaussian noise any more. Moreover, an incorrect noise model will degrade the accuracy of KF. This paper developed a new approach for noise modeling on the basis of dynamic Allan variance (DAVAR). In contrast to conventional white noise models, the new noise model contains both the white noise and the color noise. With this new noise model, the KF for the MWD was designed. Finally, two vibration experiments have been performed. Experimental results showed that the proposed vibration noise modeling approach significantly improved the estimated accuracies of the inertial sensor drifts. Compared the navigation results based on different noise model, with the DAVAR noise model, the position error and the toolface angle error are reduced more than 90%. The velocity error is reduced more than 65%. The azimuth error is reduced more than 50%.

Towards a space-borne quantum gravity gradiometer: progress in laboratory demonstration

NASA Technical Reports Server (NTRS)

Yu, Nan; Kohel, James M.; Kellogg, James R.; Maleki, Lute

2005-01-01

This paper describes the working principles and technical benefits of atom-wave interferometer-based inertial sensors, and gives a progress report on the development of a quantum gravity gradiometer for space applications at JPL.

Estimating Position of Mobile Robots From Omnidirectional Vision Using an Adaptive Algorithm.

PubMed

Li, Luyang; Liu, Yun-Hui; Wang, Kai; Fang, Mu

2015-08-01

This paper presents a novel and simple adaptive algorithm for estimating the position of a mobile robot with high accuracy in an unknown and unstructured environment by fusing images of an omnidirectional vision system with measurements of odometry and inertial sensors. Based on a new derivation where the omnidirectional projection can be linearly parameterized by the positions of the robot and natural feature points, we propose a novel adaptive algorithm, which is similar to the Slotine-Li algorithm in model-based adaptive control, to estimate the robot's position by using the tracked feature points in image sequence, the robot's velocity, and orientation angles measured by odometry and inertial sensors. It is proved that the adaptive algorithm leads to global exponential convergence of the position estimation errors to zero. Simulations and real-world experiments are performed to demonstrate the performance of the proposed algorithm.

Bundle adjustment with raw inertial observations in UAV applications

NASA Astrophysics Data System (ADS)

Cucci, Davide Antonio; Rehak, Martin; Skaloud, Jan

2017-08-01

It is well known that accurate aerial position and attitude control is beneficial for image orientation in airborne photogrammetry. The aerial control is traditionally obtained by Kalman filtering/smoothing inertial and GNSS observations prior to the bundle-adjustment. However, in Micro Aerial Vehicles this process may result in poor attitude determination due to the limited quality of the inertial sensors, large alignment uncertainty and residual correlations between sensor biases and initial attitude. We propose to include the raw inertial observations directly into the bundle-adjustment instead of as position and attitude weighted observations from a separate inertial/GNSS fusion step. The necessary observation models are derived in detail within the context of the so called "Dynamic Networks". We examine different real world cases and we show that the proposed approach is superior to the established processing pipeline in challenging scenarios such as mapping in corridors and in areas where the reception of GNSS signals is denied.

Inertial Sensor Characterization for Inertial Navigation and Human Motion Tracking Applications

DTIC Science & Technology

2012-06-01

sensor to the pendulum. The time he took to design this part in SolidWorks so that I could have it printed on a 3D printer was greatly appreciated...I would also like to thank Daniel Sakoda for his quick turnaround in printing the mounting bracket using a 3D printer . Lastly, I would like to...sensors provide three-dimensional ( 3D ) orientation, acceleration, rate of turn, and magnetic field information. Manufacturers specify both static and

Hubble Space Telescope Angular Velocity Estimation During the Robotic Servicing Mission

NASA Technical Reports Server (NTRS)

Thienel, Julie K.; Queen, Steven Z.; VanEepoel, John M.; Sanner, Robert M.

2005-01-01

During the Hubble Robotic Servicing Mission, the Hubble Space Telescope (HST) attitude and rates are necessary to achieve the capture of HST by the Hubble Robotic Vehicle (HRV). The attitude and rates must be determined without the HST gyros or HST attitude estimates. The HRV will be equipped with vision-based sensors, capable of estimating the relative attitude between HST and HRV. The HST attitude is derived from the measured relative attitude and the HRV computed inertial attitude. However, the relative rate between HST and HRV cannot be measured directly. Therefore, the HST rate with respect to inertial space is not known. Two approaches are developed to estimate the HST rates. Both methods utilize the measured relative attitude and the HRV inertial attitude and rates. First, a nonlinear estimator is developed. The nonlinear approach estimates the HST rate through an estimation of the inertial angular momentum. Second, a linearized approach is developed. The linearized approach is based on more traditional Extended Kalman filter techniques. Simulation test results for both methods are given.

Systems and Methods for Determining Inertial Navigation System Faults

NASA Technical Reports Server (NTRS)

Bharadwaj, Raj Mohan (Inventor); Bageshwar, Vibhor L. (Inventor); Kim, Kyusung (Inventor)

2017-01-01

An inertial navigation system (INS) includes a primary inertial navigation system (INS) unit configured to receive accelerometer measurements from an accelerometer and angular velocity measurements from a gyroscope. The primary INS unit is further configured to receive global navigation satellite system (GNSS) signals from a GNSS sensor and to determine a first set of kinematic state vectors based on the accelerometer measurements, the angular velocity measurements, and the GNSS signals. The INS further includes a secondary INS unit configured to receive the accelerometer measurements and the angular velocity measurements and to determine a second set of kinematic state vectors of the vehicle based on the accelerometer measurements and the angular velocity measurements. A health management system is configured to compare the first set of kinematic state vectors and the second set of kinematic state vectors to determine faults associated with the accelerometer or the gyroscope based on the comparison.

The Future of Classification in Wheelchair Sports; Can Data Science and Technological Advancement Offer an Alternative Point of View?

PubMed

van der Slikke, Rienk M A; Bregman, Daan J J; Berger, Monique A M; de Witte, Annemarie M H; Veeger, Dirk-Jan H E J

2017-11-01

Classification is a defining factor for competition in wheelchair sports, but it is a delicate and time-consuming process with often questionable validity. 1 New inertial sensor based measurement methods applied in match play and field tests, allow for more precise and objective estimates of the impairment effect on wheelchair mobility performance. It was evaluated if these measures could offer an alternative point of view for classification. Six standard wheelchair mobility performance outcomes of different classification groups were measured in match play (n=29), as well as best possible performance in a field test (n=47). In match-results a clear relationship between classification and performance level is shown, with increased performance outcomes in each adjacent higher classification group. Three outcomes differed significantly between the low and mid-class groups, and one between the mid and high-class groups. In best performance (field test), a split between the low and mid-class groups shows (5 out of 6 outcomes differed significantly) but hardly any difference between the mid and high-class groups. This observed split was confirmed by cluster analysis, revealing the existence of only two performance based clusters. The use of inertial sensor technology to get objective measures of wheelchair mobility performance, combined with a standardized field-test, brought alternative views for evidence based classification. The results of this approach provided arguments for a reduced number of classes in wheelchair basketball. Future use of inertial sensors in match play and in field testing could enhance evaluation of classification guidelines as well as individual athlete performance.

Landmark-Based Drift Compensation Algorithm for Inertial Pedestrian Navigation

PubMed Central

Munoz Diaz, Estefania; Caamano, Maria; Fuentes Sánchez, Francisco Javier

2017-01-01

The navigation of pedestrians based on inertial sensors, i.e., accelerometers and gyroscopes, has experienced a great growth over the last years. However, the noise of medium- and low-cost sensors causes a high error in the orientation estimation, particularly in the yaw angle. This error, called drift, is due to the bias of the z-axis gyroscope and other slow changing errors, such as temperature variations. We propose a seamless landmark-based drift compensation algorithm that only uses inertial measurements. The proposed algorithm adds a great value to the state of the art, because the vast majority of the drift elimination algorithms apply corrections to the estimated position, but not to the yaw angle estimation. Instead, the presented algorithm computes the drift value and uses it to prevent yaw errors and therefore position errors. In order to achieve this goal, a detector of landmarks, i.e., corners and stairs, and an association algorithm have been developed. The results of the experiments show that it is possible to reliably detect corners and stairs using only inertial measurements eliminating the need that the user takes any action, e.g., pressing a button. Associations between re-visited landmarks are successfully made taking into account the uncertainty of the position. After that, the drift is computed out of all associations and used during a post-processing stage to obtain a low-drifted yaw angle estimation, that leads to successfully drift compensated trajectories. The proposed algorithm has been tested with quasi-error-free turn rate measurements introducing known biases and with medium-cost gyroscopes in 3D indoor and outdoor scenarios. PMID:28671622

An accurate nonlinear stochastic model for MEMS-based inertial sensor error with wavelet networks

NASA Astrophysics Data System (ADS)

El-Diasty, Mohammed; El-Rabbany, Ahmed; Pagiatakis, Spiros

2007-12-01

The integration of Global Positioning System (GPS) with Inertial Navigation System (INS) has been widely used in many applications for positioning and orientation purposes. Traditionally, random walk (RW), Gauss-Markov (GM), and autoregressive (AR) processes have been used to develop the stochastic model in classical Kalman filters. The main disadvantage of classical Kalman filter is the potentially unstable linearization of the nonlinear dynamic system. Consequently, a nonlinear stochastic model is not optimal in derivative-based filters due to the expected linearization error. With a derivativeless-based filter such as the unscented Kalman filter or the divided difference filter, the filtering process of a complicated highly nonlinear dynamic system is possible without linearization error. This paper develops a novel nonlinear stochastic model for inertial sensor error using a wavelet network (WN). A wavelet network is a highly nonlinear model, which has recently been introduced as a powerful tool for modelling and prediction. Static and kinematic data sets are collected using a MEMS-based IMU (DQI-100) to develop the stochastic model in the static mode and then implement it in the kinematic mode. The derivativeless-based filtering method using GM, AR, and the proposed WN-based processes are used to validate the new model. It is shown that the first-order WN-based nonlinear stochastic model gives superior positioning results to the first-order GM and AR models with an overall improvement of 30% when 30 and 60 seconds GPS outages are introduced.

A novel approach to spinal 3-D kinematic assessment using inertial sensors: Towards effective quantitative evaluation of low back pain in clinical settings.

PubMed

Ashouri, Sajad; Abedi, Mohsen; Abdollahi, Masoud; Dehghan Manshadi, Farideh; Parnianpour, Mohamad; Khalaf, Kinda

2017-10-01

This paper presents a novel approach for evaluating LBP in various settings. The proposed system uses cost-effective inertial sensors, in conjunction with pattern recognition techniques, for identifying sensitive classifiers towards discriminate identification of LB patients. 24 healthy individuals and 28 low back pain patients performed trunk motion tasks in five different directions for validation. Four combinations of these motions were selected based on literature, and the corresponding kinematic data was collected. Upon filtering (4th order, low pass Butterworth filter) and normalizing the data, Principal Component Analysis was used for feature extraction, while Support Vector Machine classifier was applied for data classification. The results reveal that non-linear Kernel classification can be adequately employed for low back pain identification. Our preliminary results demonstrate that using a single inertial sensor placed on the thorax, in conjunction with a relatively simple test protocol, can identify low back pain with an accuracy of 96%, a sensitivity of %100, and specificity of 92%. While our approach shows promising results, further validation in a larger population is required towards using the methodology as a practical quantitative assessment tool for the detection of low back pain in clinical/rehabilitation settings. Copyright © 2017 Elsevier Ltd. All rights reserved.

Inertial Sensor Based Analysis of Lie-to-Stand Transfers in Younger and Older Adults

PubMed Central

Schwickert, Lars; Boos, Ronald; Klenk, Jochen; Bourke, Alan; Becker, Clemens; Zijlstra, Wiebren

2016-01-01

Many older adults lack the capacity to stand up again after a fall. Therefore, to analyse falls it is relevant to understand recovery patterns, including successful and failed attempts to get up from the floor in general. This study analysed different kinematic features of standing up from the floor. We used inertial sensors to describe the kinematics of lie-to-stand transfer patterns of younger and healthy older adults. Fourteen younger (20–50 years of age, 50% men) and 10 healthy older community dwellers (≥60 years; 50% men) conducted four lie-to-stand transfers from different initial lying postures. The analysed temporal, kinematic, and elliptic fitting complexity measures of transfer performance were significantly different between younger and older subjects (i.e., transfer duration, angular velocity (RMS), maximum vertical acceleration, maximum vertical velocity, smoothness, fluency, ellipse width, angle between ellipses). These results show the feasibility and potential of analysing kinematic features to describe the lie-to-stand transfer performance, to help design interventions and detection approaches to prevent long lies after falls. It is possible to describe age-related differences in lie-to-stand transfer performance using inertial sensors. The kinematic analysis remains to be tested on patterns after real-world falls. PMID:27529249

A new torsion pendulum for gravitational reference sensor technology development.

PubMed

Ciani, Giacomo; Chilton, Andrew; Apple, Stephen; Olatunde, Taiwo; Aitken, Michael; Mueller, Guido; Conklin, John W

2017-06-01

We report on the design and sensitivity of a new torsion pendulum for measuring the performance of ultra-precise inertial sensors and for the development of associated technologies for space-based gravitational wave observatories and geodesy missions. The apparatus comprises a 1 m-long, 50 μm-diameter tungsten fiber that supports an inertial member inside a vacuum system. The inertial member is an aluminum crossbar with four hollow cubic test masses at each end. This structure converts the rotation of the torsion pendulum into translation of the test masses. Two test masses are enclosed in capacitive sensors which provide readout and actuation. These test masses are electrically insulated from the rest of the crossbar and their electrical charge is controlled by photoemission using fiber-coupled ultraviolet light emitting diodes. The capacitive readout measures the test mass displacement with a broadband sensitivity of 30 nm∕Hz and is complemented by a laser interferometer with a sensitivity of about 0.5 nm∕Hz. The performance of the pendulum, as determined by the measured residual torque noise and expressed in terms of equivalent force acting on a single test mass, is roughly 200 fN∕Hz around 2 mHz, which is about a factor of 20 above the thermal noise limit of the fiber.

Microelectromechanical inertial sensor

DOEpatents

Okandan, Murat [Edgewood, NM; Nielson, Gregory N [Albuquerque, NM

2012-06-26

A microelectromechanical (MEM) inertial sensor is disclosed which can be used to sense a linear acceleration, or a Coriolis acceleration due to an angular rotation rate, or both. The MEM inertial sensor has a proof mass which is supported on a bridge extending across an opening through a substrate, with the proof mass being balanced on the bridge by a pivot, or suspended from the bridge by the pivot. The proof mass can be oscillated in a tangential direction in the plane of the substrate, with any out-of-plane movement of the proof mass in response to a sensed acceleration being optically detected using transmission gratings located about an outer edge of the proof mass to generate a diffracted light pattern which changes with the out-of-plane movement of the proof mass.

Turbulence Measurements from Compliant Moorings. Part II: Motion Correction

DOE PAGES

Kilcher, Levi F.; Thomson, Jim; Harding, Samuel; ...

2017-06-20

Acoustic Doppler velocimeters (ADVs) are a valuable tool for making high-precision measurements of turbulence, and moorings are a convenient and ubiquitous platform for making many kinds of measurements in the ocean. However, because of concerns that mooring motion can contaminate turbulence measurements and that acoustic Doppler profilers make middepth velocity measurements relatively easy, ADVs are not frequently deployed from moorings. This work demonstrates that inertial motion measurements can be used to reduce motion contamination from moored ADV velocity measurements. Three distinct mooring platforms were deployed in a tidal channel with inertial-motion-sensor-equipped ADVs. In each case, motion correction based on themore » inertial measurements reduces mooring motion contamination of velocity measurements. The spectra from these measurements are consistent with other measurements in tidal channels and have an f –5/3 slope at high frequencies - consistent with Kolmogorov's theory of isotropic turbulence. Motion correction also improves estimates of cross spectra and Reynolds stresses. A comparison of turbulence dissipation with flow speed and turbulence production indicates a bottom boundary layer production-dissipation balance during ebb and flood that is consistent with the strong tidal forcing at the site. Finally, these results indicate that inertial-motion-sensor-equipped ADVs are a valuable new tool for making high-precision turbulence measurements from moorings.« less

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

Kilcher, Levi F.; Thomson, Jim; Harding, Samuel

Acoustic Doppler velocimeters (ADVs) are a valuable tool for making high-precision measurements of turbulence, and moorings are a convenient and ubiquitous platform for making many kinds of measurements in the ocean. However, because of concerns that mooring motion can contaminate turbulence measurements and that acoustic Doppler profilers make middepth velocity measurements relatively easy, ADVs are not frequently deployed from moorings. This work demonstrates that inertial motion measurements can be used to reduce motion contamination from moored ADV velocity measurements. Three distinct mooring platforms were deployed in a tidal channel with inertial-motion-sensor-equipped ADVs. In each case, motion correction based on themore » inertial measurements reduces mooring motion contamination of velocity measurements. The spectra from these measurements are consistent with other measurements in tidal channels and have an f –5/3 slope at high frequencies - consistent with Kolmogorov's theory of isotropic turbulence. Motion correction also improves estimates of cross spectra and Reynolds stresses. A comparison of turbulence dissipation with flow speed and turbulence production indicates a bottom boundary layer production-dissipation balance during ebb and flood that is consistent with the strong tidal forcing at the site. Finally, these results indicate that inertial-motion-sensor-equipped ADVs are a valuable new tool for making high-precision turbulence measurements from moorings.« less

Kalman-Filter-Based Orientation Determination Using Inertial/Magnetic Sensors: Observability Analysis and Performance Evaluation

PubMed Central

Sabatini, Angelo Maria

2011-01-01

In this paper we present a quaternion-based Extended Kalman Filter (EKF) for estimating the three-dimensional orientation of a rigid body. The EKF exploits the measurements from an Inertial Measurement Unit (IMU) that is integrated with a tri-axial magnetic sensor. Magnetic disturbances and gyro bias errors are modeled and compensated by including them in the filter state vector. We employ the observability rank criterion based on Lie derivatives to verify the conditions under which the nonlinear system that describes the process of motion tracking by the IMU is observable, namely it may provide sufficient information for performing the estimation task with bounded estimation errors. The observability conditions are that the magnetic field, perturbed by first-order Gauss-Markov magnetic variations, and the gravity vector are not collinear and that the IMU is subject to some angular motions. Computer simulations and experimental testing are presented to evaluate the algorithm performance, including when the observability conditions are critical. PMID:22163689

PL-VIO: Tightly-Coupled Monocular Visual–Inertial Odometry Using Point and Line Features

PubMed Central

Zhao, Ji; Guo, Yue; He, Wenhao; Yuan, Kui

2018-01-01

To address the problem of estimating camera trajectory and to build a structural three-dimensional (3D) map based on inertial measurements and visual observations, this paper proposes point–line visual–inertial odometry (PL-VIO), a tightly-coupled monocular visual–inertial odometry system exploiting both point and line features. Compared with point features, lines provide significantly more geometrical structure information on the environment. To obtain both computation simplicity and representational compactness of a 3D spatial line, Plücker coordinates and orthonormal representation for the line are employed. To tightly and efficiently fuse the information from inertial measurement units (IMUs) and visual sensors, we optimize the states by minimizing a cost function which combines the pre-integrated IMU error term together with the point and line re-projection error terms in a sliding window optimization framework. The experiments evaluated on public datasets demonstrate that the PL-VIO method that combines point and line features outperforms several state-of-the-art VIO systems which use point features only. PMID:29642648

A Hybrid Indoor Localization and Navigation System with Map Matching for Pedestrians Using Smartphones.

PubMed

Tian, Qinglin; Salcic, Zoran; Wang, Kevin I-Kai; Pan, Yun

2015-12-05

Pedestrian dead reckoning is a common technique applied in indoor inertial navigation systems that is able to provide accurate tracking performance within short distances. Sensor drift is the main bottleneck in extending the system to long-distance and long-term tracking. In this paper, a hybrid system integrating traditional pedestrian dead reckoning based on the use of inertial measurement units, short-range radio frequency systems and particle filter map matching is proposed. The system is a drift-free pedestrian navigation system where position error and sensor drift is regularly corrected and is able to provide long-term accurate and reliable tracking. Moreover, the whole system is implemented on a commercial off-the-shelf smartphone and achieves real-time positioning and tracking performance with satisfactory accuracy.

Airborne Digital Sensor System and GPS-aided inertial technology for direct geopositioning in rough terrain

USGS Publications Warehouse

Sanchez, Richard D.

2004-01-01

High-resolution airborne digital cameras with onboard data collection based on the Global Positioning System (GPS) and inertial navigation systems (INS) technology may offer a real-time means to gather accurate topographic map information by reducing ground control and eliminating aerial triangulation. Past evaluations of this integrated system over relatively flat terrain have proven successful. The author uses Emerge Digital Sensor System (DSS) combined with Applanix Corporation?s Position and Orientation Solutions for Direct Georeferencing to examine the positional mapping accuracy in rough terrain. The positional accuracy documented in this study did not meet large-scale mapping requirements owing to an apparent system mechanical failure. Nonetheless, the findings yield important information on a new approach for mapping in Antarctica and other remote or inaccessible areas of the world.

Effects of vibration on inertial wind-tunnel model attitude measurement devices

NASA Technical Reports Server (NTRS)

Young, Clarence P., Jr.; Buehrle, Ralph D.; Balakrishna, S.; Kilgore, W. Allen

1994-01-01

Results of an experimental study of a wind tunnel model inertial angle-of-attack sensor response to a simulated dynamic environment are presented. The inertial device cannot distinguish between the gravity vector and the centrifugal accelerations associated with wind tunnel model vibration, this situation results in a model attitude measurement bias error. Significant bias error in model attitude measurement was found for the model system tested. The model attitude bias error was found to be vibration mode and amplitude dependent. A first order correction model was developed and used for estimating attitude measurement bias error due to dynamic motion. A method for correcting the output of the model attitude inertial sensor in the presence of model dynamics during on-line wind tunnel operation is proposed.

Spacecraft attitude calibration/verification baseline study

NASA Technical Reports Server (NTRS)

Chen, L. C.

1981-01-01

A baseline study for a generalized spacecraft attitude calibration/verification system is presented. It can be used to define software specifications for three major functions required by a mission: the pre-launch parameter observability and data collection strategy study; the in-flight sensor calibration; and the post-calibration attitude accuracy verification. Analytical considerations are given for both single-axis and three-axis spacecrafts. The three-axis attitudes considered include the inertial-pointing attitudes, the reference-pointing attitudes, and attitudes undergoing specific maneuvers. The attitude sensors and hardware considered include the Earth horizon sensors, the plane-field Sun sensors, the coarse and fine two-axis digital Sun sensors, the three-axis magnetometers, the fixed-head star trackers, and the inertial reference gyros.

A Novel Angle Computation and Calibration Algorithm of Bio-Inspired Sky-Light Polarization Navigation Sensor

PubMed Central

Xian, Zhiwen; Hu, Xiaoping; Lian, Junxiang; Zhang, Lilian; Cao, Juliang; Wang, Yujie; Ma, Tao

2014-01-01

Navigation plays a vital role in our daily life. As traditional and commonly used navigation technologies, Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) can provide accurate location information, but suffer from the accumulative error of inertial sensors and cannot be used in a satellite denied environment. The remarkable navigation ability of animals shows that the pattern of the polarization sky can be used for navigation. A bio-inspired POLarization Navigation Sensor (POLNS) is constructed to detect the polarization of skylight. Contrary to the previous approach, we utilize all the outputs of POLNS to compute input polarization angle, based on Least Squares, which provides optimal angle estimation. In addition, a new sensor calibration algorithm is presented, in which the installation angle errors and sensor biases are taken into consideration. Derivation and implementation of our calibration algorithm are discussed in detail. To evaluate the performance of our algorithms, simulation and real data test are done to compare our algorithms with several exiting algorithms. Comparison results indicate that our algorithms are superior to the others and are more feasible and effective in practice. PMID:25225872

Activity classification based on inertial and barometric pressure sensors at different anatomical locations.

PubMed

Moncada-Torres, A; Leuenberger, K; Gonzenbach, R; Luft, A; Gassert, R

2014-07-01

Miniature, wearable sensor modules are a promising technology to monitor activities of daily living (ADL) over extended periods of time. To assure both user compliance and meaningful results, the selection and placement site of sensors requires careful consideration. We investigated these aspects for the classification of 16 ADL in 6 healthy subjects under laboratory conditions using ReSense, our custom-made inertial measurement unit enhanced with a barometric pressure sensor used to capture activity-related altitude changes. Subjects wore a module on each wrist and ankle, and one on the trunk. Activities comprised whole body movements as well as gross and dextrous upper-limb activities. Wrist-module data outperformed the other locations for the three activity groups. Specifically, overall classification accuracy rates of almost 93% and more than 95% were achieved for the repeated holdout and user-specific validation methods, respectively, for all 16 activities. Including the altitude profile resulted in a considerable improvement of up to 20% in the classification accuracy for stair ascent and descent. The gyroscopes provided no useful information for activity classification under this scheme. The proposed sensor setting could allow for robust long-term activity monitoring with high compliance in different patient populations.

Adaptive Estimation and Heuristic Optimization of Nonlinear Spacecraft Attitude Dynamics

DTIC Science & Technology

2016-09-15

Algorithm GPS Global Positioning System HOUF Higher Order Unscented Filter IC initial conditions IMM Interacting Multiple Model IMU Inertial Measurement Unit ...sources ranging from inertial measurement units to star sensors are used to construct observations for attitude estimation algorithms. The sensor...parameters. A single vector measurement will provide two independent parameters, as a unit vector constraint removes a DOF making the problem underdetermined

Mobile Jump Assessment (mJump): A Descriptive and Inferential Study.

PubMed

Mateos-Angulo, Alvaro; Galán-Mercant, Alejandro; Cuesta-Vargas, Antonio

2015-08-26

Vertical jump tests are used in athletics and rehabilitation to measure physical performance in people of different age ranges and fitness. Jumping ability can be analyzed through different variables, and the most commonly used are fly time and jump height. They can be obtained by a variety of measuring devices, but most are limited to laboratory use only. The current generation of smartphones contains inertial sensors that are able to record kinematic variables for human motion analysis, since they are tools for easy access and portability for clinical use. The aim of this study was to describe and analyze the kinematics characteristics using the inertial sensor incorporated in the iPhone 4S, the lower limbs strength through a manual dynamometer, and the jump variables obtained with a contact mat in the squat jump and countermovement jump tests (fly time and jump height) from a cohort of healthy people. A cross sectional study was conducted on a population of healthy young adults. Twenty-seven participants performed three trials (n=81 jumps) of squat jump and countermovement jump tests. Acceleration variables were measured through a smartphone's inertial sensor. Additionally, jump variables from a contact mat and lower limbs dynamometry were collected. In the present study, the kinematic variables derived from acceleration through the inertial sensor of a smartphone iPhone 4S, dynamometry of lower limbs with a handheld dynamometer, and the height and flight time with a contact mat have been described in vertical jump tests from a cohort of young healthy subjects. The development of the execution has been described, examined and identified in a squat jump test and countermovement jump test under acceleration variables that were obtained with the smartphone. The built-in iPhone 4S inertial sensor is able to measure acceleration variables while performing vertical jump tests for the squat jump and countermovement jump in healthy young adults. The acceleration kinematics variables derived from the smartphone's inertial sensor are higher in the countermovement jump test than the squat jump test. ©Alvaro Mateos-Angulo, Alejandro Galán-Mercant, Antonio Cuesta-Vargas. Originally published in JMIR Rehabilitation and Assistive Technology (http://rehab.jmir.org), 26.08.2015.

Automatic Identification of Subtechniques in Skating-Style Roller Skiing Using Inertial Sensors

PubMed Central

Sakurai, Yoshihisa; Fujita, Zenya; Ishige, Yusuke

2016-01-01

This study aims to develop and validate an automated system for identifying skating-style cross-country subtechniques using inertial sensors. In the first experiment, the performance of a male cross-country skier was used to develop an automated identification system. In the second, eight male and seven female college cross-country skiers participated to validate the developed identification system. Each subject wore inertial sensors on both wrists and both roller skis, and a small video camera on a backpack. All subjects skied through a 3450 m roller ski course using a skating style at their maximum speed. The adopted subtechniques were identified by the automated method based on the data obtained from the sensors, as well as by visual observations from a video recording of the same ski run. The system correctly identified 6418 subtechniques from a total of 6768 cycles, which indicates an accuracy of 94.8%. The precisions of the automatic system for identifying the V1R, V1L, V2R, V2L, V2AR, and V2AL subtechniques were 87.6%, 87.0%, 97.5%, 97.8%, 92.1%, and 92.0%, respectively. Most incorrect identification cases occurred during a subtechnique identification that included a transition and turn event. Identification accuracy can be improved by separately identifying transition and turn events. This system could be used to evaluate each skier’s subtechniques in course conditions. PMID:27049388

Integrated micro-electro-mechanical sensor development for inertial applications

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

Allen, J.J.; Kinney, R.D.; Sarsfield, J.

Electronic sensing circuitry and micro electro mechanical sense elements can be integrated to produce inertial instruments for applications unheard of a few years ago. This paper will describe the Sandia M3EMS fabrication process, inertial instruments that have been fabricated, and the results of initial characterization tests of micro-machined accelerometers.

Dual matter-wave inertial sensors in weightlessness

PubMed Central

Barrett, Brynle; Antoni-Micollier, Laura; Chichet, Laure; Battelier, Baptiste; Lévèque, Thomas; Landragin, Arnaud; Bouyer, Philippe

2016-01-01

Quantum technology based on cold-atom interferometers is showing great promise for fields such as inertial sensing and fundamental physics. However, the finite free-fall time of the atoms limits the precision achievable on Earth, while in space interrogation times of many seconds will lead to unprecedented sensitivity. Here we realize simultaneous 87Rb–39K interferometers capable of operating in the weightless environment produced during parabolic flight. Large vibration levels (10−2 g Hz−1/2), variations in acceleration (0–1.8 g) and rotation rates (5° s−1) onboard the aircraft present significant challenges. We demonstrate the capability of our correlated quantum system by measuring the Eötvös parameter with systematic-limited uncertainties of 1.1 × 10−3 and 3.0 × 10−4 during standard- and microgravity, respectively. This constitutes a fundamental test of the equivalence principle using quantum sensors in a free-falling vehicle. Our results are applicable to inertial navigation, and can be extended to the trajectory of a satellite for future space missions. PMID:27941928

An ATP System for Deep-Space Optical Communication

NASA Technical Reports Server (NTRS)

Lee, Shinhak; Irtuzm Gerardi; Alexander, James

2008-01-01

An acquisition, tracking, and pointing (ATP) system is proposed for aiming an optical-communications downlink laser beam from deep space. In providing for a direction reference, the concept exploits the mature technology of star trackers to eliminate the need for a costly and potentially hazardous laser beacon. The system would include one optical and two inertial sensors, each contributing primarily to a different portion of the frequency spectrum of the pointing signal: a star tracker (<10 Hz), a gyroscope (<50 Hz), and a precise fluid-rotor inertial angular-displacement sensor (sometimes called, simply, "angle sensor") for the frequency range >50 Hz. The outputs of these sensors would be combined in an iterative averaging process to obtain high-bandwidth, high-accuracy pointing knowledge. The accuracy of pointing knowledge obtainable by use of the system was estimated on the basis of an 8-cm-diameter telescope and known parameters of commercially available star trackers and inertial sensors: The single-axis pointing-knowledge error was found to be characterized by a standard deviation of 150 nanoradians - below the maximum value (between 200 and 300 nanoradians) likely to be tolerable in deep-space optical communications.

A Micromechanical INS/GPS System for Small Satellites

NASA Technical Reports Server (NTRS)

Barbour, N.; Brand, T.; Haley, R.; Socha, M.; Stoll, J.; Ward, P.; Weinberg, M.

1995-01-01

The cost and complexity of large satellite space missions continue to escalate. To reduce costs, more attention is being directed toward small lightweight satellites where future demand is expected to grow dramatically. Specifically, micromechanical inertial systems and microstrip global positioning system (GPS) antennas incorporating flip-chip bonding, application specific integrated circuits (ASIC) and MCM technologies will be required. Traditional microsatellite pointing systems do not employ active control. Many systems allow the satellite to point coarsely using gravity gradient, then attempt to maintain the image on the focal plane with fast-steering mirrors. Draper's approach is to actively control the line of sight pointing by utilizing on-board attitude determination with micromechanical inertial sensors and reaction wheel control actuators. Draper has developed commercial and tactical-grade micromechanical inertial sensors, The small size, low weight, and low cost of these gyroscopes and accelerometers enable systems previously impractical because of size and cost. Evolving micromechanical inertial sensors can be applied to closed-loop, active control of small satellites for micro-radian precision-pointing missions. An inertial reference feedback control loop can be used to determine attitude and line of sight jitter to provide error information to the controller for correction. At low frequencies, the error signal is provided by GPS. At higher frequencies, feedback is provided by the micromechanical gyros. This blending of sensors provides wide-band sensing from dc to operational frequencies. First order simulation has shown that the performance of existing micromechanical gyros, with integrated GPS, is feasible for a pointing mission of 10 micro-radians of jitter stability and approximately 1 milli-radian absolute error, for a satellite with 1 meter antenna separation. Improved performance micromechanical sensors currently under development will be suitable for a range of micro-nano-satellite applications.

Integral resonator gyroscope

NASA Technical Reports Server (NTRS)

Shcheglov, Kirill V. (Inventor); Challoner, A. Dorian (Inventor); Hayworth, Ken J. (Inventor); Wiberg, Dean V. (Inventor); Yee, Karl Y. (Inventor)

2008-01-01

The present invention discloses an inertial sensor having an integral resonator. A typical sensor comprises a planar mechanical resonator for sensing motion of the inertial sensor and a case for housing the resonator. The resonator and a wall of the case are defined through an etching process. A typical method of producing the resonator includes etching a baseplate, bonding a wafer to the etched baseplate, through etching the wafer to form a planar mechanical resonator and the wall of the case and bonding an end cap wafer to the wall to complete the case.

Effective Viscosity of Liquid Helium4 - With Minute He3 Impurity at Temperatures from 0.05K to 2K and at Velocities Spanning the Critical Velocities.

DTIC Science & Technology

1981-03-01

meticulous and well thought out designs and work brought excellent solutions to our many electrical and mechanical problems. He is a gifted person with many...thorough study of the gyro design , as well as other low temperature sensors, is now called for. 1.4 Low Temperature Inertial Sensors The precision of...can only begin to imagine some of the forms that low temperature inertial sensors could take in the hands of creative design and development engineers

An experimental protocol for the definition of upper limb anatomical frames on children using magneto-inertial sensors.

PubMed

Ricci, L; Formica, D; Tamilia, E; Taffoni, F; Sparaci, L; Capirci, O; Guglielmelli, E

2013-01-01

Motion capture based on magneto-inertial sensors is a technology enabling data collection in unstructured environments, allowing "out of the lab" motion analysis. This technology is a good candidate for motion analysis of children thanks to the reduced weight and size as well as the use of wireless communication that has improved its wearability and reduced its obtrusivity. A key issue in the application of such technology for motion analysis is its calibration, i.e. a process that allows mapping orientation information from each sensor to a physiological reference frame. To date, even if there are several calibration procedures available for adults, no specific calibration procedures have been developed for children. This work addresses this specific issue presenting a calibration procedure for motion capture of thorax and upper limbs on healthy children. Reported results suggest comparable performance with similar studies on adults and emphasize some critical issues, opening the way to further improvements.

The inertial attitude augmentation for ambiguity resolution in SF/SE-GNSS attitude determination.

PubMed

Zhu, Jiancheng; Hu, Xiaoping; Zhang, Jingyu; Li, Tao; Wang, Jinling; Wu, Meiping

2014-06-26

The Unaided Single Frequency/Single Epoch Global Navigation Satellite System (SF/SE GNSS) model is the most challenging scenario for ambiguity resolution in the GNSS attitude determination application. To improve the performance of SF/SE-GNSS ambiguity resolution without excessive cost, the Micro-Electro-Mechanical System Inertial Measurement Unit (MEMS-IMU) is a proper choice for the auxiliary sensor that carries out the inertial attitude augmentation. Firstly, based on the SF/SE-GNSS compass model, the Inertial Derived Baseline Vector (IDBV) is defined to connect the MEMS-IMU attitude measurement with the SF/SE-GNSS ambiguity search space, and the mechanism of inertial attitude augmentation is revealed from the perspective of geometry. Then, through the quantitative description of model strength by Ambiguity Dilution of Precision (ADOP), two ADOPs are specified for the unaided SF/SE-GNSS compass model and its inertial attitude augmentation counterparts, respectively, and a sufficient condition is proposed for augmenting the SF/SE-GNSS model strength with inertial attitude measurement. Finally, in the framework of an integer aperture estimator with fixed failure rate, the performance of SF/SE-GNSS ambiguity resolution with inertial attitude augmentation is analyzed when the model strength is varying from strong to weak. The simulation results show that, in the SF/SE-GNSS attitude determination application, MEMS-IMU can satisfy the requirements of ambiguity resolution with inertial attitude augmentation.

The Inertial Attitude Augmentation for Ambiguity Resolution in SF/SE-GNSS Attitude Determination

PubMed Central

Zhu, Jiancheng; Hu, Xiaoping; Zhang, Jingyu; Li, Tao; Wang, Jinling; Wu, Meiping

2014-01-01

The Unaided Single Frequency/Single Epoch Global Navigation Satellite System (SF/SE GNSS) model is the most challenging scenario for ambiguity resolution in the GNSS attitude determination application. To improve the performance of SF/SE-GNSS ambiguity resolution without excessive cost, the Micro-Electro-Mechanical System Inertial Measurement Unit (MEMS-IMU) is a proper choice for the auxiliary sensor that carries out the inertial attitude augmentation. Firstly, based on the SF/SE-GNSS compass model, the Inertial Derived Baseline Vector (IDBV) is defined to connect the MEMS-IMU attitude measurement with the SF/SE-GNSS ambiguity search space, and the mechanism of inertial attitude augmentation is revealed from the perspective of geometry. Then, through the quantitative description of model strength by Ambiguity Dilution of Precision (ADOP), two ADOPs are specified for the unaided SF/SE-GNSS compass model and its inertial attitude augmentation counterparts, respectively, and a sufficient condition is proposed for augmenting the SF/SE-GNSS model strength with inertial attitude measurement. Finally, in the framework of an integer aperture estimator with fixed failure rate, the performance of SF/SE-GNSS ambiguity resolution with inertial attitude augmentation is analyzed when the model strength is varying from strong to weak. The simulation results show that, in the SF/SE-GNSS attitude determination application, MEMS-IMU can satisfy the requirements of ambiguity resolution with inertial attitude augmentation. PMID:24971472

Weighted fusion of depth and inertial data to improve view invariance for real-time human action recognition

NASA Astrophysics Data System (ADS)

Chen, Chen; Hao, Huiyan; Jafari, Roozbeh; Kehtarnavaz, Nasser

2017-05-01

This paper presents an extension to our previously developed fusion framework [10] involving a depth camera and an inertial sensor in order to improve its view invariance aspect for real-time human action recognition applications. A computationally efficient view estimation based on skeleton joints is considered in order to select the most relevant depth training data when recognizing test samples. Two collaborative representation classifiers, one for depth features and one for inertial features, are appropriately weighted to generate a decision making probability. The experimental results applied to a multi-view human action dataset show that this weighted extension improves the recognition performance by about 5% over equally weighted fusion deployed in our previous fusion framework.

I.C.E.: a transportable atomic inertial sensor for test in microgravity

NASA Astrophysics Data System (ADS)

Nyman, R. A.; Varoquaux, G.; Clement, J.-F.; Bouyer, P.; Santarelli, G.; Pereira Dos Santos, F.; Clairon, A.; Landragin, A.; Chambon, D.; Lienhart, F.; Boussen, S.; Bresson, A.

2017-11-01

We present our the construction of an atom interferometer for inertial sensing in microgravity, as part of the I.C.E. (Interferometrie Coherente pour l'Espace) collaboration. On-board laser systems have been developed based on fibre-optic components, which are insensitive to mechanical vibrations and acoustic noise, have sub-MHz linewidth, and remain frequency stabilised for weeks at a time. A compact, transportable vacuum system has been built, and used for laser cooling and magneto-optical trapping. We will use a mixture of quantum degenerate gases, bosonic 87Rb and fermionic 40K, in order to find the optimal conditions for precision and sensitivity of inertial measurements. Microgravity will be realised in parabolic flights lasting up to 20s in an Airbus.

The research of a new data glove based on MARG sensor and magnetic localization technology

NASA Astrophysics Data System (ADS)

Ding, Yi; Gao, Tongyue; Wu, Ye; Zhu, Shihao

2018-04-01

The human hand gesture can record and reproduce the posture and action information of the hand, which is of great significance to people's production and life. This paper has improved the existing data gloves based on micro inertial technology, and integrates the magnetic field localization method into finger gesture measurements. The strap down inertial navigation technology and the magnetic localization technology are combined in this paper to make the advantages complement each other, and a low cost and high degree of freedom of data gloves are put forward to realize the way of data gloves in the past.

The Use of Wearable Inertial Motion Sensors in Human Lower Limb Biomechanics Studies: A Systematic Review

PubMed Central

Fong, Daniel Tik-Pui; Chan, Yue-Yan

2010-01-01

Wearable motion sensors consisting of accelerometers, gyroscopes and magnetic sensors are readily available nowadays. The small size and low production costs of motion sensors make them a very good tool for human motions analysis. However, data processing and accuracy of the collected data are important issues for research purposes. In this paper, we aim to review the literature related to usage of inertial sensors in human lower limb biomechanics studies. A systematic search was done in the following search engines: ISI Web of Knowledge, Medline, SportDiscus and IEEE Xplore. Thirty nine full papers and conference abstracts with related topics were included in this review. The type of sensor involved, data collection methods, study design, validation methods and its applications were reviewed. PMID:22163542

The use of wearable inertial motion sensors in human lower limb biomechanics studies: a systematic review.

PubMed

Fong, Daniel Tik-Pui; Chan, Yue-Yan

2010-01-01

Wearable motion sensors consisting of accelerometers, gyroscopes and magnetic sensors are readily available nowadays. The small size and low production costs of motion sensors make them a very good tool for human motions analysis. However, data processing and accuracy of the collected data are important issues for research purposes. In this paper, we aim to review the literature related to usage of inertial sensors in human lower limb biomechanics studies. A systematic search was done in the following search engines: ISI Web of Knowledge, Medline, SportDiscus and IEEE Xplore. Thirty nine full papers and conference abstracts with related topics were included in this review. The type of sensor involved, data collection methods, study design, validation methods and its applications were reviewed.

Integrated inertial stellar attitude sensor

NASA Technical Reports Server (NTRS)

Brady, Tye M. (Inventor); Kourepenis, Anthony S. (Inventor); Wyman, Jr., William F. (Inventor)

2007-01-01

An integrated inertial stellar attitude sensor for an aerospace vehicle includes a star camera system, a gyroscope system, a controller system for synchronously integrating an output of said star camera system and an output of said gyroscope system into a stream of data, and a flight computer responsive to said stream of data for determining from the star camera system output and the gyroscope system output the attitude of the aerospace vehicle.

Pose and Wind Estimation for Autonomous Parafoils

DTIC Science & Technology

2014-09-01

Communications GT Georgia Institute of Technology IDVD Inverse Dynamics in the Virtual Domain IMU inertial measurement unit INRIA Institut National de Recherche en...sensor. The method used is a nonlinear estimator that combines the visual sensor measurements with those of an inertial measurement unit ( IMU ) on... isolated on the left side of the equation. On the other hand, when the measurement equation of (3.27) is implemented, the probabil- 58 ity

Musical Stairs: A motivational therapy tool for children with disabilities featuring automated detection of stair-climbing gait events via inertial sensors.

PubMed

Khan, Ajmal; Biddiss, Elaine

2017-02-01

Stair-climbing is a key component of rehabilitation therapies for children with physical disabilities. This paper reports on the design of a system, Musical Stairs, to provide auditory feedback during stair-climbing therapies. Musical Stairs is composed of two foot-mounted inertial sensors, a step detection algorithm, and an auditory feedback response. In Phase 1, we establish its clinical feasibility via a Wizard-of-Oz AB/BA cross-over design with 17 children, aged 4-6 years, having diverse diagnoses and gait abilities. Self-, therapist- and blinded-observer reports indicated increased motivation with auditory feedback. Phase 2 describes the construction of a database comprised of synchronized video and inertial data associated with 1568 steps up and down stairs completed by 26 children aged 4-6 years with diverse diagnoses and gait. Lastly, in Phase 3, data from 18 children in the database were used to train a rule-based step detection algorithm based on local minima in the acceleration profile and the foot's swing angle. A step detection rate of 96% [SD=3%] and false positive rate of 6% [SD=5%] were achieved with an independent test set (n=8). Recommendations for future development and evaluation are discussed. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

The Inertial Stellar Compass (ISC): A Multifunction, Low Power, Attitude Determination Technology Breakthrough

NASA Technical Reports Server (NTRS)

Bauer, Frank H. (Technical Monitor); Dennehy, Neil; Gambino, Joel; Maynard, Andrew; Brady, T.; Buckley, S.; Zinchuk, J.

2003-01-01

The Inertial Stellar Compass (ISC) is a miniature, low power, stellar inertial attitude determination system with an accuracy of better than 0.1 degree (1 sigma) in three axes. The ISC consumes only 3.5 Watts of power and is contained in a 2.5 kg package. With its embedded on-board processor, the ISC provides attitude quaternion information and has Lost-in-Space (LIS) initialization capability. The attitude accuracy and LIS capability are provided by combining a wide field of view Active Pixel Sensor (APS) star camera and Micro- ElectroMechanical System (MEMS) inertial sensor information in an integrated sensor system. The performance and small form factor make the ISC a useful sensor for a wide range of missions. In particular, the ISC represents an enabling, fully integrated, micro-satellite attitude determination system. Other applications include using the ISC as a single sensor solution for attitude determination on medium performance spacecraft and as a bolt on independent safe-hold sensor or coarse acquisition sensor for many other spacecraft. NASA's New Millennium Program (NMP) has selected the ISC technology for a Space Technology 6 (ST6) flight validation experiment scheduled for 2004. NMP missions, such a s ST6, are intended to validate advanced technologies that have not flown in space in order to reduce the risk associated with their infusion into future NASA missions. This paper describes the design, operation, and performance of the ISC and outlines the technology validation plan. A number of mission applications for the ISC technology are highlighted, both for the baseline ST6 ISC configuration and more ambitious applications where ISC hardware and software modifications would be required. These applications demonstrate the wide range of Space and Earth Science missions that would benefit from infusion of the ISC technology.

Inertial Orientation Trackers with Drift Compensation

NASA Technical Reports Server (NTRS)

Foxlin, Eric M.

2008-01-01

A class of inertial-sensor systems with drift compensation has been invented for use in measuring the orientations of human heads (and perhaps other, similarly sized objects). These systems can be designed to overcome some of the limitations of prior orientation-measuring systems that are based, variously, on magnetic, optical, mechanical-linkage, and acoustical principles. The orientation signals generated by the systems of this invention could be used for diverse purposes, including controlling head-orientation-dependent virtual reality visual displays or enabling persons whose limbs are paralyzed to control machinery by means of head motions. The inventive concept admits to variations too numerous to describe here, making it necessary to limit this description to a typical system, the selected aspects of which are illustrated in the figure. A set of sensors is mounted on a bracket on a band or a cap that gently but firmly grips the wearer s head to be tracked. Among the sensors are three drift-sensitive rotationrate sensors (e.g., integrated-circuit angular- rate-measuring gyroscopes), which put out DC voltages nominally proportional to the rates of rotation about their sensory axes. These sensors are mounted in mutually orthogonal orientations for measuring rates of rotation about the roll, pitch, and yaw axes of the wearer s head. The outputs of these rate sensors are conditioned and digitized, and the resulting data are fed to an integrator module implemented in software in a digital computer. In the integrator module, the angular-rate signals are jointly integrated by any of several established methods to obtain a set of angles that represent approximately the orientation of the head in an external, inertial coordinate system. Because some drift is always present as a component of an angular position computed by integrating the outputs of angular-rate sensors, the orientation signal is processed further in a drift-compensator software module.

Validation of a commercial inertial sensor system for spatiotemporal gait measurements in children.

PubMed

Lanovaz, Joel L; Oates, Alison R; Treen, Tanner T; Unger, Janelle; Musselman, Kristin E

2017-01-01

Although inertial sensor systems are becoming a popular tool for gait analysis in both healthy and pathological adult populations, there are currently no data on the validity of these systems for use with children. The purpose of this study was to validate spatiotemporal data from a commercial inertial sensor system (MobilityLab) in typically-developing children. Data from 10 children (5 males; 3.0-8.3 years, mean=5.1) were collected simultaneously from MobilityLab and 3D motion capture during gait at self-selected and fast walking speeds. Spatiotemporal parameters were compared between the two methods using a Bland-Altman method. The results indicate that, while the temporal gait measurements were similar between the two systems, MobilityLab demonstrated a consistent bias with respect to measurement of the spatial data (stride length). This error is likely due to differences in relative leg length and gait characteristics in children compared to the MobilityLab adult reference population used to develop the stride length algorithm. A regression-based equation was developed based on the current data to correct the MobilityLab stride length output. The correction was based on leg length, stride time, and shank range-of-motion, each of which were independently associated with stride length. Once the correction was applied, all of the spatiotemporal parameters evaluated showed good agreement. The results of this study indicate that MobilityLab is a valid tool for gait analysis in typically-developing children. Further research is needed to determine the efficacy of this system for use in children suffering from pathologies that impact gait mechanics. Copyright © 2016 Elsevier B.V. All rights reserved.

An Inertial Dual-State State Estimator for Precision Planetary Landing with Hazard Detection and Avoidance

NASA Technical Reports Server (NTRS)

Bishop, Robert H.; DeMars, Kyle; Trawny, Nikolas; Crain, Tim; Hanak, Chad; Carson, John M.; Christian, John

2016-01-01

The navigation filter architecture successfully deployed on the Morpheus flight vehicle is presented. The filter was developed as a key element of the NASA Autonomous Landing and Hazard Avoidance Technology (ALHAT) project and over the course of 15 free fights was integrated into the Morpheus vehicle, operations, and flight control loop. Flight testing completed by demonstrating autonomous hazard detection and avoidance, integration of an altimeter, surface relative velocity (velocimeter) and hazard relative navigation (HRN) measurements into the onboard dual-state inertial estimator Kalman flter software, and landing within 2 meters of the vertical testbed GPS-based navigation solution at the safe landing site target. Morpheus followed a trajectory that included an ascent phase followed by a partial descent-to-landing, although the proposed filter architecture is applicable to more general planetary precision entry, descent, and landings. The main new contribution is the incorporation of a sophisticated hazard relative navigation sensor-originally intended to locate safe landing sites-into the navigation system and employed as a navigation sensor. The formulation of a dual-state inertial extended Kalman filter was designed to address the precision planetary landing problem when viewed as a rendezvous problem with an intended landing site. For the required precision navigation system that is capable of navigating along a descent-to-landing trajectory to a precise landing, the impact of attitude errors on the translational state estimation are included in a fully integrated navigation structure in which translation state estimation is combined with attitude state estimation. The map tie errors are estimated as part of the process, thereby creating a dual-state filter implementation. Also, the filter is implemented using inertial states rather than states relative to the target. External measurements include altimeter, velocimeter, star camera, terrain relative navigation sensor, and a hazard relative navigation sensor providing information regarding hazards on a map generated on-the-fly.

SeaVipers- Computer Vision and Inertial Position/Reference Sensor System (CVIPRSS)

DTIC Science & Technology

2015-08-01

uses an Inertial Measurement Unit (IMU) to detect changes in roll , pitch, and yaw (x-, y-, and z-axis movement). We use a 9DOF Razor IMU from SparkFun... inertial measurement unit (IMU) and cameras that are hardware synchronized to provide close coupling. Several fast food companies, Internet giants like...light cameras [32]. 4.1.4 Inertial Measurement Unit To assist the PTU in video stabilization for the camera and aiming the rangefinder, Sea- Vipers

Validation of Inertial and Optical Navigation Techniques for Space Applications with UAVS

NASA Astrophysics Data System (ADS)

Montaño, J.; Wis, M.; Pulido, J. A.; Latorre, A.; Molina, P.; Fernández, E.; Angelats, E.; Colomina, I.

2015-09-01

PERIGEO is an R&D project, funded by the INNPRONTA 2011-2014 programme from Spanish CDTI, which aims to investigate the use of UAV technologies and processes for the validation of space oriented technologies. For this purpose, among different space missions and technologies, a set of activities for absolute and relative navigation are being carried out to deal with the attitude and position estimation problem from a temporal image sequence from a camera on the visible spectrum and/or Light Detection and Ranging (LIDAR) sensor. The process is covered entirely: from sensor measurements and data acquisition (images, LiDAR ranges and angles), data pre-processing (calibration and co-registration of camera and LIDAR data), features and landmarks extraction from the images and image/LiDAR-based state estimation. In addition to image processing area, classical navigation system based on inertial sensors is also included in the research. The reason of combining both approaches is to enable the possibility to keep navigation capability in environments or missions where the radio beacon or reference signal as the GNSS satellite is not available (as for example an atmospheric flight in Titan). The rationale behind the combination of those systems is that they complement each other. The INS is capable of providing accurate position, velocity and full attitude estimations at high data rates. However, they need an absolute reference observation to compensate the time accumulative errors caused by inertial sensor inaccuracies. On the other hand, imaging observables can provide absolute and relative positioning and attitude estimations. However they need that the sensor head is pointing toward ground (something that may not be possible if the carrying platform is maneuvering) to provide accurate estimations and they are not capable of provide some hundreds of Hz that can deliver an INS. This mutual complementarity has been observed in PERIGEO and because of this they are combined into one system. The inertial navigation system implemented in PERIGEO is based on a classical loosely coupled INS/GNSS approach that is very similar to the implementation of the INS/Imaging navigation system that is mentioned above. The activities envisaged in PERIGEO cover the algorithms development and validation and technology testing on UAVs under representative conditions. Past activities have covered the design and development of the algorithms and systems. This paper presents the most recent activities and results on the area of image processing for robust estimation within PERIGEO, which are related with the hardware platforms definition (including sensors) and its integration in UAVs. Results for the tests performed during the flight campaigns in representative outdoor environments will be also presented (at the time of the full paper submission the tests will be performed), as well as analyzed, together with a roadmap definition for future developments.

Characterizing Knee Loading Asymmetry in Individuals Following Anterior Cruciate Ligament Reconstruction Using Inertial Sensors

PubMed Central

Sigward, Susan M.; Chan, Ming-Sheng M.; Lin, Paige E.

2016-01-01

Limitations in the ability to identify knee extensor loading deficits during gait in individuals following anterior cruciate ligament reconstruction (ACLr) may underlie their persistence. A recent study suggested that shank angular velocity, directly output from inertial sensors, differed during gait between individuals post-ACLr and controls. However, it is not clear if this kinematic variable relates to knee moments calculated using joint kinematics and ground reaction forces. Heel rocker mechanics during loading response of gait, characterized by rapid shank rotation, require knee extensor control. Measures of shank angular velocity may be reflective of knee moments. This study investigated the relationship between shank angular velocity and knee extensor moment during gait in individuals (n=19) 96.7±16.8 days post-ACLr. Gait was assessed concurrently using inertial sensors and a marker-based motion system with force platforms. Peak angular velocity and knee extensor moment were strongly correlated (r=0.75, p<0.001) and between limb ratios of angular velocity predicted between limb ratios of extensor moment (r2=0.57 ,p<0.001) in the absence of between limb differences in spatiotemporal gait parameters. The strength of these relationships indicate that shank kinematic data offer meaningful information regarding knee loading and provide a potential alternative to full motion analysis systems for identification of altered knee loading following ACLr PMID:27395452

Android Platform for Realtime Gait Tracking Using Inertial Measurement Units.

PubMed

Aqueveque, Pablo; Sobarzo, Sergio; Saavedra, Francisco; Maldonado, Claudio; Gómez, Britam

2016-06-13

One of the most important movements performed by the humans is gait. Biomechanical Gait analysis is usually by optical capture systems. However, such systems are expensive and sensitive to light and obstacles. In order to reduce those costs a system based on Inertial Measurements Units (IMU) is proposed. IMU are a good option to make movement analisys indoor with a low post-processing data, allowing to connect those systems to an Android platform. The design is based on two elements: a) The IMU sensors and the b) Android device. The IMU sensor is simple, small (35 x 35 mm), portable and autonomous (7.8 hrs). A resolution of 0.01° in their measurements is obtained, and sends data via Bluetooth link. The Android application works for Android 4.2 or higher, and it is compatible with Bluetooth devices 2.0 or higher. Three IMU sensors send data to a Tablet wirelessly, in order to evaluate the angles evolution for each joint of the leg (hip, knee and ankle). This information is used to calculate gait index and evaluate the gait quality online during the physical therapist is working with the patient.

Model-based extended quaternion Kalman filter to inertial orientation tracking of arbitrary kinematic chains.

PubMed

Szczęsna, Agnieszka; Pruszowski, Przemysław

2016-01-01

Inertial orientation tracking is still an area of active research, especially in the context of out-door, real-time, human motion capture. Existing systems either propose loosely coupled tracking approaches where each segment is considered independently, taking the resulting drawbacks into account, or tightly coupled solutions that are limited to a fixed chain with few segments. Such solutions have no flexibility to change the skeleton structure, are dedicated to a specific set of joints, and have high computational complexity. This paper describes the proposal of a new model-based extended quaternion Kalman filter that allows for estimation of orientation based on outputs from the inertial measurements unit sensors. The filter considers interdependencies resulting from the construction of the kinematic chain so that the orientation estimation is more accurate. The proposed solution is a universal filter that does not predetermine the degree of freedom at the connections between segments of the model. To validation the motion of 3-segments single link pendulum captured by optical motion capture system is used. The next step in the research will be to use this method for inertial motion capture with a human skeleton model.

Utilizing Glove-Based Gestures and a Tactile Vest Display for Covert Communications and Robot Control

DTIC Science & Technology

2014-06-01

transmitted from a controller mechanism that contains inertial measurement unit ( IMU ) sensors to sense rotation and acceleration of movement. Earlier...assets, and standard hand signal commands can be presented to human team members via a variety of modalities. IMU sensor technologies placed on the body...obstacle event (e.g., climbing, crawling, combat roll , running) and between obstacles (i.e., walking). The following analyses are for each task

An Improved Method for Dynamic Measurement of Deflections of the Vertical Based on the Maintenance of Attitude Reference

PubMed Central

Dai, Dongkai; Wang, Xingshu; Zhan, Dejun; Huang, Zongsheng

2014-01-01

A new method for dynamic measurement of deflections of the vertical (DOV) is proposed in this paper. The integration of an inertial navigation system (INS) and global navigation satellite system (GNSS) is constructed to measure the body's attitude with respect to the astronomical coordinates. Simultaneously, the attitude with respect to the geodetic coordinates is initially measured by a star sensor under quasi-static condition and then maintained by the laser gyroscope unit (LGU), which is composed of three gyroscopes in the INS, when the vehicle travels along survey lines. Deflections of the vertical are calculated by using the difference between the attitudes with respect to the geodetic coordinates and astronomical coordinates. Moreover, an algorithm for removing the trend error of the vertical deflections is developed with the aid of Earth Gravitational Model 2008 (EGM2008). In comparison with traditional methods, the new method required less accurate GNSS, because the dynamic acceleration calculation is avoided. The errors of inertial sensors are well resolved in the INS/GNSS integration, which is implemented by a Rauch–Tung–Striebel (RTS) smoother. In addition, a single-axis indexed INS is adopted to improve the observability of the system errors and to restrain the inertial sensor errors. The proposed method is validated by Monte Carlo simulations. The results show that deflections of the vertical can achieve a precision of better than 1″ for a single survey line. The proposed method can be applied to a gravimetry system based on a ground vehicle or ship with a speed lower than 25 m/s. PMID:25192311

An improved method for dynamic measurement of deflections of the vertical based on the maintenance of attitude reference.

PubMed

Dai, Dongkai; Wang, Xingshu; Zhan, Dejun; Huang, Zongsheng

2014-09-03

A new method for dynamic measurement of deflections of the vertical (DOV) is proposed in this paper. The integration of an inertial navigation system (INS) and global navigation satellite system (GNSS) is constructed to measure the body's attitude with respect to the astronomical coordinates. Simultaneously, the attitude with respect to the geodetic coordinates is initially measured by a star sensor under quasi-static condition and then maintained by the laser gyroscope unit (LGU), which is composed of three gyroscopes in the INS, when the vehicle travels along survey lines. Deflections of the vertical are calculated by using the difference between the attitudes with respect to the geodetic coordinates and astronomical coordinates. Moreover, an algorithm for removing the trend error of the vertical deflections is developed with the aid of Earth Gravitational Model 2008 (EGM2008). In comparison with traditional methods, the new method required less accurate GNSS, because the dynamic acceleration calculation is avoided. The errors of inertial sensors are well resolved in the INS/GNSS integration, which is implemented by a Rauch-Tung-Striebel (RTS) smoother. In addition, a single-axis indexed INS is adopted to improve the observability of the system errors and to restrain the inertial sensor errors. The proposed method is validated by Monte Carlo simulations. The results show that deflections of the vertical can achieve a precision of better than 1″ for a single survey line. The proposed method can be applied to a gravimetry system based on a ground vehicle or ship with a speed lower than 25 m/s.

The Additional Error of Inertial Sensors Induced by Hypersonic Flight Conditions

PubMed Central

Karachun, Volodimir; Mel’nick, Viktorij; Korobiichuk, Igor; Nowicki, Michał; Szewczyk, Roman; Kobzar, Svitlana

2016-01-01

The emergence of hypersonic technology pose a new challenge for inertial navigation sensors, widely used in aerospace industry. The main problems are: extremely high temperatures, vibration of the fuselage, penetrating acoustic radiation and shock N-waves. The nature of the additional errors of the gyroscopic inertial sensor with hydrostatic suspension components under operating conditions generated by forced precession of the movable part of the suspension due to diffraction phenomena in acoustic fields is explained. The cause of the disturbing moments in the form of the Coriolis inertia forces during the transition of the suspension surface into the category of impedance is revealed. The boundaries of occurrence of the features on the resonance wave match are described. The values of the “false” angular velocity as a result of the elastic-stress state of suspension in the acoustic fields are determined. PMID:26927122

An Effective Terrain Aided Navigation for Low-Cost Autonomous Underwater Vehicles.

PubMed

Zhou, Ling; Cheng, Xianghong; Zhu, Yixian; Dai, Chenxi; Fu, Jinbo

2017-03-25

Terrain-aided navigation is a potentially powerful solution for obtaining submerged position fixes for autonomous underwater vehicles. The application of terrain-aided navigation with high-accuracy inertial navigation systems has demonstrated meter-level navigation accuracy in sea trials. However, available sensors may be limited depending on the type of the mission. Such limitations, especially for low-grade navigation sensors, not only degrade the accuracy of traditional navigation systems, but further impact the ability to successfully employ terrain-aided navigation. To address this problem, a tightly-coupled navigation is presented to successfully estimate the critical sensor errors by incorporating raw sensor data directly into an augmented navigation system. Furthermore, three-dimensional distance errors are calculated, providing measurement updates through the particle filter for absolute and bounded position error. The development of the terrain aided navigation system is elaborated for a vehicle equipped with a non-inertial-grade strapdown inertial navigation system, a 4-beam Doppler Velocity Log range sensor and a sonar altimeter. Using experimental data for navigation performance evaluation in areas with different terrain characteristics, the experiment results further show that the proposed method can be successfully applied to the low-cost AUVs and significantly improves navigation performance.

An Effective Terrain Aided Navigation for Low-Cost Autonomous Underwater Vehicles

PubMed Central

Zhou, Ling; Cheng, Xianghong; Zhu, Yixian; Dai, Chenxi; Fu, Jinbo

2017-01-01

Terrain-aided navigation is a potentially powerful solution for obtaining submerged position fixes for autonomous underwater vehicles. The application of terrain-aided navigation with high-accuracy inertial navigation systems has demonstrated meter-level navigation accuracy in sea trials. However, available sensors may be limited depending on the type of the mission. Such limitations, especially for low-grade navigation sensors, not only degrade the accuracy of traditional navigation systems, but further impact the ability to successfully employ terrain-aided navigation. To address this problem, a tightly-coupled navigation is presented to successfully estimate the critical sensor errors by incorporating raw sensor data directly into an augmented navigation system. Furthermore, three-dimensional distance errors are calculated, providing measurement updates through the particle filter for absolute and bounded position error. The development of the terrain aided navigation system is elaborated for a vehicle equipped with a non-inertial-grade strapdown inertial navigation system, a 4-beam Doppler Velocity Log range sensor and a sonar altimeter. Using experimental data for navigation performance evaluation in areas with different terrain characteristics, the experiment results further show that the proposed method can be successfully applied to the low-cost AUVs and significantly improves navigation performance. PMID:28346346

Wearable Textile Platform for Assessing Stroke Patient Treatment in Daily Life Conditions

PubMed Central

Lorussi, Federico; Carbonaro, Nicola; De Rossi, Danilo; Paradiso, Rita; Veltink, Peter; Tognetti, Alessandro

2016-01-01

Monitoring physical activities during post-stroke rehabilitation in daily life may help physicians to optimize and tailor the training program for patients. The European research project INTERACTION (FP7-ICT-2011-7-287351) evaluated motor capabilities in stroke patients during the recovery treatment period. We developed wearable sensing platform based on the sensor fusion among inertial, knitted piezoresistive sensors and textile EMG electrodes. The device was conceived in modular form and consists of a separate shirt, trousers, glove, and shoe. Thanks to the novel fusion approach it has been possible to develop a model for the shoulder taking into account the scapulo-thoracic joint of the scapular girdle, considerably improving the estimation of the hand position in reaching activities. In order to minimize the sensor set used to monitor gait, a single inertial sensor fused with a textile goniometer proved to reconstruct the orientation of all the body segments of the leg. Finally, the sensing glove, endowed with three textile goniometers and three force sensors showed good capabilities in the reconstruction of grasping activities and evaluating the interaction of the hand with the environment, according to the project specifications. This paper reports on the design and the technical evaluation of the performance of the sensing platform, tested on healthy subjects. PMID:27047939

A Simulation Environment for Benchmarking Sensor Fusion-Based Pose Estimators.

PubMed

Ligorio, Gabriele; Sabatini, Angelo Maria

2015-12-19

In-depth analysis and performance evaluation of sensor fusion-based estimators may be critical when performed using real-world sensor data. For this reason, simulation is widely recognized as one of the most powerful tools for algorithm benchmarking. In this paper, we present a simulation framework suitable for assessing the performance of sensor fusion-based pose estimators. The systems used for implementing the framework were magnetic/inertial measurement units (MIMUs) and a camera, although the addition of further sensing modalities is straightforward. Typical nuisance factors were also included for each sensor. The proposed simulation environment was validated using real-life sensor data employed for motion tracking. The higher mismatch between real and simulated sensors was about 5% of the measured quantity (for the camera simulation), whereas a lower correlation was found for an axis of the gyroscope (0.90). In addition, a real benchmarking example of an extended Kalman filter for pose estimation from MIMU and camera data is presented.

Tightly Integrating Optical And Inertial Sensors For Navigation Using The UKF

DTIC Science & Technology

2008-03-01

832. September 2004. 3. Brown , Robert Grover and Patrick Y.C. Hwang . Introduction to Random Signals and Applied Kalman Filtering. John Wiley and Sons...effectiveness of fusing imaging and inertial sensors using an Extended Kalman Filter (EKF) algorithm has been shown in previous research efforts. In this...model assumed by the EKF. In order to cope with divergence problem, the Unscented (Sigma-Point) Kalman Filter (UKF) has been proposed in the literature in

Hand-Held EMI Sensor Combined with Inertial Positioning for Cued UXO Discrimination - APG Standardized UXO Test Site

DTIC Science & Technology

2013-04-01

Measurement Tracking System (SAINT) with an advanced hand-held, time-domain electromagnetic sensor (TEM-HH) and document classification performance at...rejecting 77% of the clutter. 15. SUBJECT TERMS EMI, electromagnetic induction, UXO classification, UXO, IMU, inertial measurement unit, 16. SECURITY...U c. THIS PAGE U UU 19b. TELEPHONE NUMBER (include area code) 919-677-1560 Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std. Z39.18

Inertial sensor real-time feedback enhances the learning of cervical spine manipulation: a prospective study

PubMed Central

2014-01-01

Background Cervical Spinal Manipulation (CSM) is considered a high-level skill of the central nervous system because it requires bimanual coordinated rhythmical movements therefore necessitating training to achieve proficiency. The objective of the present study was to investigate the effect of real-time feedback on the performance of CSM. Methods Six postgraduate physiotherapy students attending a training workshop on Cervical Spine Manipulation Technique (CSMT) using inertial sensor derived real-time feedback participated in this study. The key variables were pre-manipulative position, angular displacement of the thrust and angular velocity of the thrust. Differences between variables before and after training were investigated using t-tests. Results There were no significant differences after training for the pre-manipulative position (rotation p = 0.549; side bending p = 0.312) or for thrust displacement (rotation p = 0.247; side bending p = 0.314). Thrust angular velocity demonstrated a significant difference following training for rotation (pre-training mean (sd) 48.9°/s (35.1); post-training mean (sd) 96.9°/s (53.9); p = 0.027) but not for side bending (p = 0.521). Conclusion Real-time feedback using an inertial sensor may be valuable in the development of specific manipulative skill. Future studies investigating manipulation could consider a randomized controlled trial using inertial sensor real time feedback compared to traditional training. PMID:24942483

The influence of inertial sensor sampling frequency on the accuracy of measurement parameters in rearfoot running.

PubMed

Mitschke, Christian; Zaumseil, Falk; Milani, Thomas L

2017-11-01

Increasingly, inertial sensors are being used for running analyses. The aim of this study was to systematically investigate the influence of inertial sensor sampling frequencies (SF) on the accuracy of kinematic, spatio-temporal, and kinetic parameters. We hypothesized that running analyses at lower SF result in less signal information and therefore the inability to sufficiently interpret measurement data. Twenty-one subjects participated in this study. Rearfoot strikers ran on an indoor running track at a velocity of 3.5 ± 0.1 ms -1 . A uniaxial accelerometer was attached at the tibia and an inertial measurement unit was mounted at the heel of the right shoe. All sensors were synchronized at the start and data was measured with 1000 Hz (reference SF). Datasets were reduced to 500, 333, 250, 200, and 100 Hz in post-processing. The results of this study showed that a minimum SF of 500 Hz should be used to accurately measure kinetic parameters (e.g. peak heel acceleration). In contrast, stride length showed accurate results even at 333 Hz. 200 Hz were required to calculate parameters accurately for peak tibial acceleration, stride duration, and all kinematic measurements. The information from this study is necessary to correctly interpret measurement data of existing investigations and to plan future studies.

An Application of UAV Attitude Estimation Using a Low-Cost Inertial Navigation System

NASA Technical Reports Server (NTRS)

Eure, Kenneth W.; Quach, Cuong Chi; Vazquez, Sixto L.; Hogge, Edward F.; Hill, Boyd L.

2013-01-01

Unmanned Aerial Vehicles (UAV) are playing an increasing role in aviation. Various methods exist for the computation of UAV attitude based on low cost microelectromechanical systems (MEMS) and Global Positioning System (GPS) receivers. There has been a recent increase in UAV autonomy as sensors are becoming more compact and onboard processing power has increased significantly. Correct UAV attitude estimation will play a critical role in navigation and separation assurance as UAVs share airspace with civil air traffic. This paper describes attitude estimation derived by post-processing data from a small low cost Inertial Navigation System (INS) recorded during the flight of a subscale commercial off the shelf (COTS) UAV. Two discrete time attitude estimation schemes are presented here in detail. The first is an adaptation of the Kalman Filter to accommodate nonlinear systems, the Extended Kalman Filter (EKF). The EKF returns quaternion estimates of the UAV attitude based on MEMS gyro, magnetometer, accelerometer, and pitot tube inputs. The second scheme is the complementary filter which is a simpler algorithm that splits the sensor frequency spectrum based on noise characteristics. The necessity to correct both filters for gravity measurement errors during turning maneuvers is demonstrated. It is shown that the proposed algorithms may be used to estimate UAV attitude. The effects of vibration on sensor measurements are discussed. Heuristic tuning comments pertaining to sensor filtering and gain selection to achieve acceptable performance during flight are given. Comparisons of attitude estimation performance are made between the EKF and the complementary filter.

Simultaneous calibrations of Voyager celestial and inertial attitude control systems in flight

NASA Technical Reports Server (NTRS)

Jahanshahi, M. H.

1982-01-01

A mathematical description of the data reduction technique used to simultaneously calibrate the Voyager celestial and inertial attitude control subsystems is given. It is shown that knowledge of the spacecraft limit cycle motion, as measured by the celestial and the inertial sensors, is adequate to result in the estimates of a selected number of errors which adversely affect the spacecraft attitude knowledge.

A novel algorithm for detecting active propulsion in wheelchair users following spinal cord injury.

PubMed

Popp, Werner L; Brogioli, Michael; Leuenberger, Kaspar; Albisser, Urs; Frotzler, Angela; Curt, Armin; Gassert, Roger; Starkey, Michelle L

2016-03-01

Physical activity in wheelchair-bound individuals can be assessed by monitoring their mobility as this is one of the most intense upper extremity activities they perform. Current accelerometer-based approaches for describing wheelchair mobility do not distinguish between self- and attendant-propulsion and hence may overestimate total physical activity. The aim of this study was to develop and validate an inertial measurement unit based algorithm to monitor wheel kinematics and the type of wheelchair propulsion (self- or attendant-) within a "real-world" situation. Different sensor set-ups were investigated, ranging from a high precision set-up including four sensor modules with a relatively short measurement duration of 24 h, to a less precise set-up with only one module attached at the wheel exceeding one week of measurement because the gyroscope of the sensor was turned off. The "high-precision" algorithm distinguished self- and attendant-propulsion with accuracy greater than 93% whilst the long-term measurement set-up showed an accuracy of 82%. The estimation accuracy of kinematic parameters was greater than 97% for both set-ups. The possibility of having different sensor set-ups allows the use of the inertial measurement units as high precision tools for researchers as well as unobtrusive and simple tools for manual wheelchair users. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

A Cost-Effective Vehicle Localization Solution Using an Interacting Multiple Model−Unscented Kalman Filters (IMM-UKF) Algorithm and Grey Neural Network

PubMed Central

Xu, Qimin; Li, Xu; Chan, Ching-Yao

2017-01-01

In this paper, we propose a cost-effective localization solution for land vehicles, which can simultaneously adapt to the uncertain noise of inertial sensors and bridge Global Positioning System (GPS) outages. First, three Unscented Kalman filters (UKFs) with different noise covariances are introduced into the framework of Interacting Multiple Model (IMM) algorithm to form the proposed IMM-based UKF, termed as IMM-UKF. The IMM algorithm can provide a soft switching among the three UKFs and therefore adapt to different noise characteristics. Further, two IMM-UKFs are executed in parallel when GPS is available. One fuses the information of low-cost GPS, in-vehicle sensors, and micro electromechanical system (MEMS)-based reduced inertial sensor systems (RISS), while the other fuses only in-vehicle sensors and MEMS-RISS. The differences between the state vectors of the two IMM-UKFs are considered as training data of a Grey Neural Network (GNN) module, which is known for its high prediction accuracy with a limited amount of samples. The GNN module can predict and compensate position errors when GPS signals are blocked. To verify the feasibility and effectiveness of the proposed solution, road-test experiments with various driving scenarios were performed. The experimental results indicate that the proposed solution outperforms all the compared methods. PMID:28629165

WISDOM: wheelchair inertial sensors for displacement and orientation monitoring

NASA Astrophysics Data System (ADS)

Pansiot, J.; Zhang, Z.; Lo, B.; Yang, G. Z.

2011-10-01

Improved wheelchair design in recent years has significantly increased the mobility of people with disabilities, which has also enhanced the competitive advantage of wheelchair sports. For the latter, detailed assessment of biomechanical factors influencing individual performance and team tactics requires real-time wireless sensing and data modelling. In this paper, we propose the use of a miniaturized wireless wheel-mounted inertial sensor for wheelchair motion monitoring and tracking in an indoor sport environment. Based on a combined use of 3D microelectromechanical system (MEMS) gyroscopes and 2D MEMS accelerometers, the proposed system provides real-time velocity, heading, ground distance covered and motion trajectory of the wheelchair across the sports court. The proposed system offers a number of advantages compared to existing platforms in terms of size, weight and ease of installation. Beyond sport applications, it also has important applications for training and rehabilitation for people with disabilities.

Classification of frailty and falls history using a combination of sensor-based mobility assessments.

PubMed

Greene, Barry R; Doheny, Emer P; Kenny, Rose A; Caulfield, Brian

2014-10-01

Frailty is an important geriatric syndrome strongly linked to falls risk as well as increased mortality and morbidity. Taken alone, falls are the most common cause of injury and hospitalization and one of the principal causes of death and disability in older adults worldwide. Reliable determination of older adults' frailty state in concert with their falls risk could lead to targeted intervention and improved quality of care. We report a mobile assessment platform employing inertial and pressure sensors to quantify the balance and mobility of older adults using three physical assessments (timed up and go (TUG), five times sit to stand (FTSS) and quiet standing balance). This study examines the utility of each individual assessment, and the novel combination of assessments, to screen for frailty and falls risk in older adults.Data were acquired from inertial and pressure sensors during TUG, FTSS and balance assessments using a touchscreen mobile device, from 124 community dwelling older adults (mean age 75.9 ± 6.6 years, 91 female). Participants were given a comprehensive geriatric assessment which included questions on falls and frailty. Methods based on support vector machines (SVM) were developed using sensor-derived features from each physical assessment to classify patients at risk of falls risk and frailty.In classifying falls history, combining sensor data from the TUG, Balance and FTSS tests to a single classifier model per gender yielded mean cross-validated classification accuracy of 87.58% (95% CI: 84.47-91.03%) for the male model and 78.11% (95% CI: 75.38-81.10%) for the female model. These results compared well or exceeded those for classifier models for each test taken individually. Similarly, when classifying frailty status, combining sensor data from the TUG, balance and FTSS tests to a single classifier model per gender, yielded mean cross-validated classification accuracy of 93.94% (95% CI: 91.16-96.51%) for the male model and 84.14% (95% CI: 82.11-86.33%) for the female model (mean 89.04%) which compared well or exceeded results for physical tests taken individually.Results suggest that the combination of these three tests, quantified using body-worn inertial sensors, could lead to improved methods for assessing frailty and falls risk.

On Inertial Body Tracking in the Presence of Model Calibration Errors

PubMed Central

Miezal, Markus; Taetz, Bertram; Bleser, Gabriele

2016-01-01

In inertial body tracking, the human body is commonly represented as a biomechanical model consisting of rigid segments with known lengths and connecting joints. The model state is then estimated via sensor fusion methods based on data from attached inertial measurement units (IMUs). This requires the relative poses of the IMUs w.r.t. the segments—the IMU-to-segment calibrations, subsequently called I2S calibrations—to be known. Since calibration methods based on static poses, movements and manual measurements are still the most widely used, potentially large human-induced calibration errors have to be expected. This work compares three newly developed/adapted extended Kalman filter (EKF) and optimization-based sensor fusion methods with an existing EKF-based method w.r.t. their segment orientation estimation accuracy in the presence of model calibration errors with and without using magnetometer information. While the existing EKF-based method uses a segment-centered kinematic chain biomechanical model and a constant angular acceleration motion model, the newly developed/adapted methods are all based on a free segments model, where each segment is represented with six degrees of freedom in the global frame. Moreover, these methods differ in the assumed motion model (constant angular acceleration, constant angular velocity, inertial data as control input), the state representation (segment-centered, IMU-centered) and the estimation method (EKF, sliding window optimization). In addition to the free segments representation, the optimization-based method also represents each IMU with six degrees of freedom in the global frame. In the evaluation on simulated and real data from a three segment model (an arm), the optimization-based method showed the smallest mean errors, standard deviations and maximum errors throughout all tests. It also showed the lowest dependency on magnetometer information and motion agility. Moreover, it was insensitive w.r.t. I2S position and segment length errors in the tested ranges. Errors in the I2S orientations were, however, linearly propagated into the estimated segment orientations. In the absence of magnetic disturbances, severe model calibration errors and fast motion changes, the newly developed IMU centered EKF-based method yielded comparable results with lower computational complexity. PMID:27455266

Online Estimation of Allan Variance Coefficients Based on a Neural-Extended Kalman Filter

PubMed Central

Miao, Zhiyong; Shen, Feng; Xu, Dingjie; He, Kunpeng; Tian, Chunmiao

2015-01-01

As a noise analysis method for inertial sensors, the traditional Allan variance method requires the storage of a large amount of data and manual analysis for an Allan variance graph. Although the existing online estimation methods avoid the storage of data and the painful procedure of drawing slope lines for estimation, they require complex transformations and even cause errors during the modeling of dynamic Allan variance. To solve these problems, first, a new state-space model that directly models the stochastic errors to obtain a nonlinear state-space model was established for inertial sensors. Then, a neural-extended Kalman filter algorithm was used to estimate the Allan variance coefficients. The real noises of an ADIS16405 IMU and fiber optic gyro-sensors were analyzed by the proposed method and traditional methods. The experimental results show that the proposed method is more suitable to estimate the Allan variance coefficients than the traditional methods. Moreover, the proposed method effectively avoids the storage of data and can be easily implemented using an online processor. PMID:25625903

Spatial filtering self-velocimeter for vehicle application using a CMOS linear image sensor

NASA Astrophysics Data System (ADS)

He, Xin; Zhou, Jian; Nie, Xiaoming; Long, Xingwu

2015-03-01

The idea of using a spatial filtering velocimeter (SFV) to measure the velocity of a vehicle for an inertial navigation system is put forward. The presented SFV is based on a CMOS linear image sensor with a high-speed data rate, large pixel size, and built-in timing generator. These advantages make the image sensor suitable to measure vehicle velocity. The power spectrum of the output signal is obtained by fast Fourier transform and is corrected by a frequency spectrum correction algorithm. This velocimeter was used to measure the velocity of a conveyor belt driven by a rotary table and the measurement uncertainty is ˜0.54%. Furthermore, it was also installed on a vehicle together with a laser Doppler velocimeter (LDV) to measure self-velocity. The measurement result of the designed SFV is compared with that of the LDV. It is shown that the measurement result of the SFV is coincident with that of the LDV. Therefore, the designed SFV is suitable for a vehicle self-contained inertial navigation system.

Underwater image mosaicking and visual odometry

NASA Astrophysics Data System (ADS)

Sadjadi, Firooz; Tangirala, Sekhar; Sorber, Scott

2017-05-01

This paper summarizes the results of studies in underwater odometery using a video camera for estimating the velocity of an unmanned underwater vehicle (UUV). Underwater vehicles are usually equipped with sonar and Inertial Measurement Unit (IMU) - an integrated sensor package that combines multiple accelerometers and gyros to produce a three dimensional measurement of both specific force and angular rate with respect to an inertial reference frame for navigation. In this study, we investigate the use of odometry information obtainable from a video camera mounted on a UUV to extract vehicle velocity relative to the ocean floor. A key challenge with this process is the seemingly bland (i.e. featureless) nature of video data obtained underwater which could make conventional approaches to image-based motion estimation difficult. To address this problem, we perform image enhancement, followed by frame to frame image transformation, registration and mosaicking/stitching. With this approach the velocity components associated with the moving sensor (vehicle) are readily obtained from (i) the components of the transform matrix at each frame; (ii) information about the height of the vehicle above the seabed; and (iii) the sensor resolution. Preliminary results are presented.

Inertial Head-Tracker Sensor Fusion by a Complementary Separate-Bias Kalman Filter

NASA Technical Reports Server (NTRS)

Foxlin, Eric

1996-01-01

Current virtual environment and teleoperator applications are hampered by the need for an accurate, quick-responding head-tracking system with a large working volume. Gyroscopic orientation sensors can overcome problems with jitter, latency, interference, line-of-sight obscurations, and limited range, but suffer from slow drift. Gravimetric inclinometers can detect attitude without drifting, but are slow and sensitive to transverse accelerations. This paper describes the design of a Kalman filter to integrate the data from these two types of sensors in order to achieve the excellent dynamic response of an inertial system without drift, and without the acceleration sensitivity of inclinometers.

GPS free navigation inspired by insects through monocular camera and inertial sensors

NASA Astrophysics Data System (ADS)

Liu, Yi; Liu, J. G.; Cao, H.; Huang, Y.

2015-12-01

Navigation without GPS and other knowledge of environment have been studied for many decades. Advance technology have made sensors more compact and subtle that can be easily integrated into micro and hand-hold device. Recently researchers found that bee and fruit fly have an effectively and efficiently navigation mechanism through optical flow information and process only with their miniature brain. We present a navigation system inspired by the study of insects through a calibrated camera and other inertial sensors. The system utilizes SLAM theory and can be worked in many GPS denied environment. Simulation and experimental results are presented for validation and quantification.

Eddy-current non-inertial displacement sensing for underwater infrasound measurements.

PubMed

Donskoy, Dimitri M; Cray, Benjamin A

2011-06-01

A non-inertial sensing approach for an Acoustic Vector Sensor (AVS), which utilizes eddy-current displacement sensors and operates well at Ultra-Low Frequencies (ULF), is described here. In the past, most ULF measurements (from mHertz to approximately 10 Hertz) have been conducted using heavy geophones or seismometers that must be installed on the seafloor; these sensors are not suitable for water column measurements. Currently, there are no readily available compact and affordable underwater AVS that operate within this frequency region. Test results have confirmed the validity of the proposed eddy-current AVS design and have demonstrated high acoustic sensitivity. © 2011 Acoustical Society of America

Inertial head-tracker sensor fusion by a complementary separate-bias Kalman filter

NASA Technical Reports Server (NTRS)

Foxlin, Eric

1996-01-01

Current virtual environment and teleoperator applications are hampered by the need for an accurate, quick responding head-tracking system with a large working volume. Gyroscopic orientation sensors can overcome problems with jitter, latency, interference, line-of-sight obscurations, and limited range, but suffer from slow drift. Gravimetric inclinometers can detect attitude without drifting, but are slow and sensitive to transverse accelerations. This paper describes the design of a Kalman filter to integrate the data from these two types of sensors in order to achieve the excellent dynamic response of an inertial system without drift, and without the acceleration sensitivity of inclinometers.

Architectural elements of hybrid navigation systems for future space transportation

NASA Astrophysics Data System (ADS)

Trigo, Guilherme F.; Theil, Stephan

2018-06-01

The fundamental limitations of inertial navigation, currently employed by most launchers, have raised interest for GNSS-aided solutions. Combination of inertial measurements and GNSS outputs allows inertial calibration online, solving the issue of inertial drift. However, many challenges and design options unfold. In this work we analyse several architectural elements and design aspects of a hybrid GNSS/INS navigation system conceived for space transportation. The most fundamental architectural features such as coupling depth, modularity between filter and inertial propagation, and open-/closed-loop nature of the configuration, are discussed in the light of the envisaged application. Importance of the inertial propagation algorithm and sensor class in the overall system are investigated, being the handling of sensor errors and uncertainties that arise with lower grade sensory also considered. In terms of GNSS outputs we consider receiver solutions (position and velocity) and raw measurements (pseudorange, pseudorange-rate and time-difference carrier phase). Receiver clock error handling options and atmospheric error correction schemes for these measurements are analysed under flight conditions. System performance with different GNSS measurements is estimated through covariance analysis, being the differences between loose and tight coupling emphasized through partial outage simulation. Finally, we discuss options for filter algorithm robustness against non-linearities and system/measurement errors. A possible scheme for fault detection, isolation and recovery is also proposed.

A novel visual-inertial monocular SLAM

NASA Astrophysics Data System (ADS)

Yue, Xiaofeng; Zhang, Wenjuan; Xu, Li; Liu, JiangGuo

2018-02-01

With the development of sensors and computer vision research community, cameras, which are accurate, compact, wellunderstood and most importantly cheap and ubiquitous today, have gradually been at the center of robot location. Simultaneous localization and mapping (SLAM) using visual features, which is a system getting motion information from image acquisition equipment and rebuild the structure in unknown environment. We provide an analysis of bioinspired flights in insects, employing a novel technique based on SLAM. Then combining visual and inertial measurements to get high accuracy and robustness. we present a novel tightly-coupled Visual-Inertial Simultaneous Localization and Mapping system which get a new attempt to address two challenges which are the initialization problem and the calibration problem. experimental results and analysis show the proposed approach has a more accurate quantitative simulation of insect navigation, which can reach the positioning accuracy of centimeter level.

Anatomical calibration for wearable motion capture systems: Video calibrated anatomical system technique.

PubMed

Bisi, Maria Cristina; Stagni, Rita; Caroselli, Alessio; Cappello, Angelo

2015-08-01

Inertial sensors are becoming widely used for the assessment of human movement in both clinical and research applications, thanks to their usability out of the laboratory. This work aims to propose a method for calibrating anatomical landmark position in the wearable sensor reference frame with an ease to use, portable and low cost device. An off-the-shelf camera, a stick and a pattern, attached to the inertial sensor, compose the device. The proposed technique is referred to as video Calibrated Anatomical System Technique (vCAST). The absolute orientation of a synthetic femur was tracked both using the vCAST together with an inertial sensor and using stereo-photogrammetry as reference. Anatomical landmark calibration showed mean absolute error of 0.6±0.5 mm: these errors are smaller than those affecting the in-vivo identification of anatomical landmarks. The roll, pitch and yaw anatomical frame orientations showed root mean square errors close to the accuracy limit of the wearable sensor used (1°), highlighting the reliability of the proposed technique. In conclusion, the present paper proposes and preliminarily verifies the performance of a method (vCAST) for calibrating anatomical landmark position in the wearable sensor reference frame: the technique is low time consuming, highly portable, easy to implement and usable outside laboratory. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Reliability in the parameterization of the functional reach test in elderly stroke patients: a pilot study.

PubMed

Merchán-Baeza, Jose Antonio; González-Sánchez, Manuel; Cuesta-Vargas, Antonio Ignacio

2014-01-01

Postural instability is one of the major complications found in stroke survivors. Parameterising the functional reach test (FRT) could be useful in clinical practice and basic research. To analyse the reliability, sensitivity, and specificity in the FRT parameterisation using inertial sensors for recording kinematic variables in patients who have suffered a stroke. Cross-sectional study. While performing FRT, two inertial sensors were placed on the patient's back (lumbar and trunk). Five subjects over 65 who suffer from a stroke. FRT measures, lumbosacral/thoracic maximum angular displacement, maximum time of lumbosacral/thoracic angular displacement, time return initial position, and total time. Speed and acceleration of the movements were calculated indirectly. FRT measure is  12.75±2.06 cm. Intrasubject reliability values range from 0.829 (time to return initial position (lumbar sensor)) to 0.891 (lumbosacral maximum angular displacement). Intersubject reliability values range from 0.821 (time to return initial position (lumbar sensor)) to 0.883 (lumbosacral maximum angular displacement). FRT's reliability was 0.987 (0.983-0.992) and 0.983 (0.979-0.989) intersubject and intrasubject, respectively. The main conclusion could be that the inertial sensors are a tool with excellent reliability and validity in the parameterization of the FRT in people who have had a stroke.

Recent progress in MEMS technology development for military applications

NASA Astrophysics Data System (ADS)

Ruffin, Paul B.; Burgett, Sherrie J.

2001-08-01

The recent progress of ongoing efforts at the Army Aviation and Missile Command (AMCOM) to develop microelectromechanical systems (MEMS) technology for military applications is discussed in this paper. The current maturity level of low cost, low power, micro devices in industry, which range from simple temperature and pressure sensors to accelerometers in airbags, provides a viable foundation for the development of rugged MEMS devices for dual-use applications. Early MEMS technology development efforts at AMCOM emphasized inertial MEMS sensors. An Army Science and Technology Objective (STO) project was initiated to develop low cost inertial components with moderate angular rate sensor resolution for measuring pitch and yaw of missile attitude and rotational roll rate. Leveraging the Defense Advanced Research Projects Agency and other Government agencies has resulted in the development of breadboard inertial MEMS devices with improved robustness. During the past two years, MEMS research at AMCOM has been expanded to include environmental MEMS sensors for missile health monitoring, RF-MEMS, optical MEMS devices for beam steering, and micro-optic 'benches' for opto-electronics miniaturization. Additionally, MEMS packaging and integration issues have come into focus and are being addressed. Selected ongoing research efforts in these areas are presented, and some horizon MEMS sensors requirements for Army and law enforcement are presented for consideration.

SmartStuff: A case study of a smart water bottle.

PubMed

Jovanov, Emil; Nallathimmareddygari, Vindhya R; Pryor, Jonathan E

2016-08-01

The rapid growth of Internet of Things (IoT) and miniature wearable biosensors have generated new opportunities for personalized eHealth and mHealth services. Smart objects equipped with physiological sensors can provide robust monitoring of activities of daily living and context for wearable physiological sensors. We present a case study of an intelligent water bottle that can precisely measure the amount of liquid in the bottle, monitor activity using inertial sensors, and physiological parameters using a touch and photoplethysmographic sensor. We evaluate two system configurations: a smart water bottle integrated into a personal body sensor network and a cloud based device. This paper presents system organization and the results from preliminary field testing of the prototype device.

Optimal geometrical design of inertial vibration DC piezoelectric nanogenerators based on obliquely aligned InN nanowire arrays.

PubMed

Ku, Nai-Jen; Liu, Guocheng; Wang, Chao-Hung; Gupta, Kapil; Liao, Wei-Shun; Ban, Dayan; Liu, Chuan-Pu

2017-09-28

Piezoelectric nanogenerators have been investigated to generate electricity from environmental vibrations due to their energy conversion capabilities. In this study, we demonstrate an optimal geometrical design of inertial vibration direct-current piezoelectric nanogenerators based on obliquely aligned InN nanowire (NW) arrays with an optimized oblique angle of ∼58°, and driven by the inertial force of their own weight, using a mechanical shaker without any AC/DC converters. The nanogenerator device manifests potential applications not only as a unique energy harvesting device capable of scavenging energy from weak mechanical vibrations, but also as a sensitive strain sensor. The maximum output power density of the nanogenerator is estimated to be 2.9 nW cm -2 , leading to an improvement of about 3-12 times that of vertically aligned ZnO NW DC nanogenerators. Integration of two nanogenerators also exhibits a linear increase in the output power, offering an enormous potential for the creation of self-powered sustainable nanosystems utilizing incessantly natural ambient energy sources.

Estimation of Center of Mass Trajectory using Wearable Sensors during Golf Swing.

PubMed

Najafi, Bijan; Lee-Eng, Jacqueline; Wrobel, James S; Goebel, Ruben

2015-06-01

This study suggests a wearable sensor technology to estimate center of mass (CoM) trajectory during a golf swing. Groups of 3, 4, and 18 participants were recruited, respectively, for the purpose of three validation studies. Study 1 examined the accuracy of the system to estimate a 3D body segment angle compared to a camera-based motion analyzer (Vicon®). Study 2 assessed the accuracy of three simplified CoM trajectory models. Finally, Study 3 assessed the accuracy of the proposed CoM model during multiple golf swings. A relatively high agreement was observed between wearable sensors and the reference (Vicon®) for angle measurement (r > 0.99, random error <1.2° (1.5%) for anterior-posterior; <0.9° (2%) for medial-lateral; and <3.6° (2.5%) for internal-external direction). The two-link model yielded a better agreement with the reference system compared to one-link model (r > 0.93 v. r = 0.52, respectively). On the same note, the proposed two-link model estimated CoM trajectory during golf swing with relatively good accuracy (r > 0.9, A-P random error <1cm (7.7%) and <2cm (10.4%) for M-L). The proposed system appears to accurately quantify the kinematics of CoM trajectory as a surrogate of dynamic postural control during an athlete's movement and its portability, makes it feasible to fit the competitive environment without restricting surface type. Key pointsThis study demonstrates that wearable technology based on inertial sensors are accurate to estimate center of mass trajectory in complex athletic task (e.g., golf swing)This study suggests that two-link model of human body provides optimum tradeoff between accuracy and minimum number of sensor module for estimation of center of mass trajectory in particular during fast movements.Wearable technologies based on inertial sensors are viable option for assessing dynamic postural control in complex task outside of gait laboratory and constraints of cameras, surface, and base of support.

Sensor Fusion of a Mobile Device to Control and Acquire Videos or Images of Coffee Branches and for Georeferencing Trees.

PubMed

Giraldo, Paula Jimena Ramos; Aguirre, Álvaro Guerrero; Muñoz, Carlos Mario; Prieto, Flavio Augusto; Oliveros, Carlos Eugenio

2017-04-06

Smartphones show potential for controlling and monitoring variables in agriculture. Their processing capacity, instrumentation, connectivity, low cost, and accessibility allow farmers (among other users in rural areas) to operate them easily with applications adjusted to their specific needs. In this investigation, the integration of inertial sensors, a GPS, and a camera are presented for the monitoring of a coffee crop. An Android-based application was developed with two operating modes: ( i ) Navigation: for georeferencing trees, which can be as close as 0.5 m from each other; and ( ii ) Acquisition: control of video acquisition, based on the movement of the mobile device over a branch, and measurement of image quality, using clarity indexes to select the most appropriate frames for application in future processes. The integration of inertial sensors in navigation mode, shows a mean relative error of ±0.15 m, and total error ±5.15 m. In acquisition mode, the system correctly identifies the beginning and end of mobile phone movement in 99% of cases, and image quality is determined by means of a sharpness factor which measures blurriness. With the developed system, it will be possible to obtain georeferenced information about coffee trees, such as their production, nutritional state, and presence of plagues or diseases.

Performance Characteristic Mems-Based IMUs for UAVs Navigation

NASA Astrophysics Data System (ADS)

Mohamed, H. A.; Hansen, J. M.; Elhabiby, M. M.; El-Sheimy, N.; Sesay, A. B.

2015-08-01

Accurate 3D reconstruction has become essential for non-traditional mapping applications such as urban planning, mining industry, environmental monitoring, navigation, surveillance, pipeline inspection, infrastructure monitoring, landslide hazard analysis, indoor localization, and military simulation. The needs of these applications cannot be satisfied by traditional mapping, which is based on dedicated data acquisition systems designed for mapping purposes. Recent advances in hardware and software development have made it possible to conduct accurate 3D mapping without using costly and high-end data acquisition systems. Low-cost digital cameras, laser scanners, and navigation systems can provide accurate mapping if they are properly integrated at the hardware and software levels. Unmanned Aerial Vehicles (UAVs) are emerging as a mobile mapping platform that can provide additional economical and practical advantages. However, such economical and practical requirements need navigation systems that can provide uninterrupted navigation solution. Hence, testing the performance characteristics of Micro-Electro-Mechanical Systems (MEMS) or low cost navigation sensors for various UAV applications is important research. This work focuses on studying the performance characteristics under different manoeuvres using inertial measurements integrated with single point positioning, Real-Time-Kinematic (RTK), and additional navigational aiding sensors. Furthermore, the performance of the inertial sensors is tested during Global Positioning System (GPS) signal outage.

Sensor Fusion of a Mobile Device to Control and Acquire Videos or Images of Coffee Branches and for Georeferencing Trees

PubMed Central

Ramos Giraldo, Paula Jimena; Guerrero Aguirre, Álvaro; Muñoz, Carlos Mario; Prieto, Flavio Augusto; Oliveros, Carlos Eugenio

2017-01-01

Smartphones show potential for controlling and monitoring variables in agriculture. Their processing capacity, instrumentation, connectivity, low cost, and accessibility allow farmers (among other users in rural areas) to operate them easily with applications adjusted to their specific needs. In this investigation, the integration of inertial sensors, a GPS, and a camera are presented for the monitoring of a coffee crop. An Android-based application was developed with two operating modes: (i) Navigation: for georeferencing trees, which can be as close as 0.5 m from each other; and (ii) Acquisition: control of video acquisition, based on the movement of the mobile device over a branch, and measurement of image quality, using clarity indexes to select the most appropriate frames for application in future processes. The integration of inertial sensors in navigation mode, shows a mean relative error of ±0.15 m, and total error ±5.15 m. In acquisition mode, the system correctly identifies the beginning and end of mobile phone movement in 99% of cases, and image quality is determined by means of a sharpness factor which measures blurriness. With the developed system, it will be possible to obtain georeferenced information about coffee trees, such as their production, nutritional state, and presence of plagues or diseases. PMID:28383494

Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion

PubMed Central

Filippeschi, Alessandro; Schmitz, Norbert; Miezal, Markus; Bleser, Gabriele; Ruffaldi, Emanuele; Stricker, Didier

2017-01-01

Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error). PMID:28587178

Hubble Space Telescope Angular Velocity Estimation During the Robotic Servicing Mission

NASA Technical Reports Server (NTRS)

Thienel, Julie K.; Queen, Steven Z.; VanEepoel, John M.; Sanner, Robert M.

2005-01-01

In 2004 NASA began investigation of a robotic servicing mission for the Hubble Space Telescope (HST). Such a mission would require estimates of the HST attitude and rates in order to achieve a capture by the proposed Hubble robotic vehicle (HRV). HRV was to be equipped with vision-based sensors, capable of estimating the relative attitude between HST and HRV. The inertial HST attitude is derived from the measured relative attitude and the HRV computed inertial attitude. However, the relative rate between HST and HRV cannot be measured directly. Therefore, the HST rate with respect to inertial space is not known. Two approaches are developed to estimate the HST rates. Both methods utilize the measured relative attitude and the HRV inertial attitude and rates. First, a non-linear estimator is developed. The nonlinear approach estimates the HST rate through an estimation of the inertial angular momentum. Second, a linearized approach is developed. The linearized approach is a pseudo-linear Kalman filter. Simulation test results for both methods are given. Even though the development began as an application for the HST robotic servicing mission, the methods presented are applicable to any rendezvous/capture mission involving a non-cooperative target spacecraft.

Sensors integration for smartphone navigation: performances and future challenges

NASA Astrophysics Data System (ADS)

Aicardi, I.; Dabove, P.; Lingua, A.; Piras, M.

2014-08-01

Nowadays the modern smartphones include several sensors which are usually adopted in geomatic application, as digital camera, GNSS (Global Navigation Satellite System) receivers, inertial platform, RFID and Wi-Fi systems. In this paper the authors would like to testing the performances of internal sensors (Inertial Measurement Unit, IMU) of three modern smartphones (Samsung GalaxyS4, Samsung GalaxyS5 and iPhone4) compared to external mass-market IMU platform in order to verify their accuracy levels, in terms of positioning. Moreover, the Image Based Navigation (IBN) approach is also investigated: this approach can be very useful in hard-urban environment or for indoor positioning, as alternative to GNSS positioning. IBN allows to obtain a sub-metrical accuracy, but a special database of georeferenced images (Image DataBase, IDB) is needed, moreover it is necessary to use dedicated algorithm to resizing the images which are collected by smartphone, in order to share it with the server where is stored the IDB. Moreover, it is necessary to characterize smartphone camera lens in terms of focal length and lens distortions. The authors have developed an innovative method with respect to those available today, which has been tested in a covered area, adopting a special support where all sensors under testing have been installed. Geomatic instrument have been used to define the reference trajectory, with purpose to compare this one, with the path obtained with IBN solution. First results leads to have an horizontal and vertical accuracies better than 60 cm, respect to the reference trajectories. IBN method, sensors, test and result will be described in the paper.

A Bionic Camera-Based Polarization Navigation Sensor

PubMed Central

Wang, Daobin; Liang, Huawei; Zhu, Hui; Zhang, Shuai

2014-01-01

Navigation and positioning technology is closely related to our routine life activities, from travel to aerospace. Recently it has been found that Cataglyphis (a kind of desert ant) is able to detect the polarization direction of skylight and navigate according to this information. This paper presents a real-time bionic camera-based polarization navigation sensor. This sensor has two work modes: one is a single-point measurement mode and the other is a multi-point measurement mode. An indoor calibration experiment of the sensor has been done under a beam of standard polarized light. The experiment results show that after noise reduction the accuracy of the sensor can reach up to 0.3256°. It is also compared with GPS and INS (Inertial Navigation System) in the single-point measurement mode through an outdoor experiment. Through time compensation and location compensation, the sensor can be a useful alternative to GPS and INS. In addition, the sensor also can measure the polarization distribution pattern when it works in multi-point measurement mode. PMID:25051029

Accurate human limb angle measurement: sensor fusion through Kalman, least mean squares and recursive least-squares adaptive filtering

NASA Astrophysics Data System (ADS)

Olivares, A.; Górriz, J. M.; Ramírez, J.; Olivares, G.

2011-02-01

Inertial sensors are widely used in human body motion monitoring systems since they permit us to determine the position of the subject's limbs. Limb angle measurement is carried out through the integration of the angular velocity measured by a rate sensor and the decomposition of the components of static gravity acceleration measured by an accelerometer. Different factors derived from the sensors' nature, such as the angle random walk and dynamic bias, lead to erroneous measurements. Dynamic bias effects can be reduced through the use of adaptive filtering based on sensor fusion concepts. Most existing published works use a Kalman filtering sensor fusion approach. Our aim is to perform a comparative study among different adaptive filters. Several least mean squares (LMS), recursive least squares (RLS) and Kalman filtering variations are tested for the purpose of finding the best method leading to a more accurate and robust limb angle measurement. A new angle wander compensation sensor fusion approach based on LMS and RLS filters has been developed.

System Dynamic Analysis of a Wind Tunnel Model with Applications to Improve Aerodynamic Data Quality

NASA Technical Reports Server (NTRS)

Buehrle, Ralph David

1997-01-01

The research investigates the effect of wind tunnel model system dynamics on measured aerodynamic data. During wind tunnel tests designed to obtain lift and drag data, the required aerodynamic measurements are the steady-state balance forces and moments, pressures, and model attitude. However, the wind tunnel model system can be subjected to unsteady aerodynamic and inertial loads which result in oscillatory translations and angular rotations. The steady-state force balance and inertial model attitude measurements are obtained by filtering and averaging data taken during conditions of high model vibrations. The main goals of this research are to characterize the effects of model system dynamics on the measured steady-state aerodynamic data and develop a correction technique to compensate for dynamically induced errors. Equations of motion are formulated for the dynamic response of the model system subjected to arbitrary aerodynamic and inertial inputs. The resulting modal model is examined to study the effects of the model system dynamic response on the aerodynamic data. In particular, the equations of motion are used to describe the effect of dynamics on the inertial model attitude, or angle of attack, measurement system that is used routinely at the NASA Langley Research Center and other wind tunnel facilities throughout the world. This activity was prompted by the inertial model attitude sensor response observed during high levels of model vibration while testing in the National Transonic Facility at the NASA Langley Research Center. The inertial attitude sensor cannot distinguish between the gravitational acceleration and centrifugal accelerations associated with wind tunnel model system vibration, which results in a model attitude measurement bias error. Bias errors over an order of magnitude greater than the required device accuracy were found in the inertial model attitude measurements during dynamic testing of two model systems. Based on a theoretical modal approach, a method using measured vibration amplitudes and measured or calculated modal characteristics of the model system is developed to correct for dynamic bias errors in the model attitude measurements. The correction method is verified through dynamic response tests on two model systems and actual wind tunnel test data.

An Inertial Sensor-Based Method for Estimating the Athlete's Relative Joint Center Positions and Center of Mass Kinematics in Alpine Ski Racing

PubMed Central

Fasel, Benedikt; Spörri, Jörg; Schütz, Pascal; Lorenzetti, Silvio; Aminian, Kamiar

2017-01-01

For the purpose of gaining a deeper understanding of the relationship between external training load and health in competitive alpine skiing, an accurate and precise estimation of the athlete's kinematics is an essential methodological prerequisite. This study proposes an inertial sensor-based method to estimate the athlete's relative joint center positions and center of mass (CoM) kinematics in alpine skiing. Eleven inertial sensors were fixed to the lower and upper limbs, trunk, and head. The relative positions of the ankle, knee, hip, shoulder, elbow, and wrist joint centers, as well as the athlete's CoM kinematics were validated against a marker-based optoelectronic motion capture system during indoor carpet skiing. For all joints centers analyzed, position accuracy (mean error) was below 110 mm and precision (error standard deviation) was below 30 mm. CoM position accuracy and precision were 25.7 and 6.7 mm, respectively. Both the accuracy and precision of the system to estimate the distance between the ankle of the outside leg and CoM (measure quantifying the skier's overall vertical motion) were found to be below 11 mm. Some poorer accuracy and precision values (below 77 mm) were observed for the athlete's fore-aft position (i.e., the projection of the outer ankle-CoM vector onto the line corresponding to the projection of ski's longitudinal axis on the snow surface). In addition, the system was found to be sensitive enough to distinguish between different types of turns (wide/narrow). Thus, the method proposed in this paper may also provide a useful, pervasive way to monitor and control adverse external loading patterns that occur during regular on-snow training. Moreover, as demonstrated earlier, such an approach might have a certain potential to quantify competition time, movement repetitions and/or the accelerations acting on the different segments of the human body. However, prior to getting feasible for applications in daily training, future studies should primarily focus on a simplification of the sensor setup, as well as a fusion with global navigation satellite systems (i.e., the estimation of the absolute joint and CoM positions). PMID:29163196

An Inertial Sensor-Based Method for Estimating the Athlete's Relative Joint Center Positions and Center of Mass Kinematics in Alpine Ski Racing.

PubMed

Fasel, Benedikt; Spörri, Jörg; Schütz, Pascal; Lorenzetti, Silvio; Aminian, Kamiar

2017-01-01

For the purpose of gaining a deeper understanding of the relationship between external training load and health in competitive alpine skiing, an accurate and precise estimation of the athlete's kinematics is an essential methodological prerequisite. This study proposes an inertial sensor-based method to estimate the athlete's relative joint center positions and center of mass (CoM) kinematics in alpine skiing. Eleven inertial sensors were fixed to the lower and upper limbs, trunk, and head. The relative positions of the ankle, knee, hip, shoulder, elbow, and wrist joint centers, as well as the athlete's CoM kinematics were validated against a marker-based optoelectronic motion capture system during indoor carpet skiing. For all joints centers analyzed, position accuracy (mean error) was below 110 mm and precision (error standard deviation) was below 30 mm. CoM position accuracy and precision were 25.7 and 6.7 mm, respectively. Both the accuracy and precision of the system to estimate the distance between the ankle of the outside leg and CoM (measure quantifying the skier's overall vertical motion) were found to be below 11 mm. Some poorer accuracy and precision values (below 77 mm) were observed for the athlete's fore-aft position (i.e., the projection of the outer ankle-CoM vector onto the line corresponding to the projection of ski's longitudinal axis on the snow surface). In addition, the system was found to be sensitive enough to distinguish between different types of turns (wide/narrow). Thus, the method proposed in this paper may also provide a useful, pervasive way to monitor and control adverse external loading patterns that occur during regular on-snow training. Moreover, as demonstrated earlier, such an approach might have a certain potential to quantify competition time, movement repetitions and/or the accelerations acting on the different segments of the human body. However, prior to getting feasible for applications in daily training, future studies should primarily focus on a simplification of the sensor setup, as well as a fusion with global navigation satellite systems (i.e., the estimation of the absolute joint and CoM positions).

Fuzzy adaptive integration scheme for low-cost SINS/GPS navigation system

NASA Astrophysics Data System (ADS)

Nourmohammadi, Hossein; Keighobadi, Jafar

2018-01-01

Due to weak stand-alone accuracy as well as poor run-to-run stability of micro-electro mechanical system (MEMS)-based inertial sensors, special approaches are required to integrate low-cost strap-down inertial navigation system (SINS) with global positioning system (GPS), particularly in long-term applications. This paper aims to enhance long-term performance of conventional SINS/GPS navigation systems using a fuzzy adaptive integration scheme. The main concept behind the proposed adaptive integration is the good performance of attitude-heading reference system (AHRS) in low-accelerated motions and its degradation in maneuvered or accelerated motions. Depending on vehicle maneuvers, gravity-based attitude angles can be intelligently utilized to improve orientation estimation in the SINS. Knowledge-based fuzzy inference system is developed for decision-making between the AHRS and the SINS according to vehicle maneuvering conditions. Inertial measurements are the main input data of the fuzzy system to determine the maneuvering level during the vehicle motions. Accordingly, appropriate weighting coefficients are produced to combine the SINS/GPS and the AHRS, efficiently. The assessment of the proposed integrated navigation system is conducted via real data in airborne tests.

Inertial Sensor Error Reduction through Calibration and Sensor Fusion.

PubMed

Lambrecht, Stefan; Nogueira, Samuel L; Bortole, Magdo; Siqueira, Adriano A G; Terra, Marco H; Rocon, Eduardo; Pons, José L

2016-02-17

This paper presents the comparison between cooperative and local Kalman Filters (KF) for estimating the absolute segment angle, under two calibration conditions. A simplified calibration, that can be replicated in most laboratories; and a complex calibration, similar to that applied by commercial vendors. The cooperative filters use information from either all inertial sensors attached to the body, Matricial KF; or use information from the inertial sensors and the potentiometers of an exoskeleton, Markovian KF. A one minute walking trial of a subject walking with a 6-DoF exoskeleton was used to assess the absolute segment angle of the trunk, thigh, shank, and foot. The results indicate that regardless of the segment and filter applied, the more complex calibration always results in a significantly better performance compared to the simplified calibration. The interaction between filter and calibration suggests that when the quality of the calibration is unknown the Markovian KF is recommended. Applying the complex calibration, the Matricial and Markovian KF perform similarly, with average RMSE below 1.22 degrees. Cooperative KFs perform better or at least equally good as Local KF, we therefore recommend to use cooperative KFs instead of local KFs for control or analysis of walking.

Magnetometer-augmented IMU simulator: in-depth elaboration.

PubMed

Brunner, Thomas; Lauffenburger, Jean-Philippe; Changey, Sébastien; Basset, Michel

2015-03-04

The location of objects is a growing research topic due, for instance, to the expansion of civil drones or intelligent vehicles. This expansion was made possible through the development of microelectromechanical systems (MEMS), inexpensive and miniaturized inertial sensors. In this context, this article describes the development of a new simulator which generates sensor measurements, giving a specific input trajectory. This will allow the comparison of pose estimation algorithms. To develop this simulator, the measurement equations of every type of sensor have to be analytically determined. To achieve this objective, classical kinematic equations are used for the more common sensors, i.e., accelerometers and rate gyroscopes. As nowadays, the MEMS inertial measurement units (IMUs) are generally magnetometer-augmented, an absolute world magnetic model is implemented. After the determination of the perfect measurement (through the error-free sensor models), realistic error models are developed to simulate real IMU behavior. Finally, the developed simulator is subjected to different validation tests.

Magnetometer-Augmented IMU Simulator: In-Depth Elaboration

PubMed Central

Brunner, Thomas; Lauffenburger, Jean-Philippe; Changey, Sébastien; Basset, Michel

2015-01-01

The location of objects is a growing research topic due, for instance, to the expansion of civil drones or intelligent vehicles. This expansion was made possible through the development of microelectromechanical systems (MEMS), inexpensive and miniaturized inertial sensors. In this context, this article describes the development of a new simulator which generates sensor measurements, giving a specific input trajectory. This will allow the comparison of pose estimation algorithms. To develop this simulator, the measurement equations of every type of sensor have to be analytically determined. To achieve this objective, classical kinematic equations are used for the more common sensors, i.e., accelerometers and rate gyroscopes. As nowadays, the MEMS inertial measurement units (IMUs) are generally magnetometer-augmented, an absolute world magnetic model is implemented. After the determination of the perfect measurement (through the error-free sensor models), realistic error models are developed to simulate real IMU behavior. Finally, the developed simulator is subjected to different validation tests. PMID:25746095

Real-Time Telemetry System for Monitoring Motion of Ships Based on Inertial Sensors.

PubMed

Núñez, José M; Araújo, Marta G; García-Tuñón, I

2017-04-25

A telemetry system for real-time monitoring of the motions, position, speed and course of a ship at sea is presented in this work. The system, conceived as a subsystem of a radar cross-section measurement unit, could also be used in other applications as ships dynamics characterization, on-board cranes, antenna stabilizers, etc. This system was designed to be stand-alone, reliable, easy to deploy, low-cost and free of requirements related to stabilization procedures. In order to achieve such a unique combination of functionalities, we have developed a telemetry system based on redundant inertial and magnetic sensors and GPS (Global Positioning System) measurements. It provides a proper data storage and also has real-time radio data transmission capabilities to an on-shore station. The output of the system can be used either for on-line or off-line processing. Additionally, the system uses dual technologies and COTS (Commercial Off-The-Shelf) components. Motion-positioning measurements and radio data link tests were successfully carried out in several ships of the Spanish Navy, proving the compliance with the design targets and validating our telemetry system.

Trends Supporting the In-Field Use of Wearable Inertial Sensors for Sport Performance Evaluation: A Systematic Review.

PubMed

Camomilla, Valentina; Bergamini, Elena; Fantozzi, Silvia; Vannozzi, Giuseppe

2018-03-15

Recent technological developments have led to the production of inexpensive, non-invasive, miniature magneto-inertial sensors, ideal for obtaining sport performance measures during training or competition. This systematic review evaluates current evidence and the future potential of their use in sport performance evaluation. Articles published in English (April 2017) were searched in Web-of-Science, Scopus, Pubmed, and Sport-Discus databases. A keyword search of titles, abstracts and keywords which included studies using accelerometers, gyroscopes and/or magnetometers to analyse sport motor-tasks performed by athletes (excluding risk of injury, physical activity, and energy expenditure) resulted in 2040 papers. Papers and reference list screening led to the selection of 286 studies and 23 reviews. Information on sport, motor-tasks, participants, device characteristics, sensor position and fixing, experimental setting and performance indicators was extracted. The selected papers dealt with motor capacity assessment (51 papers), technique analysis (163), activity classification (19), and physical demands assessment (61). Focus was placed mainly on elite and sub-elite athletes (59%) performing their sport in-field during training (62%) and competition (7%). Measuring movement outdoors created opportunities in winter sports (8%), water sports (16%), team sports (25%), and other outdoor activities (27%). Indications on the reliability of sensor-based performance indicators are provided, together with critical considerations and future trends.

Quantum gyroscope based on Berry phase of spins in diamond

NASA Astrophysics Data System (ADS)

Song, Xuerui; Wang, Liujun; Diao, Wenting; Duan, Chongdi

2018-02-01

Gyroscope is the crucial sensor of the inertial navigation system, there is always high demand to improve the sensitivity and reduce the size of the gyroscopes. Using the NV center electronic spin and nuclear spin qubits in diamond, we introduce the research of new types of quantum gyroscopes based on the Berry phase shifts of the spin states during the rotation of the sensor systems. Compared with the performance of the traditional MEMS gyroscope, the sensitivity of the new types of quantum gyroscopes was highly improved and the spatial resolution was reduced to nano-scale. With the help of micro-manufacturing technology in the semiconductor industry, the quantum gyroscopes introduced here can be further integrated into chip-scale sensors.

A study of redundancy management strategy for tetrad strap-down inertial systems. [error detection codes

NASA Technical Reports Server (NTRS)

Hruby, R. J.; Bjorkman, W. S.; Schmidt, S. F.; Carestia, R. A.

1979-01-01

Algorithms were developed that attempt to identify which sensor in a tetrad configuration has experienced a step failure. An algorithm is also described that provides a measure of the confidence with which the correct identification was made. Experimental results are presented from real-time tests conducted on a three-axis motion facility utilizing an ortho-skew tetrad strapdown inertial sensor package. The effects of prediction errors and of quantization on correct failure identification are discussed as well as an algorithm for detecting second failures through prediction.

Physical Human Activity Recognition Using Wearable Sensors.

PubMed

Attal, Ferhat; Mohammed, Samer; Dedabrishvili, Mariam; Chamroukhi, Faicel; Oukhellou, Latifa; Amirat, Yacine

2015-12-11

This paper presents a review of different classification techniques used to recognize human activities from wearable inertial sensor data. Three inertial sensor units were used in this study and were worn by healthy subjects at key points of upper/lower body limbs (chest, right thigh and left ankle). Three main steps describe the activity recognition process: sensors' placement, data pre-processing and data classification. Four supervised classification techniques namely, k-Nearest Neighbor (k-NN), Support Vector Machines (SVM), Gaussian Mixture Models (GMM), and Random Forest (RF) as well as three unsupervised classification techniques namely, k-Means, Gaussian mixture models (GMM) and Hidden Markov Model (HMM), are compared in terms of correct classification rate, F-measure, recall, precision, and specificity. Raw data and extracted features are used separately as inputs of each classifier. The feature selection is performed using a wrapper approach based on the RF algorithm. Based on our experiments, the results obtained show that the k-NN classifier provides the best performance compared to other supervised classification algorithms, whereas the HMM classifier is the one that gives the best results among unsupervised classification algorithms. This comparison highlights which approach gives better performance in both supervised and unsupervised contexts. It should be noted that the obtained results are limited to the context of this study, which concerns the classification of the main daily living human activities using three wearable accelerometers placed at the chest, right shank and left ankle of the subject.

Development of esMOCA Biomechanic, Motion Capture Instrumentation for Biomechanics Analysis

NASA Astrophysics Data System (ADS)

Arendra, A.; Akhmad, S.

2018-01-01

This study aims to build motion capture instruments using inertial measurement unit sensors to assist in the analysis of biomechanics. Sensors used are accelerometer and gyroscope. Estimation of orientation sensors is done by digital motion processing in each sensor nodes. There are nine sensor nodes attached to the upper limbs. This sensor is connected to the pc via a wireless sensor network. The development of kinematics and inverse dynamamic models of the upper limb is done in simulink simmechanic. The kinematic model receives streaming data of sensor nodes mounted on the limbs. The output of the kinematic model is the pose of each limbs and visualized on display. The dynamic inverse model outputs the reaction force and reaction moment of each joint based on the limb motion input. Model validation in simulink with mathematical model of mechanical analysis showed results that did not differ significantly

MEMS and FOG Technologies for Tactical and Navigation Grade Inertial Sensors—Recent Improvements and Comparison

PubMed Central

Deppe, Olaf; Dorner, Georg; König, Stefan; Martin, Tim; Voigt, Sven; Zimmermann, Steffen

2017-01-01

In the following paper, we present an industry perspective of inertial sensors for navigation purposes driven by applications and customer needs. Microelectromechanical system (MEMS) inertial sensors have revolutionized consumer, automotive, and industrial applications and they have started to fulfill the high end tactical grade performance requirements of hybrid navigation systems on a series production scale. The Fiber Optic Gyroscope (FOG) technology, on the other hand, is further pushed into the near navigation grade performance region and beyond. Each technology has its special pros and cons making it more or less suitable for specific applications. In our overview paper, we present latest improvements at NG LITEF in tactical and navigation grade MEMS accelerometers, MEMS gyroscopes, and Fiber Optic Gyroscopes, based on our long-term experience in the field. We demonstrate how accelerometer performance has improved by switching from wet etching to deep reactive ion etching (DRIE) technology. For MEMS gyroscopes, we show that better than 1°/h series production devices are within reach, and for FOGs we present how limitations in noise performance were overcome by signal processing. The paper also intends a comparison of the different technologies, emphasizing suitability for different navigation applications, thus providing guidance to system engineers. PMID:28287483

Validity of the Instrumented Push and Release Test to Quantify Postural Responses in Persons With Multiple Sclerosis.

PubMed

El-Gohary, Mahmoud; Peterson, Daniel; Gera, Geetanjali; Horak, Fay B; Huisinga, Jessie M

2017-07-01

To test the validity of wearable inertial sensors to provide objective measures of postural stepping responses to the push and release clinical test in people with multiple sclerosis. Cross-sectional study. University medical center balance disorder laboratory. Total sample N=73; persons with multiple sclerosis (PwMS) n=52; healthy controls n=21. Stepping latency, time and number of steps required to reach stability, and initial step length were calculated using 3 inertial measurement units placed on participants' lumbar spine and feet. Correlations between inertial sensor measures and measures obtained from the laboratory-based systems were moderate to strong and statistically significant for all variables: time to release (r=.992), latency (r=.655), time to stability (r=.847), time of first heel strike (r=.665), number of steps (r=.825), and first step length (r=.592). Compared with healthy controls, PwMS demonstrated a longer time to stability and required a larger number of steps to reach stability. The instrumented push and release test is a valid measure of postural responses in PwMS and could be used as a clinical outcome measures for patient care decisions or for clinical trials aimed at improving postural control in PwMS. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Evaluation of Event-Based Algorithms for Optical Flow with Ground-Truth from Inertial Measurement Sensor

PubMed Central

Rueckauer, Bodo; Delbruck, Tobi

2016-01-01

In this study we compare nine optical flow algorithms that locally measure the flow normal to edges according to accuracy and computation cost. In contrast to conventional, frame-based motion flow algorithms, our open-source implementations compute optical flow based on address-events from a neuromorphic Dynamic Vision Sensor (DVS). For this benchmarking we created a dataset of two synthesized and three real samples recorded from a 240 × 180 pixel Dynamic and Active-pixel Vision Sensor (DAVIS). This dataset contains events from the DVS as well as conventional frames to support testing state-of-the-art frame-based methods. We introduce a new source for the ground truth: In the special case that the perceived motion stems solely from a rotation of the vision sensor around its three camera axes, the true optical flow can be estimated using gyro data from the inertial measurement unit integrated with the DAVIS camera. This provides a ground-truth to which we can compare algorithms that measure optical flow by means of motion cues. An analysis of error sources led to the use of a refractory period, more accurate numerical derivatives and a Savitzky-Golay filter to achieve significant improvements in accuracy. Our pure Java implementations of two recently published algorithms reduce computational cost by up to 29% compared to the original implementations. Two of the algorithms introduced in this paper further speed up processing by a factor of 10 compared with the original implementations, at equal or better accuracy. On a desktop PC, they run in real-time on dense natural input recorded by a DAVIS camera. PMID:27199639

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.

Measurement of Infrasound from the Marine Environment

DTIC Science & Technology

2015-09-01

ocean heave, which are due to the change in the background atmospheric pressure as the sensor moves up and down. An external inertial measurement unit ... inertial measurement unit (IMU) was used to estimate the heave, and was highly correlated with the pressure interference signal. Mission area... MEASUREMENT UNIT ..................................................... 13 ADAPTIVE NOISE CANCELATION

Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors.

PubMed

Heredia, Guillermo; Caballero, Fernando; Maza, Iván; Merino, Luis; Viguria, Antidio; Ollero, Aníbal

2009-01-01

This paper presents a method to increase the reliability of Unmanned Aerial Vehicle (UAV) sensor Fault Detection and Identification (FDI) in a multi-UAV context. Differential Global Positioning System (DGPS) and inertial sensors are used for sensor FDI in each UAV. The method uses additional position estimations that augment individual UAV FDI system. These additional estimations are obtained using images from the same planar scene taken from two different UAVs. Since accuracy and noise level of the estimation depends on several factors, dynamic replanning of the multi-UAV team can be used to obtain a better estimation in case of faults caused by slow growing errors of absolute position estimation that cannot be detected by using local FDI in the UAVs. Experimental results with data from two real UAVs are also presented.

Wearable Inertial Sensor Systems for Lower Limb Exercise Detection and Evaluation: A Systematic Review.

PubMed

O'Reilly, Martin; Caulfield, Brian; Ward, Tomas; Johnston, William; Doherty, Cailbhe

2018-05-01

Analysis of lower limb exercises is traditionally completed with four distinct methods: (1) 3D motion capture; (2) depth-camera-based systems; (3) visual analysis from a qualified exercise professional; and (4) self-assessment. Each method is associated with a number of limitations. The aim of this systematic review is to synthesise and evaluate studies which have investigated the capacity for inertial measurement unit (IMU) technologies to assess movement quality in lower limb exercises. A systematic review of studies identified through the databases of PubMed, ScienceDirect and Scopus was conducted. Articles written in English and published in the last 10 years which investigated an IMU system for the analysis of repetition-based targeted lower limb exercises were included. The quality of included studies was measured using an adapted version of the STROBE assessment criteria for cross-sectional studies. The studies were categorised into three groupings: exercise detection, movement classification or measurement validation. Each study was then qualitatively summarised. From the 2452 articles that were identified with the search strategies, 47 papers are included in this review. Twenty-six of the 47 included studies were deemed as being of high quality. Wearable inertial sensor systems for analysing lower limb exercises is a rapidly growing field of research. Research over the past 10 years has predominantly focused on validating measurements that the systems produce and classifying users' exercise quality. There have been very few user evaluation studies and no clinical trials in this field to date.

Loose Coupling of Wearable-Based INSs with Automatic Heading Evaluation.

PubMed

Bousdar Ahmed, Dina; Munoz Diaz, Estefania

2017-11-03

Position tracking of pedestrians by means of inertial sensors is a highly explored field of research. In fact, there are already many approaches to implement inertial navigation systems (INSs). However, most of them use a single inertial measurement unit (IMU) attached to the pedestrian's body. Since wearable-devices will be given items in the future, this work explores the implementation of an INS using two wearable-based IMUs. A loosely coupled approach is proposed to combine the outputs of wearable-based INSs. The latter are based on a pocket-mounted IMU and a foot-mounted IMU. The loosely coupled fusion combines the output of the two INSs not only when these outputs are least erroneous, but also automatically favoring the best output. This approach is named smart update. The main challenge is determining the quality of the heading estimation of each INS, which changes every time. In order to address this, a novel concept to determine the quality of the heading estimation is presented. This concept is subject to a patent application. The results show that the position error rate of the loosely coupled fusion is 10 cm/s better than either the foot INS's or pocket INS's error rate in 95% of the cases.

Postural strategies assessed with inertial sensors in healthy and parkinsonian subjects.

PubMed

Baston, Chiara; Mancini, Martina; Schoneburg, Bernadette; Horak, Fay; Rocchi, Laura

2014-01-01

The present study introduces a novel instrumented method to characterize postural movement strategies to maintain balance during stance (ankle and hip strategy), by means of inertial sensors, positioned on the legs and on the trunk. We evaluated postural strategies in subjects with 2 types of Parkinsonism: idiopathic Parkinson's disease (PD) and Progressive Supranuclear Palsy (PSP), and in age-matched control subjects standing under perturbed conditions implemented by the Sensory Organization Test (SOT). Coordination between the upper and lower segments of the body during postural sway was measured using a covariance index over time, by a sliding-window algorithm. Afterwards, a postural strategy index was computed. We also measured the amount of postural sway, as adjunctive information to characterize balance, by the root mean square of the horizontal trunk acceleration signal (RMS). showed that control subjects were able to change their postural strategy, whilst PSP and PD subjects persisted in use of an ankle strategy in all conditions. PD subjects had RMS values similar to control subjects even without changing postural strategy appropriately, whereas PSP subjects showed much larger RMS values than controls, resulting in several falls during the most challenging SOT conditions (5 and 6). Results are in accordance with the corresponding clinical literature describing postural behavior in the same kind of subjects. The proposed strategy index, based on the use of inertial sensors on the upper and lower body segments, is a promising and unobtrusive tool to characterize postural strategies performed to attain balance. Copyright © 2014 Elsevier B.V. All rights reserved.

A high-accuracy two-position alignment inertial navigation system for lunar rovers aided by a star sensor with a calibration and positioning function

NASA Astrophysics Data System (ADS)

Lu, Jiazhen; Lei, Chaohua; Yang, Yanqiang; Liu, Ming

2016-12-01

An integrated inertial/celestial navigation system (INS/CNS) has wide applicability in lunar rovers as it provides accurate and autonomous navigational information. Initialization is particularly vital for a INS. This paper proposes a two-position initialization method based on a standard Kalman filter. The difference between the computed star vector and the measured star vector is measured. With the aid of a star sensor and the two positions, the attitudinal and positional errors can be greatly reduced, and the biases of three gyros and accelerometers can also be estimated. The semi-physical simulation results show that the positional and attitudinal errors converge within 0.07″ and 0.1 m, respectively, when the given initial positional error is 1 km and the attitudinal error is 10°. These good results show that the proposed method can accomplish alignment, positioning and calibration functions simultaneously. Thus the proposed two-position initialization method has the potential for application in lunar rover navigation.

Attitude Heading Reference System Using MEMS Inertial Sensors with Dual-Axis Rotation

PubMed Central

Kang, Li; Ye, Lingyun; Song, Kaichen; Zhou, Yang

2014-01-01

This paper proposes a low cost and small size attitude and heading reference system based on MEMS inertial sensors. A dual-axis rotation structure with a proper rotary scheme according to the design principles is applied in the system to compensate for the attitude and heading drift caused by the large gyroscope biases. An optimization algorithm is applied to compensate for the installation angle error between the body frame and the rotation table's frame. Simulations and experiments are carried out to evaluate the performance of the AHRS. The results show that the proper rotation could significantly reduce the attitude and heading drifts. Moreover, the new AHRS is not affected by magnetic interference. After the rotation, the attitude and heading are almost just oscillating in a range. The attitude error is about 3° and the heading error is less than 3° which are at least 5 times better than the non-rotation condition. PMID:25268911

Integrated INS/GPS Navigation from a Popular Perspective

NASA Technical Reports Server (NTRS)

Omerbashich, Mensur

2002-01-01

Inertial navigation, blended with other navigation aids, Global Positioning System (GPS) in particular, has gained significance due to enhanced navigation and inertial reference performance and dissimilarity for fault tolerance and anti-jamming. Relatively new concepts based upon using Differential GPS (DGPS) blended with Inertial (and visual) Navigation Sensors (INS) offer the possibility of low cost, autonomous aircraft landing. The FAA has decided to implement the system in a sophisticated form as a new standard navigation tool during this decade. There have been a number of new inertial sensor concepts in the recent past that emphasize increased accuracy of INS/GPS versus INS and reliability of navigation, as well as lower size and weight, and higher power, fault tolerance, and long life. The principles of GPS are not discussed; rather the attention is directed towards general concepts and comparative advantages. A short introduction to the problems faced in kinematics is presented. The intention is to relate the basic principles of kinematics to probably the most used navigation method in the future-INS/GPS. An example of the airborne INS is presented, with emphasis on how it works. The discussion of the error types and sources in navigation, and of the role of filters in optimal estimation of the errors then follows. The main question this paper is trying to answer is 'What are the benefits of the integration of INS and GPS and how is this, navigation concept of the future achieved in reality?' The main goal is to communicate the idea about what stands behind a modern navigation method.

Ultrasensitive Inertial and Force Sensors with Diamagnetically Levitated Magnets

NASA Astrophysics Data System (ADS)

Prat-Camps, J.; Teo, C.; Rusconi, C. C.; Wieczorek, W.; Romero-Isart, O.

2017-09-01

We theoretically show that a magnet can be stably levitated on top of a punctured superconductor sheet in the Meissner state without applying any external field. The trapping potential created by such induced-only superconducting currents is characterized for magnetic spheres ranging from tens of nanometers to tens of millimeters. Such a diamagnetically levitated magnet is predicted to be extremely well isolated from the environment. We propose to use it as an ultrasensitive force and inertial sensor. A magnetomechanical readout of its displacement can be performed by using superconducting quantum interference devices. An analysis using current technology shows that force and acceleration sensitivities on the order of 10-23 N /√{Hz } (for a 100-nm magnet) and 10-14 g /√{Hz } (for a 10-mm magnet) might be within reach in a cryogenic environment. Such remarkable sensitivities, both in force and acceleration, can be used for a variety of purposes, from designing ultrasensitive inertial sensors for technological applications (e.g., gravimetry, avionics, and space industry), to scientific investigations on measuring Casimir forces of magnetic origin and gravitational physics.

Autonomous star tracker based on active pixel sensors (APS)

NASA Astrophysics Data System (ADS)

Schmidt, U.

2017-11-01

Star trackers are opto-electronic sensors used onboard of satellites for the autonomous inertial attitude determination. During the last years, star trackers became more and more important in the field of the attitude and orbit control system (AOCS) sensors. High performance star trackers are based up today on charge coupled device (CCD) optical camera heads. The Jena-Optronik GmbH is active in the field of opto-electronic sensors like star trackers since the early 80-ties. Today, with the product family ASTRO5, ASTRO10 and ASTRO15, all marked segments like earth observation, scientific applications and geo-telecom are supplied to European and Overseas customers. A new generation of star trackers can be designed based on the APS detector technical features. The measurement performance of the current CCD based star trackers can be maintained, the star tracker functionality, reliability and robustness can be increased while the unit costs are saved.

Loosely Coupled GPS-Aided Inertial Navigation System for Range Safety

NASA Technical Reports Server (NTRS)

Heatwole, Scott; Lanzi, Raymond J.

2010-01-01

The Autonomous Flight Safety System (AFSS) aims to replace the human element of range safety operations, as well as reduce reliance on expensive, downrange assets for launches of expendable launch vehicles (ELVs). The system consists of multiple navigation sensors and flight computers that provide a highly reliable platform. It is designed to ensure that single-event failures in a flight computer or sensor will not bring down the whole system. The flight computer uses a rules-based structure derived from range safety requirements to make decisions whether or not to destroy the rocket.

Mechanical monolithic compact sensors for real-time linear and angular broadband low frequency monitoring and control of spacecrafts and satellites

NASA Astrophysics Data System (ADS)

Barone, F.; Giordano, G.

2017-09-01

In this paper we describe the characteristics and performances of a monolithic sensor designed for low frequency motion measurement of spacecrafts and satellites, whose mechanics is based on the UNISA Folded Pendulum. The latter, developed for ground-based applications, exhibits unique features (compactness, lightness, scalability, low resonance frequency and high quality factor), consequence of the action of the gravitational force on its inertial mass. In this paper we introduce and discuss the general methodology used to extend the application of ground-based folded pendulums to space, also in total absence of gravity, still keeping all their peculiar features and characteristics.

Error Modelling for Multi-Sensor Measurements in Infrastructure-Free Indoor Navigation

PubMed Central

Ruotsalainen, Laura; Kirkko-Jaakkola, Martti; Rantanen, Jesperi; Mäkelä, Maija

2018-01-01

The long-term objective of our research is to develop a method for infrastructure-free simultaneous localization and mapping (SLAM) and context recognition for tactical situational awareness. Localization will be realized by propagating motion measurements obtained using a monocular camera, a foot-mounted Inertial Measurement Unit (IMU), sonar, and a barometer. Due to the size and weight requirements set by tactical applications, Micro-Electro-Mechanical (MEMS) sensors will be used. However, MEMS sensors suffer from biases and drift errors that may substantially decrease the position accuracy. Therefore, sophisticated error modelling and implementation of integration algorithms are key for providing a viable result. Algorithms used for multi-sensor fusion have traditionally been different versions of Kalman filters. However, Kalman filters are based on the assumptions that the state propagation and measurement models are linear with additive Gaussian noise. Neither of the assumptions is correct for tactical applications, especially for dismounted soldiers, or rescue personnel. Therefore, error modelling and implementation of advanced fusion algorithms are essential for providing a viable result. Our approach is to use particle filtering (PF), which is a sophisticated option for integrating measurements emerging from pedestrian motion having non-Gaussian error characteristics. This paper discusses the statistical modelling of the measurement errors from inertial sensors and vision based heading and translation measurements to include the correct error probability density functions (pdf) in the particle filter implementation. Then, model fitting is used to verify the pdfs of the measurement errors. Based on the deduced error models of the measurements, particle filtering method is developed to fuse all this information, where the weights of each particle are computed based on the specific models derived. The performance of the developed method is tested via two experiments, one at a university’s premises and another in realistic tactical conditions. The results show significant improvement on the horizontal localization when the measurement errors are carefully modelled and their inclusion into the particle filtering implementation correctly realized. PMID:29443918

Inertial Pocket Navigation System: Unaided 3D Positioning

PubMed Central

Munoz Diaz, Estefania

2015-01-01

Inertial navigation systems use dead-reckoning to estimate the pedestrian's position. There are two types of pedestrian dead-reckoning, the strapdown algorithm and the step-and-heading approach. Unlike the strapdown algorithm, which consists of the double integration of the three orthogonal accelerometer readings, the step-and-heading approach lacks the vertical displacement estimation. We propose the first step-and-heading approach based on unaided inertial data solving 3D positioning. We present a step detector for steps up and down and a novel vertical displacement estimator. Our navigation system uses the sensor introduced in the front pocket of the trousers, a likely location of a smartphone. The proposed algorithms are based on the opening angle of the leg or pitch angle. We analyzed our step detector and compared it with the state-of-the-art, as well as our already proposed step length estimator. Lastly, we assessed our vertical displacement estimator in a real-world scenario. We found that our algorithms outperform the literature step and heading algorithms and solve 3D positioning using unaided inertial data. Additionally, we found that with the pitch angle, five activities are distinguishable: standing, sitting, walking, walking up stairs and walking down stairs. This information complements the pedestrian location and is of interest for applications, such as elderly care. PMID:25897501

Real-Time Motion Tracking for Mobile Augmented/Virtual Reality Using Adaptive Visual-Inertial Fusion

PubMed Central

Fang, Wei; Zheng, Lianyu; Deng, Huanjun; Zhang, Hongbo

2017-01-01

In mobile augmented/virtual reality (AR/VR), real-time 6-Degree of Freedom (DoF) motion tracking is essential for the registration between virtual scenes and the real world. However, due to the limited computational capacity of mobile terminals today, the latency between consecutive arriving poses would damage the user experience in mobile AR/VR. Thus, a visual-inertial based real-time motion tracking for mobile AR/VR is proposed in this paper. By means of high frequency and passive outputs from the inertial sensor, the real-time performance of arriving poses for mobile AR/VR is achieved. In addition, to alleviate the jitter phenomenon during the visual-inertial fusion, an adaptive filter framework is established to cope with different motion situations automatically, enabling the real-time 6-DoF motion tracking by balancing the jitter and latency. Besides, the robustness of the traditional visual-only based motion tracking is enhanced, giving rise to a better mobile AR/VR performance when motion blur is encountered. Finally, experiments are carried out to demonstrate the proposed method, and the results show that this work is capable of providing a smooth and robust 6-DoF motion tracking for mobile AR/VR in real-time. PMID:28475145

Real-Time Motion Tracking for Mobile Augmented/Virtual Reality Using Adaptive Visual-Inertial Fusion.

PubMed

Fang, Wei; Zheng, Lianyu; Deng, Huanjun; Zhang, Hongbo

2017-05-05

In mobile augmented/virtual reality (AR/VR), real-time 6-Degree of Freedom (DoF) motion tracking is essential for the registration between virtual scenes and the real world. However, due to the limited computational capacity of mobile terminals today, the latency between consecutive arriving poses would damage the user experience in mobile AR/VR. Thus, a visual-inertial based real-time motion tracking for mobile AR/VR is proposed in this paper. By means of high frequency and passive outputs from the inertial sensor, the real-time performance of arriving poses for mobile AR/VR is achieved. In addition, to alleviate the jitter phenomenon during the visual-inertial fusion, an adaptive filter framework is established to cope with different motion situations automatically, enabling the real-time 6-DoF motion tracking by balancing the jitter and latency. Besides, the robustness of the traditional visual-only based motion tracking is enhanced, giving rise to a better mobile AR/VR performance when motion blur is encountered. Finally, experiments are carried out to demonstrate the proposed method, and the results show that this work is capable of providing a smooth and robust 6-DoF motion tracking for mobile AR/VR in real-time.

SGA-WZ: A New Strapdown Airborne Gravimeter

PubMed Central

Huang, Yangming; Olesen, Arne Vestergaard; Wu, Meiping; Zhang, Kaidong

2012-01-01

Inertial navigation systems and gravimeters are now routinely used to map the regional gravitational quantities from an aircraft with mGal accuracy and a spatial resolution of a few kilometers. However, airborne gravimeter of this kind is limited by the inaccuracy of the inertial sensor performance, the integrated navigation technique and the kinematic acceleration determination. As the GPS technique developed, the vehicle acceleration determination is no longer the limiting factor in airborne gravity due to the cancellation of the common mode acceleration in differential mode. A new airborne gravimeter taking full advantage of the inertial navigation system is described with improved mechanical design, high precision time synchronization, better thermal control and optimized sensor modeling. Apart from the general usage, the Global Positioning System (GPS) after differentiation is integrated to the inertial navigation system which provides not only more precise altitude information along with the navigation aiding, but also an effective way to calculate the vehicle acceleration. Design description and test results on the performance of the gyroscopes and accelerations will be emphasized. Analysis and discussion of the airborne field test results are also given. PMID:23012545

Error reduction by combining strapdown inertial measurement units in a baseball stitch

NASA Astrophysics Data System (ADS)

Tracy, Leah

A poor musical performance is rarely due to an inferior instrument. When a device is under performing, the temptation is to find a better device or a new technology to achieve performance objectives; however, another solution may be improving how existing technology is used through a better understanding of device characteristics, i.e., learning to play the instrument better. This thesis explores improving position and attitude estimates of inertial navigation systems (INS) through an understanding of inertial sensor errors, manipulating inertial measurement units (IMUs) to reduce that error and multisensor fusion of multiple IMUs to reduce error in a GPS denied environment.

Positional Accuracy of Airborne Integrated Global Positioning and Inertial Navigation Systems for Mapping in Glen Canyon, Arizona

USGS Publications Warehouse

Sanchez, Richard D.; Hothem, Larry D.

2002-01-01

High-resolution airborne and satellite image sensor systems integrated with onboard data collection based on the Global Positioning System (GPS) and inertial navigation systems (INS) may offer a quick and cost-effective way to gather accurate topographic map information without ground control or aerial triangulation. The Applanix Corporation?s Position and Orientation Solutions for Direct Georeferencing of aerial photography was used in this project to examine the positional accuracy of integrated GPS/INS for terrain mapping in Glen Canyon, Arizona. The research application in this study yielded important information on the usefulness and limits of airborne integrated GPS/INS data-capture systems for mapping.

Candidate configuration trade study, Stellar-inertial Measurement Systems (SIMS) for an Earth Observation Satellite (EOS)

NASA Technical Reports Server (NTRS)

Ogletree, G.; Coccoli, J.; Mckern, R.; Smith, M.; White, R.

1972-01-01

The results of analytical and simulation studies of the stellar-inertial measurement system (SIMS) for an earth observation satellite are presented. Subsystem design analyses and sensor design trades are reported. Three candidate systems are considered: (1) structure-mounted gyros with structure-mounted star mapper, (2) structure-mounted gyros with gimbaled star tracker, and (3) gimbaled gyros with structure-mounted star mapper. The purpose of the study is to facilitate the decisions pertaining to gimbaled versus structure-mounted gyros and star sensors, and combinations of systems suitable for the EOS satellite.

Hubble Space Telescope Angular Velocity Estimation During the Robotic Servicing Mission

NASA Technical Reports Server (NTRS)

Thienel, Julie K.; Sanner, Robert M.

2005-01-01

In 2004 NASA began investigation of a robotic servicing mission for the Hubble Space Telescope (HST). Such a mission would require estimates of the HST attitude and rates in order to achieve a capture by the proposed Hubble robotic vehicle (HRV). HRV was to be equipped with vision-based sensors, capable of estimating the relative attitude between HST and HRV. The inertial HST attitude is derived from the measured relative attitude and the HRV computed inertial attitude. However, the relative rate between HST and HRV cannot be measured directly. Therefore, the HST rate with respect to inertial space is not known. Two approaches are developed to estimate the HST rates. Both methods utilize the measured relative attitude and the HRV inertial attitude and rates. First, a nonlinear estimator is developed. The nonlinear approach estimates the HST rate through an estimation of the inertial angular momentum. The development includes an analysis of the estimator stability given errors in the measured attitude. Second, a linearized approach is developed. The linearized approach is a pseudo-linear Kalman filter. Simulation test results for both methods are given, including scenarios with erroneous measured attitudes. Even though the development began as an application for the HST robotic servicing mission, the methods presented are applicable to any rendezvous/capture mission involving a non-cooperative target spacecraft.

Systematic Calibration for Ultra-High Accuracy Inertial Measurement Units.

PubMed

Cai, Qingzhong; Yang, Gongliu; Song, Ningfang; Liu, Yiliang

2016-06-22

An inertial navigation system (INS) has been widely used in challenging GPS environments. With the rapid development of modern physics, an atomic gyroscope will come into use in the near future with a predicted accuracy of 5 × 10(-6)°/h or better. However, existing calibration methods and devices can not satisfy the accuracy requirements of future ultra-high accuracy inertial sensors. In this paper, an improved calibration model is established by introducing gyro g-sensitivity errors, accelerometer cross-coupling errors and lever arm errors. A systematic calibration method is proposed based on a 51-state Kalman filter and smoother. Simulation results show that the proposed calibration method can realize the estimation of all the parameters using a common dual-axis turntable. Laboratory and sailing tests prove that the position accuracy in a five-day inertial navigation can be improved about 8% by the proposed calibration method. The accuracy can be improved at least 20% when the position accuracy of the atomic gyro INS can reach a level of 0.1 nautical miles/5 d. Compared with the existing calibration methods, the proposed method, with more error sources and high order small error parameters calibrated for ultra-high accuracy inertial measurement units (IMUs) using common turntables, has a great application potential in future atomic gyro INSs.

Differential optical shadow sensor for sub-nanometer displacement measurement and its application to drag-free satellites.

PubMed

Zoellner, Andreas; Tan, Si; Saraf, Shailendhar; Alfauwaz, Abdul; DeBra, Dan; Buchman, Sasha; Lipa, John A

2017-10-16

We present a method for 3D sub-nanometer displacement measurement using a set of differential optical shadow sensors. It is based on using pairs of collimated beams on opposite sides of an object that are partially blocked by it. Applied to a sphere, our 3-axis sensor module consists of 8 parallel beam-detector sets for redundancy. The sphere blocks half of each beam's power in the nominal centered position, and any displacement can be measured by the differential optical power changes amongst the pairs of detectors. We have experimentally demonstrated a displacement sensitivity of 0.87nm/Hz at 1 Hz and 0.39nm/Hz at 10 Hz. We describe the application of the module to the inertial sensor of a drag-free satellite, which can potentially be used for navigation, geodesy and fundamental science experiments as well as ground based applications.

The Design of an Autonomous Underwater Vehicle for Water Quality Monitoring

NASA Astrophysics Data System (ADS)

Li, Yulong; Liu, Rong; Liu, Shujin

2018-01-01

This paper describes the development of a civilian-used autonomous underwater vehicle (AUV) for water quality monitoring at reservoirs and watercourses that can obtain realtime visual and locational information. The mechanical design was completed with CAD software Solidworks. Four thrusters—two horizontal and two vertical—on board enable the vehicle to surge, heave, yaw, and pitch. A specialized water sample collection compartment is designed to perform water collection at target locations. The vehicle has a central controller—STM32—and a sub-coordinate controller—Arduino MEGA 2560—that coordinates multiple sensors including an inertial sensor, ultrasonic sensors, etc. Global Navigation Satellite System (GNSS) and the inertial sensor enable the vehicle’s localization. Remote operators monitor and control the vehicle via a host computer system. Operators choose either semi-autonomous mode in which they set target locations or manual mode. The experimental results show that the vehicle is able to perform well in either mode.

Attitude measurement: Principles and sensors

NASA Technical Reports Server (NTRS)

Duchon, P.; Vermande, M. P.

1981-01-01

Tools used in the measurement of satellite attitude are described. Attention is given to the elements that characterize an attitude sensor, the references employed (stars, moon, Sun, Earth, magnetic fields, etc.), and the detectors (optical, magnetic, and inertial). Several examples of attitude sensors are described, including sun sensors, star sensors, earth sensors, triaxial magnetometers, and gyrometers. Finally, sensor combinations that make it possible to determine a complete attitude are considered; the SPOT attitude measurement system and a combined CCD star sensor-gyrometer system are discussed.

Lightweight, Miniature Inertial Measurement System

NASA Technical Reports Server (NTRS)

Tang, Liang; Crassidis, Agamemnon

2012-01-01

A miniature, lighter-weight, and highly accurate inertial navigation system (INS) is coupled with GPS receivers to provide stable and highly accurate positioning, attitude, and inertial measurements while being subjected to highly dynamic maneuvers. In contrast to conventional methods that use extensive, groundbased, real-time tracking and control units that are expensive, large, and require excessive amounts of power to operate, this method focuses on the development of an estimator that makes use of a low-cost, miniature accelerometer array fused with traditional measurement systems and GPS. Through the use of a position tracking estimation algorithm, onboard accelerometers are numerically integrated and transformed using attitude information to obtain an estimate of position in the inertial frame. Position and velocity estimates are subject to drift due to accelerometer sensor bias and high vibration over time, and so require the integration with GPS information using a Kalman filter to provide highly accurate and reliable inertial tracking estimations. The method implemented here uses the local gravitational field vector. Upon determining the location of the local gravitational field vector relative to two consecutive sensors, the orientation of the device may then be estimated, and the attitude determined. Improved attitude estimates further enhance the inertial position estimates. The device can be powered either by batteries, or by the power source onboard its target platforms. A DB9 port provides the I/O to external systems, and the device is designed to be mounted in a waterproof case for all-weather conditions.

Wellbore inertial directional surveying system

DOEpatents

Andreas, R.D.; Heck, G.M.; Kohler, S.M.; Watts, A.C.

1982-09-08

A wellbore inertial directional surveying system for providing a complete directional survey of an oil or gas well borehole to determine the displacement in all three directions of the borehole path relative to the well head at the surface. The information generated by the present invention is especially useful when numerous wells are drilled to different geographical targets from a single offshore platform. Accurate knowledge of the path of the borehole allows proper well spacing and provides assurance that target formations are reached. The tool is lowered down into a borehole on an electrical cable. A computer positioned on the surface communicates with the tool via the cable. The tool contains a sensor block which is supported on a single gimbal, the rotation axis of which is aligned with the cylinder axis of the tool and, correspondingly, the borehole. The gyroscope measurement of the sensor block rotation is used in a null-seeking servo loop which essentially prevents rotation of the sensor block about the gimbal axis. Angular rates of the sensor block about axes which are perpendicular to te gimbal axis are measured by gyroscopes in a manner similar to a strapped-down arrangement. Three accelerometers provide acceleration information as the tool is lowered within the borehole. The uphole computer derives position information based upon acceleration information and angular rate information. Kalman estimation techniques are used to compensate for system errors. 25 figures.

Wellbore inertial directional surveying system

DOEpatents

Andreas, Ronald D.; Heck, G. Michael; Kohler, Stewart M.; Watts, Alfred C.

1991-01-01

A wellbore inertial directional surveying system for providing a complete directional survey of an oil or gas well borehole to determine the displacement in all three directions of the borehole path relative to the well head at the surface. The information generated by the present invention is especially useful when numerous wells are drilled to different geographical targets from a single off-shore platform. Accurate knowledge of the path of the borehole allows proper well spacing and provides assurance that target formations are reached. The tool is lowered down into a borehole on the electrical cable. A computer positioned on the surface communicates with the tool via the cable. The tool contains a sensor block which is supported on a single gimbal, the rotation axis of which is aligned with the cylinder axis of the tool and, correspondingly, the borehole. The gyroscope measurement of the sensor block rotation is used in a null-seeking servo loop which essentially prevents rotation of the sensor block aboutthe gimbal axis. Angular rates of the sensor block about axes which are perpendicular to the gimbal axis are measured by gyroscopes in a manner similar to a strapped-down arrangement. Three accelerometers provide acceleration information as the tool is lowered within the borehole. The uphole computer derives position information based upon acceleration information and anular rate information. Kalman estimation techniques are used to compensate for system errors.

Trends Supporting the In-Field Use of Wearable Inertial Sensors for Sport Performance Evaluation: A Systematic Review

PubMed Central

2018-01-01

Recent technological developments have led to the production of inexpensive, non-invasive, miniature magneto-inertial sensors, ideal for obtaining sport performance measures during training or competition. This systematic review evaluates current evidence and the future potential of their use in sport performance evaluation. Articles published in English (April 2017) were searched in Web-of-Science, Scopus, Pubmed, and Sport-Discus databases. A keyword search of titles, abstracts and keywords which included studies using accelerometers, gyroscopes and/or magnetometers to analyse sport motor-tasks performed by athletes (excluding risk of injury, physical activity, and energy expenditure) resulted in 2040 papers. Papers and reference list screening led to the selection of 286 studies and 23 reviews. Information on sport, motor-tasks, participants, device characteristics, sensor position and fixing, experimental setting and performance indicators was extracted. The selected papers dealt with motor capacity assessment (51 papers), technique analysis (163), activity classification (19), and physical demands assessment (61). Focus was placed mainly on elite and sub-elite athletes (59%) performing their sport in-field during training (62%) and competition (7%). Measuring movement outdoors created opportunities in winter sports (8%), water sports (16%), team sports (25%), and other outdoor activities (27%). Indications on the reliability of sensor-based performance indicators are provided, together with critical considerations and future trends. PMID:29543747

An Adaptive Orientation Estimation Method for Magnetic and Inertial Sensors in the Presence of Magnetic Disturbances

PubMed Central

Fan, Bingfei; Li, Qingguo; Wang, Chao; Liu, Tao

2017-01-01

Magnetic and inertial sensors have been widely used to estimate the orientation of human segments due to their low cost, compact size and light weight. However, the accuracy of the estimated orientation is easily affected by external factors, especially when the sensor is used in an environment with magnetic disturbances. In this paper, we propose an adaptive method to improve the accuracy of orientation estimations in the presence of magnetic disturbances. The method is based on existing gradient descent algorithms, and it is performed prior to sensor fusion algorithms. The proposed method includes stationary state detection and magnetic disturbance severity determination. The stationary state detection makes this method immune to magnetic disturbances in stationary state, while the magnetic disturbance severity determination helps to determine the credibility of magnetometer data under dynamic conditions, so as to mitigate the negative effect of the magnetic disturbances. The proposed method was validated through experiments performed on a customized three-axis instrumented gimbal with known orientations. The error of the proposed method and the original gradient descent algorithms were calculated and compared. Experimental results demonstrate that in stationary state, the proposed method is completely immune to magnetic disturbances, and in dynamic conditions, the error caused by magnetic disturbance is reduced by 51.2% compared with original MIMU gradient descent algorithm. PMID:28534858

Integrated multi-sensor fusion for mapping and localization in outdoor environments for mobile robots

NASA Astrophysics Data System (ADS)

Emter, Thomas; Petereit, Janko

2014-05-01

An integrated multi-sensor fusion framework for localization and mapping for autonomous navigation in unstructured outdoor environments based on extended Kalman filters (EKF) is presented. The sensors for localization include an inertial measurement unit, a GPS, a fiber optic gyroscope, and wheel odometry. Additionally a 3D LIDAR is used for simultaneous localization and mapping (SLAM). A 3D map is built while concurrently a localization in a so far established 2D map is estimated with the current scan of the LIDAR. Despite of longer run-time of the SLAM algorithm compared to the EKF update, a high update rate is still guaranteed by sophisticatedly joining and synchronizing two parallel localization estimators.

Estimation of pelvis kinematics in level walking based on a single inertial sensor positioned close to the sacrum: validation on healthy subjects with stereophotogrammetric system.

PubMed

Buganè, Francesca; Benedetti, Maria Grazia; D'Angeli, Valentina; Leardini, Alberto

2014-10-21

Kinematics measures from inertial sensors have a value in the clinical assessment of pathological gait, to track quantitatively the outcome of interventions and rehabilitation programs. To become a standard tool for clinicians, it is necessary to evaluate their capability to provide reliable and comprehensible information, possibly by comparing this with that provided by the traditional gait analysis. The aim of this study was to assess by state-of-the-art gait analysis the reliability of a single inertial device attached to the sacrum to measure pelvis kinematics during level walking. The output signals of the three-axis gyroscope were processed to estimate the spatial orientation of the pelvis in the sagittal (tilt angle), frontal (obliquity) and transverse (rotation) anatomical planes These estimated angles were compared with those provided by a 8 TV-cameras stereophotogrammetric system utilizing a standard experimental protocol, with four markers on the pelvis. This was observed in a group of sixteen healthy subjects while performing three repetitions of level walking along a 10 meter walkway at slow, normal and fast speeds. The determination coefficient, the scale factor and the bias of a linear regression model were calculated to represent the differences between the angular patterns from the two measurement systems. For the intra-subject variability, one volunteer was asked to repeat walking at normal speed 10 times. A good match was observed for obliquity and rotation angles. For the tilt angle, the pattern and range of motion was similar, but a bias was observed, due to the different initial inclination angle in the sagittal plane of the inertial sensor with respect to the pelvis anatomical frame. A good intra-subject consistency has also been shown by the small variability of the pelvic angles as estimated by the new system, confirmed by very small values of standard deviation for all three angles. These results suggest that this inertial device is a reliable alternative to stereophotogrammetric systems for pelvis kinematics measurements, in addition to being easier to use and cheaper. The device can provide to the patient and to the examiner reliable feedback in real-time during routine clinical tests.

Satellite-Based Fusion of Image/Inertial Sensors for Precise Geolocation

DTIC Science & Technology

2009-03-01

largest contributor and is a valid approximation of orbital position prediction [15]. According to Newton, the gravitational force of the Earth onto an...steps in developing an image-aided navigation system for an orbiting satellite is the understanding of the satellite’s trajectory around the Earth . This...Development . . . . . . . . . . . . . . . . . . . . . . . . 77 4.2 Low Earth Orbit Simulation . . . . . . . . . . . . . . . . . . . . . . . 78 4.3 High Earth

Evaluation on the impact of IMU grades on BDS + GPS PPP/INS tightly coupled integration

NASA Astrophysics Data System (ADS)

Gao, Zhouzheng; Ge, Maorong; Shen, Wenbin; Li, You; Chen, Qijin; Zhang, Hongping; Niu, Xiaoji

2017-09-01

The unexpected observing environments in dynamic applications may lead to partial and/or complete satellite signal outages frequently, which can definitely impact on the positioning performance of the Precise Point Positioning (PPP) in terms of decreasing available satellite numbers, breaking the continuity of observations, and degrading PPP's positioning accuracy. Generally, both the Inertial Navigation System (INS) and the multi-constellation Global Navigation Satellite System (GNSS) can be used to enhance the performance of PPP. This paper introduces the mathematical models of the multi-GNSS PPP/INS Tightly Coupled Integration (TCI), and investigates its performance from several aspects. Specifically, it covers (1) the use of the BDS/GPS PPP, PPP/INS, and their combination; (2) three positioning modes including PPP, PPP/INS TCI, and PPP/INS Loosely Coupled Integration (LCI); (3) the use of four various INS systems named navigation grade, tactical grade, auto grade, and Micro-Electro-Mechanical-Sensors (MEMS) one; (4) three PPP observation scenarios including PPP available, partially available, and fully outage. According to the statistics results, (1) the positioning performance of the PPP/INS (either TCI or LCI) mode is insignificantly depended on the grade of inertial sensor, when there are enough available satellites; (2) after the complete GNSS outages, the TCI mode expresses both higher convergence speed and more accurate positioning solutions than the LCI mode. Furthermore, in the TCI mode, using a higher grade inertial sensor is beneficial for the PPP convergence; (3) under the partial GNSS outage situations, the PPP/INS TCI mode position divergence speed is also restrained significantly; and (4) the attitude determination accuracy of the PPP/INS integration is highly correlated with the grade of inertial sensor.

IMU-Based Gait Recognition Using Convolutional Neural Networks and Multi-Sensor Fusion.

PubMed

Dehzangi, Omid; Taherisadr, Mojtaba; ChangalVala, Raghvendar

2017-11-27

The wide spread usage of wearable sensors such as in smart watches has provided continuous access to valuable user generated data such as human motion that could be used to identify an individual based on his/her motion patterns such as, gait. Several methods have been suggested to extract various heuristic and high-level features from gait motion data to identify discriminative gait signatures and distinguish the target individual from others. However, the manual and hand crafted feature extraction is error prone and subjective. Furthermore, the motion data collected from inertial sensors have complex structure and the detachment between manual feature extraction module and the predictive learning models might limit the generalization capabilities. In this paper, we propose a novel approach for human gait identification using time-frequency (TF) expansion of human gait cycles in order to capture joint 2 dimensional (2D) spectral and temporal patterns of gait cycles. Then, we design a deep convolutional neural network (DCNN) learning to extract discriminative features from the 2D expanded gait cycles and jointly optimize the identification model and the spectro-temporal features in a discriminative fashion. We collect raw motion data from five inertial sensors placed at the chest, lower-back, right hand wrist, right knee, and right ankle of each human subject synchronously in order to investigate the impact of sensor location on the gait identification performance. We then present two methods for early (input level) and late (decision score level) multi-sensor fusion to improve the gait identification generalization performance. We specifically propose the minimum error score fusion (MESF) method that discriminatively learns the linear fusion weights of individual DCNN scores at the decision level by minimizing the error rate on the training data in an iterative manner. 10 subjects participated in this study and hence, the problem is a 10-class identification task. Based on our experimental results, 91% subject identification accuracy was achieved using the best individual IMU and 2DTF-DCNN. We then investigated our proposed early and late sensor fusion approaches, which improved the gait identification accuracy of the system to 93.36% and 97.06%, respectively.

Design and Implementation of Foot-Mounted Inertial Sensor Based Wearable Electronic Device for Game Play Application.

PubMed

Zhou, Qifan; Zhang, Hai; Lari, Zahra; Liu, Zhenbo; El-Sheimy, Naser

2016-10-21

Wearable electronic devices have experienced increasing development with the advances in the semiconductor industry and have received more attention during the last decades. This paper presents the development and implementation of a novel inertial sensor-based foot-mounted wearable electronic device for a brand new application: game playing. The main objective of the introduced system is to monitor and identify the human foot stepping direction in real time, and coordinate these motions to control the player operation in games. This proposed system extends the utilized field of currently available wearable devices and introduces a convenient and portable medium to perform exercise in a more compelling way in the near future. This paper provides an overview of the previously-developed system platforms, introduces the main idea behind this novel application, and describes the implemented human foot moving direction identification algorithm. Practical experiment results demonstrate that the proposed system is capable of recognizing five foot motions, jump, step left, step right, step forward, and step backward, and has achieved an over 97% accuracy performance for different users. The functionality of the system for real-time application has also been verified through the practical experiments.

Mastication Evaluation With Unsupervised Learning: Using an Inertial Sensor-Based System.

PubMed

Lucena, Caroline Vieira; Lacerda, Marcelo; Caldas, Rafael; De Lima Neto, Fernando Buarque; Rativa, Diego

2018-01-01

There is a direct relationship between the prevalence of musculoskeletal disorders of the temporomandibular joint and orofacial disorders. A well-elaborated analysis of the jaw movements provides relevant information for healthcare professionals to conclude their diagnosis. Different approaches have been explored to track jaw movements such that the mastication analysis is getting less subjective; however, all methods are still highly subjective, and the quality of the assessments depends much on the experience of the health professional. In this paper, an accurate and non-invasive method based on a commercial low-cost inertial sensor (MPU6050) to measure jaw movements is proposed. The jaw-movement feature values are compared to the obtained with clinical analysis, showing no statistically significant difference between both methods. Moreover, We propose to use unsupervised paradigm approaches to cluster mastication patterns of healthy subjects and simulated patients with facial trauma. Two techniques were used in this paper to instantiate the method: Kohonen's Self-Organizing Maps and K-Means Clustering. Both algorithms have excellent performances to process jaw-movements data, showing encouraging results and potential to bring a full assessment of the masticatory function. The proposed method can be applied in real-time providing relevant dynamic information for health-care professionals.

Design and Implementation of Foot-Mounted Inertial Sensor Based Wearable Electronic Device for Game Play Application

PubMed Central

Zhou, Qifan; Zhang, Hai; Lari, Zahra; Liu, Zhenbo; El-Sheimy, Naser

2016-01-01

Wearable electronic devices have experienced increasing development with the advances in the semiconductor industry and have received more attention during the last decades. This paper presents the development and implementation of a novel inertial sensor-based foot-mounted wearable electronic device for a brand new application: game playing. The main objective of the introduced system is to monitor and identify the human foot stepping direction in real time, and coordinate these motions to control the player operation in games. This proposed system extends the utilized field of currently available wearable devices and introduces a convenient and portable medium to perform exercise in a more compelling way in the near future. This paper provides an overview of the previously-developed system platforms, introduces the main idea behind this novel application, and describes the implemented human foot moving direction identification algorithm. Practical experiment results demonstrate that the proposed system is capable of recognizing five foot motions, jump, step left, step right, step forward, and step backward, and has achieved an over 97% accuracy performance for different users. The functionality of the system for real-time application has also been verified through the practical experiments. PMID:27775673

Real-Time Telemetry System for Monitoring Motion of Ships Based on Inertial Sensors

PubMed Central

Núñez, José M.; Araújo, Marta G.; García-Tuñón, I.

2017-01-01

A telemetry system for real-time monitoring of the motions, position, speed and course of a ship at sea is presented in this work. The system, conceived as a subsystem of a radar cross-section measurement unit, could also be used in other applications as ships dynamics characterization, on-board cranes, antenna stabilizers, etc. This system was designed to be stand-alone, reliable, easy to deploy, low-cost and free of requirements related to stabilization procedures. In order to achieve such a unique combination of functionalities, we have developed a telemetry system based on redundant inertial and magnetic sensors and GPS (Global Positioning System) measurements. It provides a proper data storage and also has real-time radio data transmission capabilities to an on-shore station. The output of the system can be used either for on-line or off-line processing. Additionally, the system uses dual technologies and COTS (Commercial Off-The-Shelf) components. Motion-positioning measurements and radio data link tests were successfully carried out in several ships of the Spanish Navy, proving the compliance with the design targets and validating our telemetry system. PMID:28441330

Performance Evaluation of State of the Art Systems for Physical Activity Classification of Older Subjects Using Inertial Sensors in a Real Life Scenario: A Benchmark Study

PubMed Central

Awais, Muhammad; Palmerini, Luca; Bourke, Alan K.; Ihlen, Espen A. F.; Helbostad, Jorunn L.; Chiari, Lorenzo

2016-01-01

The popularity of using wearable inertial sensors for physical activity classification has dramatically increased in the last decade due to their versatility, low form factor, and low power requirements. Consequently, various systems have been developed to automatically classify daily life activities. However, the scope and implementation of such systems is limited to laboratory-based investigations. Furthermore, these systems are not directly comparable, due to the large diversity in their design (e.g., number of sensors, placement of sensors, data collection environments, data processing techniques, features set, classifiers, cross-validation methods). Hence, the aim of this study is to propose a fair and unbiased benchmark for the field-based validation of three existing systems, highlighting the gap between laboratory and real-life conditions. For this purpose, three representative state-of-the-art systems are chosen and implemented to classify the physical activities of twenty older subjects (76.4 ± 5.6 years). The performance in classifying four basic activities of daily life (sitting, standing, walking, and lying) is analyzed in controlled and free living conditions. To observe the performance of laboratory-based systems in field-based conditions, we trained the activity classification systems using data recorded in a laboratory environment and tested them in real-life conditions in the field. The findings show that the performance of all systems trained with data in the laboratory setting highly deteriorates when tested in real-life conditions, thus highlighting the need to train and test the classification systems in the real-life setting. Moreover, we tested the sensitivity of chosen systems to window size (from 1 s to 10 s) suggesting that overall accuracy decreases with increasing window size. Finally, to evaluate the impact of the number of sensors on the performance, chosen systems are modified considering only the sensing unit worn at the lower back. The results, similarly to the multi-sensor setup, indicate substantial degradation of the performance when laboratory-trained systems are tested in the real-life setting. This degradation is higher than in the multi-sensor setup. Still, the performance provided by the single-sensor approach, when trained and tested with real data, can be acceptable (with an accuracy above 80%). PMID:27973434

Estimation of Center of Mass Trajectory using Wearable Sensors during Golf Swing

PubMed Central

Najafi, Bijan; Lee-Eng, Jacqueline; Wrobel, James S.; Goebel, Ruben

2015-01-01

This study suggests a wearable sensor technology to estimate center of mass (CoM) trajectory during a golf swing. Groups of 3, 4, and 18 participants were recruited, respectively, for the purpose of three validation studies. Study 1 examined the accuracy of the system to estimate a 3D body segment angle compared to a camera-based motion analyzer (Vicon®). Study 2 assessed the accuracy of three simplified CoM trajectory models. Finally, Study 3 assessed the accuracy of the proposed CoM model during multiple golf swings. A relatively high agreement was observed between wearable sensors and the reference (Vicon®) for angle measurement (r > 0.99, random error <1.2° (1.5%) for anterior-posterior; <0.9° (2%) for medial-lateral; and <3.6° (2.5%) for internal-external direction). The two-link model yielded a better agreement with the reference system compared to one-link model (r > 0.93 v. r = 0.52, respectively). On the same note, the proposed two-link model estimated CoM trajectory during golf swing with relatively good accuracy (r > 0.9, A-P random error <1cm (7.7%) and <2cm (10.4%) for M-L). The proposed system appears to accurately quantify the kinematics of CoM trajectory as a surrogate of dynamic postural control during an athlete’s movement and its portability, makes it feasible to fit the competitive environment without restricting surface type. Key points This study demonstrates that wearable technology based on inertial sensors are accurate to estimate center of mass trajectory in complex athletic task (e.g., golf swing) This study suggests that two-link model of human body provides optimum tradeoff between accuracy and minimum number of sensor module for estimation of center of mass trajectory in particular during fast movements. Wearable technologies based on inertial sensors are viable option for assessing dynamic postural control in complex task outside of gait laboratory and constraints of cameras, surface, and base of support. PMID:25983585

Differences in Trunk Accelerometry Between Frail and Nonfrail Elderly Persons in Sit-to-Stand and Stand-to-Sit Transitions Based on a Mobile Inertial Sensor.

PubMed

Galán-Mercant, Alejandro; Cuesta-Vargas, Antonio I

2013-08-16

Clinical frailty syndrome is a common geriatric syndrome, which is characterized by physiological reserve decreases and increased vulnerability. The changes associated to ageing and frailties are associated to changes in gait characteristics and the basic functional capacities. Traditional clinical evaluation of Sit-to-Stand (Si-St) and Stand-to-Sit (St-Si) transition is based on visual observation of joint angle motion to describe alterations in coordination and movement pattern. The latest generation smartphones often include inertial sensors with subunits such as accelerometers and gyroscopes, which can detect acceleration. Firstly, to describe the variability of the accelerations, angular velocity, and displacement of the trunk during the Sit-to-Stand and Stand-to-Sit transitions in two groups of frail and physically active elderly persons, through instrumentation with the iPhone 4 smartphone. Secondly, we want to analyze the differences between the two study groups. A cross-sectional study that involved 30 subjects over 65 years, 14 frail and 16 fit subjects. The participants were classified with frail syndrome by the Fried criteria. Linear acceleration was measured along three orthogonal axes using the iPhone 4 accelerometer. Each subject performed up to three successive Si-St and St-Si postural transitions using a standard chair with armrest. Significant differences were found between the two groups of frail and fit elderly persons in the accelerometry and angular displacement variables obtained in the kinematic readings of the trunk during both transitions. The inertial sensor fitted in the iPhone 4 is able to study and analyze the kinematics of the Si-St and St-Si transitions in frail and physically active elderly persons. The accelerometry values for the frail elderly are lower than for the physically active elderly, while variability in the readings for the frail elderly is also lower than for the control group.

Sensor-Aware Recognition and Tracking for Wide-Area Augmented Reality on Mobile Phones

PubMed Central

Chen, Jing; Cao, Ruochen; Wang, Yongtian

2015-01-01

Wide-area registration in outdoor environments on mobile phones is a challenging task in mobile augmented reality fields. We present a sensor-aware large-scale outdoor augmented reality system for recognition and tracking on mobile phones. GPS and gravity information is used to improve the VLAD performance for recognition. A kind of sensor-aware VLAD algorithm, which is self-adaptive to different scale scenes, is utilized to recognize complex scenes. Considering vision-based registration algorithms are too fragile and tend to drift, data coming from inertial sensors and vision are fused together by an extended Kalman filter (EKF) to achieve considerable improvements in tracking stability and robustness. Experimental results show that our method greatly enhances the recognition rate and eliminates the tracking jitters. PMID:26690439

Sensor-Aware Recognition and Tracking for Wide-Area Augmented Reality on Mobile Phones.

PubMed

Chen, Jing; Cao, Ruochen; Wang, Yongtian

2015-12-10

Wide-area registration in outdoor environments on mobile phones is a challenging task in mobile augmented reality fields. We present a sensor-aware large-scale outdoor augmented reality system for recognition and tracking on mobile phones. GPS and gravity information is used to improve the VLAD performance for recognition. A kind of sensor-aware VLAD algorithm, which is self-adaptive to different scale scenes, is utilized to recognize complex scenes. Considering vision-based registration algorithms are too fragile and tend to drift, data coming from inertial sensors and vision are fused together by an extended Kalman filter (EKF) to achieve considerable improvements in tracking stability and robustness. Experimental results show that our method greatly enhances the recognition rate and eliminates the tracking jitters.

Four methods of attitude determination for spin-stabilized spacecraft with applications and comparative results

NASA Technical Reports Server (NTRS)

Smith, G. A.

1975-01-01

The attitude of a spacecraft is determined by specifying independent parameters which relate the spacecraft axes to an inertial coordinate system. Sensors which measure angles between spin axis and other vectors directed to objects or fields external to the spacecraft are discussed. For the spin-stabilized spacecraft considered, the spin axis is constant over at least an orbit, but separate solutions based on sensor angle measurements are different due to propagation of errors. Sensor-angle solution methods are described which minimize the propagated errors by making use of least squares techniques over many sensor angle measurements and by solving explicitly (in closed form) for the spin axis coordinates. These methods are compared with star observation solutions to determine if satisfactory accuracy is obtained by each method.

A Newton-Euler Description for Sediment Movement.

NASA Astrophysics Data System (ADS)

Maniatis, G.; Hoey, T.; Drysdale, T.; Hodge, R. A.; Valyrakis, M.

2015-12-01

We present progress from the development of a purpose specific sensing system for sediment transport (Maniatis et al. 2013). This system utilises the capabilities of contemporary inertial micro-sensors (strap-down accelerometers and gyroscopes) to record fluvial transport from the moving body-frame of artificial pebbles modelled precisely to represent the motion of real, coarse sediment grains (D90=100 mm class). This type of measurements can be useful in the context of sediment transport only if the existing mathematical understanding of the process is updated. We test a new mathematical model which defines specifically how the data recorded in the body frame of the sensor (Lagrangian frame of reference) can be generalised to the reference frame of the flow (channel, Eulerian frame of reference). Given the association of the two most widely used models for sediment transport with those frames of reference (Shields' to Eulerian frame and HA. Einstein's to Lagrangian frame), this description builds the basis for the definition of explicit incipient motion criteria (Maniatis et al. 2015) and for the upscaling from point-grain scale measurements to averaged, cross-sectional, stream related metrics. Flume experiments where conducted in the Hydraulics laboratory of the University of Glasgow where a spherical sensor of 800 mm diameter and capable of recoding inertial dynamics at 80Hz frequency was tested under fluvial transport conditions. We managed to measure the dynamical response of the unit during pre-entrainment/entrainment transitions, on scaled and non-scaled to the sensor's diameter bed and for a range of hydrodynamic conditions (slope up to 0.02 and flow increase rate up to 0.05m3.s-1. Preliminary results from field deployment on a mixed bedrock-alluvial channel are also presented. Maniatis et. al 2013 J. Sens. Actuator Netw. 2013, 2(4), 761-779; Maniatis et. al 2015: "CALCULATION OF EXPLICIT PROBABILITY OF ENTRAINMENT BASED ON INERTIAL ACCELERATION MEASUREMENTS" J. Hydraulic Engineering, Under review.

Hierarchical information fusion for global displacement estimation in microsensor motion capture.

PubMed

Meng, Xiaoli; Zhang, Zhi-Qiang; Wu, Jian-Kang; Wong, Wai-Choong

2013-07-01

This paper presents a novel hierarchical information fusion algorithm to obtain human global displacement for different gait patterns, including walking, running, and hopping based on seven body-worn inertial and magnetic measurement units. In the first-level sensor fusion, the orientation for each segment is achieved by a complementary Kalman filter (CKF) which compensates for the orientation error of the inertial navigation system solution through its error state vector. For each foot segment, the displacement is also estimated by the CKF, and zero velocity update is included for the drift reduction in foot displacement estimation. Based on the segment orientations and left/right foot locations, two global displacement estimates can be acquired from left/right lower limb separately using a linked biomechanical model. In the second-level geometric fusion, another Kalman filter is deployed to compensate for the difference between the two estimates from the sensor fusion and get more accurate overall global displacement estimation. The updated global displacement will be transmitted to left/right foot based on the human lower biomechanical model to restrict the drifts in both feet displacements. The experimental results have shown that our proposed method can accurately estimate human locomotion for the three different gait patterns with regard to the optical motion tracker.

A Fault Tolerant System for an Integrated Avionics Sensor Configuration

NASA Technical Reports Server (NTRS)

Caglayan, A. K.; Lancraft, R. E.

1984-01-01

An aircraft sensor fault tolerant system methodology for the Transport Systems Research Vehicle in a Microwave Landing System (MLS) environment is described. The fault tolerant system provides reliable estimates in the presence of possible failures both in ground-based navigation aids, and in on-board flight control and inertial sensors. Sensor failures are identified by utilizing the analytic relationships between the various sensors arising from the aircraft point mass equations of motion. The estimation and failure detection performance of the software implementation (called FINDS) of the developed system was analyzed on a nonlinear digital simulation of the research aircraft. Simulation results showing the detection performance of FINDS, using a dual redundant sensor compliment, are presented for bias, hardover, null, ramp, increased noise and scale factor failures. In general, the results show that FINDS can distinguish between normal operating sensor errors and failures while providing an excellent detection speed for bias failures in the MLS, indicated airspeed, attitude and radar altimeter sensors.

Attitude determination for high-accuracy submicroradian jitter pointing on space-based platforms

NASA Astrophysics Data System (ADS)

Gupta, Avanindra A.; van Houten, Charles N.; Germann, Lawrence M.

1990-10-01

A description of the requirement definition process is given for a new wideband attitude determination subsystem (ADS) for image motion compensation (IMC) systems. The subsystem consists of either lateral accelerometers functioning in differential pairs or gas-bearing gyros for high-frequency sensors using CCD-based star trackers for low-frequency sensors. To minimize error the sensor signals are combined so that the mixing filter does not allow phase distortion. The two ADS models are introduced in an IMC simulation to predict measurement error, correction capability, and residual image jitter for a variety of system parameters. The IMC three-axis testbed is utilized to simulate an incoming beam in inertial space. Results demonstrate that both mechanical and electronic IMC meet the requirements of image stabilization for space-based observation at submicroradian-jitter levels. Currently available technology may be employed to implement IMC systems.

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter

PubMed Central

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Gu, Chengfan

2018-01-01

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation. PMID:29415509

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

PubMed

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

2018-02-06

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

Low-power sensor module for long-term activity monitoring.

PubMed

Leuenberger, Kaspar; Gassert, Roger

2011-01-01

Wearable sensor modules are a promising approach to collecting data on functional motor activities, both for repeated and long-term assessments, as well as to investigate the transfer of therapy to activities of daily living at home, but have so far either had limited sensing capabilities, or were not laid out for long-term monitoring. This paper presents ReSense, a miniature sensor unit optimized for long-term monitoring of functional activity. Inertial MEMS sensors capture accelerations along six degrees of freedom and a barometric pressure sensor serves as a precise altimeter. Data is written to an integrated memory card. The realized module measures Ø25 × 10 mm, weighs 10 g and can record continuously for 27 h at 25 Hz and over 22 h at 100 Hz. The integrated power-management system detects inactivity and extends the operating time by about a factor of two, as shown by initial 24 h recordings on five energetic healthy adults. The integrated barometric pressure sensor allowed to identify activities incorporating a change in altitude, such as going up/down stairs or riding an elevator. By taking into account data from the inertial sensors during the altitude changes, it becomes possible to distinguish between these two activities.

Fluvial experiments using inertial sensors.

NASA Astrophysics Data System (ADS)

Maniatis, Georgios; Valyrakis, Manousos; Hodge, Rebecca; Drysdale, Tim; Hoey, Trevor

2017-04-01

During the last four years we have announced results on the development of a smart pebble that is constructed and calibrated specifically for capturing the dynamics of coarse sediment motion in river beds, at a grain scale. In this presentation we report details of our experimental validation across a range of flow regimes. The smart pebble contains Inertial Measurements Units (IMUs), which are sensors capable of recording the inertial acceleration and the angular velocity of the rigid bodies into which they are attached. IMUs are available across a range of performance levels, with commensurate increase in size, cost and performance as one progresses from integrated-circuit devices for use in commercial applications such as gaming and mobile phones, to larger brick-sized systems sometimes found in industrial applications such as vibration monitoring and quality control, or even the rack-mount equipment used in some aerospace and navigation applications (which can go as far as to include lasers and optical components). In parallel with developments in commercial and industrial settings, geomorphologists started recently to explore means of deploying IMUs in smart pebbles. The less-expensive, chip-scale IMUs have been shown to have adequate performance for this application, as well as offering a sufficiently compact form-factor. Four prototype sensors have been developed so far, and the latest (400 g acceleration range, 50-200 Hz sampling frequency) has been tested in fluvial laboratory experiments. We present results from three different experimental regimes designed for the evaluation of this sensor: a) an entrainment threshold experiment ; b) a bed impact experiment ; and c) a rolling experiment. All experiments used a 100 mm spherical sensor, and set a) were repeated using an equivalent size elliptical sensor. The experiments were conducted in the fluvial laboratory of the University of Glasgow (0.9 m wide flume) under different hydraulic conditions. The use of IMU results into direct parametrization of the inertial forces of grains which for the tested grain sizes were, as expected, always comparable to the independently measured hydrodynamic forces. However, the validity of IMU measurements is subjected to specific design, processing and experimental considerations, and we present the results of our analysis of these.

Description of a dual fail operational redundant strapdown inertial measurement unit for integrated avionics systems research

NASA Technical Reports Server (NTRS)

Bryant, W. H.; Morrell, F. R.

1981-01-01

An experimental redundant strapdown inertial measurement unit (RSDIMU) is developed as a link to satisfy safety and reliability considerations in the integrated avionics concept. The unit includes four two degree-of-freedom tuned rotor gyros, and four accelerometers in a skewed and separable semioctahedral array. These sensors are coupled to four microprocessors which compensate sensor errors. These microprocessors are interfaced with two flight computers which process failure detection, isolation, redundancy management, and general flight control/navigation algorithms. Since the RSDIMU is a developmental unit, it is imperative that the flight computers provide special visibility and facility in algorithm modification.

Estimation of Full-Body Poses Using Only Five Inertial Sensors: An Eager or Lazy Learning Approach?

PubMed Central

Wouda, Frank J.; Giuberti, Matteo; Bellusci, Giovanni; Veltink, Peter H.

2016-01-01

Human movement analysis has become easier with the wide availability of motion capture systems. Inertial sensing has made it possible to capture human motion without external infrastructure, therefore allowing measurements in any environment. As high-quality motion capture data is available in large quantities, this creates possibilities to further simplify hardware setups, by use of data-driven methods to decrease the number of body-worn sensors. In this work, we contribute to this field by analyzing the capabilities of using either artificial neural networks (eager learning) or nearest neighbor search (lazy learning) for such a problem. Sparse orientation features, resulting from sensor fusion of only five inertial measurement units with magnetometers, are mapped to full-body poses. Both eager and lazy learning algorithms are shown to be capable of constructing this mapping. The full-body output poses are visually plausible with an average joint position error of approximately 7 cm, and average joint angle error of 7∘. Additionally, the effects of magnetic disturbances typical in orientation tracking on the estimation of full-body poses was also investigated, where nearest neighbor search showed better performance for such disturbances. PMID:27983676

Estimation of Full-Body Poses Using Only Five Inertial Sensors: An Eager or Lazy Learning Approach?

PubMed

Wouda, Frank J; Giuberti, Matteo; Bellusci, Giovanni; Veltink, Peter H

2016-12-15

Human movement analysis has become easier with the wide availability of motion capture systems. Inertial sensing has made it possible to capture human motion without external infrastructure, therefore allowing measurements in any environment. As high-quality motion capture data is available in large quantities, this creates possibilities to further simplify hardware setups, by use of data-driven methods to decrease the number of body-worn sensors. In this work, we contribute to this field by analyzing the capabilities of using either artificial neural networks (eager learning) or nearest neighbor search (lazy learning) for such a problem. Sparse orientation features, resulting from sensor fusion of only five inertial measurement units with magnetometers, are mapped to full-body poses. Both eager and lazy learning algorithms are shown to be capable of constructing this mapping. The full-body output poses are visually plausible with an average joint position error of approximately 7 cm, and average joint angle error of 7 ∘ . Additionally, the effects of magnetic disturbances typical in orientation tracking on the estimation of full-body poses was also investigated, where nearest neighbor search showed better performance for such disturbances.

Loose Coupling of Wearable-Based INSs with Automatic Heading Evaluation

PubMed Central

Munoz Diaz, Estefania

2017-01-01

Position tracking of pedestrians by means of inertial sensors is a highly explored field of research. In fact, there are already many approaches to implement inertial navigation systems (INSs). However, most of them use a single inertial measurement unit (IMU) attached to the pedestrian’s body. Since wearable-devices will be given items in the future, this work explores the implementation of an INS using two wearable-based IMUs. A loosely coupled approach is proposed to combine the outputs of wearable-based INSs. The latter are based on a pocket-mounted IMU and a foot-mounted IMU. The loosely coupled fusion combines the output of the two INSs not only when these outputs are least erroneous, but also automatically favoring the best output. This approach is named smart update. The main challenge is determining the quality of the heading estimation of each INS, which changes every time. In order to address this, a novel concept to determine the quality of the heading estimation is presented. This concept is subject to a patent application. The results show that the position error rate of the loosely coupled fusion is 10 cm/s better than either the foot INS’s or pocket INS’s error rate in 95% of the cases. PMID:29099807

Modelling of rotation-induced frequency shifts in whispering gallery modes

NASA Astrophysics Data System (ADS)

Venediktov, V. Yu; Kukaev, A. S.; Filatov, Yu V.; Shalymov, E. V.

2018-02-01

We study the angular velocity sensors based on whispering gallery mode resonators. Rotation of such resonators gives rise to various effects that can cause a spectral shift of their modes. Optical methods allow this shift to be determined with high precision, which can be used practically to measure the angular velocity in inertial orientation and navigation systems. The basic principles of constructing the angular velocity sensors utilising these effects are considered, their advantages and drawbacks are indicated. We also study the interrelation between the effects and the possibility of their mutual influence on each other. Based on the analytical studies of the effects, we consider the possibility of their combined application for angular velocity measurements.

The Performance of a Tight Ins/gnss/photogrammetric Integration Scheme for Land Based MMS Applications in Gnss Denied Environments

NASA Astrophysics Data System (ADS)

Chu, Chien-Hsun; Chiang, Kai-Wei

2016-06-01

The early development of mobile mapping system (MMS) was restricted to applications that permitted the determination of the elements of exterior orientation from existing ground control. Mobile mapping refers to a means of collecting geospatial data using mapping sensors that are mounted on a mobile platform. Research works concerning mobile mapping dates back to the late 1980s. This process is mainly driven by the need for highway infrastructure mapping and transportation corridor inventories. In the early nineties, advances in satellite and inertial technology made it possible to think about mobile mapping in a different way. Instead of using ground control points as references for orienting the images in space, the trajectory and attitude of the imager platform could now be determined directly. Cameras, along with navigation and positioning sensors are integrated and mounted on a land vehicle for mapping purposes. Objects of interest can be directly measured and mapped from images that have been georeferenced using navigation and positioning sensors. Direct georeferencing (DG) is the determination of time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using the Global Navigation Satellite System (GNSS) and inertial navigation using an Inertial Measuring Unit (IMU). Although either technology used along could in principle determine both position and orientation, they are usually integrated in such a way that the IMU is the main orientation sensor, while the GNSS receiver is the main position sensor. However, GNSS signals are obstructed due to limited number of visible satellites in GNSS denied environments such as urban canyon, foliage, tunnel and indoor that cause the GNSS gap or interfered by reflected signals that cause abnormal measurement residuals thus deteriorates the positioning accuracy in GNSS denied environments. This study aims at developing a novel method that uses ground control points to maintain the positioning accuracy of the MMS in GNSS denied environments. At last, this study analyses the performance of proposed method using about 20 check-points through DG process.

Validation of distal limb mounted inertial measurement unit sensors for stride detection in Warmblood horses at walk and trot.

PubMed

Bragança, F M; Bosch, S; Voskamp, J P; Marin-Perianu, M; Van der Zwaag, B J; Vernooij, J C M; van Weeren, P R; Back, W

2017-07-01

Inertial measurement unit (IMU) sensor-based techniques are becoming more popular in horses as a tool for objective locomotor assessment. To describe, evaluate and validate a method of stride detection and quantification at walk and trot using distal limb mounted IMU sensors. Prospective validation study comparing IMU sensors and motion capture with force plate data. A total of seven Warmblood horses equipped with metacarpal/metatarsal IMU sensors and reflective markers for motion capture were hand walked and trotted over a force plate. Using four custom built algorithms hoof-on/hoof-off timing over the force plate were calculated for each trial from the IMU data. Accuracy of the computed parameters was calculated as the mean difference in milliseconds between the IMU or motion capture generated data and the data from the force plate, precision as the s.d. of these differences and percentage of error with accuracy of the calculated parameter as a percentage of the force plate stance duration. Accuracy, precision and percentage of error of the best performing IMU algorithm for stance duration at walk were 28.5, 31.6 ms and 3.7% for the forelimbs and -5.5, 20.1 ms and -0.8% for the hindlimbs, respectively. At trot the best performing algorithm achieved accuracy, precision and percentage of error of -27.6/8.8 ms/-8.4% for the forelimbs and 6.3/33.5 ms/9.1% for the hindlimbs. The described algorithms have not been assessed on different surfaces. Inertial measurement unit technology can be used to determine temporal kinematic stride variables at walk and trot justifying its use in gait and performance analysis. However, precision of the method may not be sufficient to detect all possible lameness-related changes. These data seem promising enough to warrant further research to evaluate whether this approach will be useful for appraising the majority of clinically relevant gait changes encountered in practice. © 2016 The Authors. Equine Veterinary Journal published by John Wiley & Sons Ltd on behalf of EVJ Ltd.

Influence of the model's degree of freedom on human body dynamics identification.

PubMed

Maita, Daichi; Venture, Gentiane

2013-01-01

In fields of sports and rehabilitation, opportunities of using motion analysis of the human body have dramatically increased. To analyze the motion dynamics, a number of subject specific parameters and measurements are required. For example the contact forces measurement and the inertial parameters of each segment of the human body are necessary to compute the joint torques. In this study, in order to perform accurate dynamic analysis we propose to identify the inertial parameters of the human body and to evaluate the influence of the model's number of degrees of freedom (DoF) on the results. We use a method to estimate the inertial parameters without torque sensor, using generalized coordinates of the base link, joint angles and external forces information. We consider a 34DoF model, a 58DoF model, as well as the case when the human is manipulating a tool (here a tennis racket). We compare the obtained in results in terms of contact force estimation.

Reliability analysis and fault-tolerant system development for a redundant strapdown inertial measurement unit. [inertial platforms

NASA Technical Reports Server (NTRS)

Motyka, P.

1983-01-01

A methodology is developed and applied for quantitatively analyzing the reliability of a dual, fail-operational redundant strapdown inertial measurement unit (RSDIMU). A Markov evaluation model is defined in terms of the operational states of the RSDIMU to predict system reliability. A 27 state model is defined based upon a candidate redundancy management system which can detect and isolate a spectrum of failure magnitudes. The results of parametric studies are presented which show the effect on reliability of the gyro failure rate, both the gyro and accelerometer failure rates together, false alarms, probability of failure detection, probability of failure isolation, and probability of damage effects and mission time. A technique is developed and evaluated for generating dynamic thresholds for detecting and isolating failures of the dual, separated IMU. Special emphasis is given to the detection of multiple, nonconcurrent failures. Digital simulation time histories are presented which show the thresholds obtained and their effectiveness in detecting and isolating sensor failures.

Image-Aided Navigation Using Cooperative Binocular Stereopsis

DTIC Science & Technology

2014-03-27

Global Postioning System . . . . . . . . . . . . . . . . . . . . . . . . . 1 IMU Inertial Measurement Unit...an intertial measurement unit ( IMU ). This technique capitalizes on an IMU’s ability to capture quick motion and the ability of GPS to constrain long...the sensor-aided IMU framework. Visual sensors provide a number of benefits, such as low cost and weight. These sensors are also able to measure

Pedestrian dead reckoning employing simultaneous activity recognition cues

NASA Astrophysics Data System (ADS)

Altun, Kerem; Barshan, Billur

2012-02-01

We consider the human localization problem using body-worn inertial/magnetic sensor units. Inertial sensors are characterized by a drift error caused by the integration of their rate output to obtain position information. Because of this drift, the position and orientation data obtained from inertial sensors are reliable over only short periods of time. Therefore, position updates from externally referenced sensors are essential. However, if the map of the environment is known, the activity context of the user can provide information about his position. In particular, the switches in the activity context correspond to discrete locations on the map. By performing localization simultaneously with activity recognition, we detect the activity context switches and use the corresponding position information as position updates in a localization filter. The localization filter also involves a smoother that combines the two estimates obtained by running the zero-velocity update algorithm both forward and backward in time. We performed experiments with eight subjects in indoor and outdoor environments involving walking, turning and standing activities. Using a spatial error criterion, we show that the position errors can be decreased by about 85% on the average. We also present the results of two 3D experiments performed in realistic indoor environments and demonstrate that it is possible to achieve over 90% error reduction in position by performing localization simultaneously with activity recognition.

Development and validity of methods for the estimation of temporal gait parameters from heel-attached inertial sensors in younger and older adults.

PubMed

Misu, Shogo; Asai, Tsuyoshi; Ono, Rei; Sawa, Ryuichi; Tsutsumimoto, Kota; Ando, Hiroshi; Doi, Takehiko

2017-09-01

The heel is likely a suitable location to which inertial sensors are attached for the detection of gait events. However, there are few studies to detect gait events and determine temporal gait parameters using sensors attached to the heels. We developed two methods to determine temporal gait parameters: detecting heel-contact using acceleration and detecting toe-off using angular velocity data (acceleration-angular velocity method; A-V method), and detecting both heel-contact and toe-off using angular velocity data (angular velocity-angular velocity method; V-V method). The aim of this study was to examine the concurrent validity of the A-V and V-V methods against the standard method, and to compare their accuracy. Temporal gait parameters were measured in 10 younger and 10 older adults. The intra-class correlation coefficients were excellent in both methods compared with the standard method (0.80 to 1.00). The root mean square errors of stance and swing time in the A-V method were smaller than the V-V method in older adults, although there were no significant discrepancies in the other comparisons. Our study suggests that inertial sensors attached to the heels, using the A-V method in particular, provide a valid measurement of temporal gait parameters. Copyright © 2017 Elsevier B.V. All rights reserved.

Strapdown system redundancy management flight demonstration. [vertical takeoff and landing aircraft

NASA Technical Reports Server (NTRS)

1978-01-01

The suitability of strapdown inertial systems in providing highly reliable short-term navigation for vertical take-off and landing (VTOL) aircraft operating in an intra-urban setting under all-weather conditions was assessed. A preliminary design configuration of a skewed sensor inertial reference system employing a redundancy management concept to achieve fail-operational, fail-operational performance, was developed.

Fourier-based integration of quasi-periodic gait accelerations for drift-free displacement estimation using inertial sensors.

PubMed

Sabatini, Angelo Maria; Ligorio, Gabriele; Mannini, Andrea

2015-11-23

In biomechanical studies Optical Motion Capture Systems (OMCS) are considered the gold standard for determining the orientation and the position (pose) of an object in a global reference frame. However, the use of OMCS can be difficult, which has prompted research on alternative sensing technologies, such as body-worn inertial sensors. We developed a drift-free method to estimate the three-dimensional (3D) displacement of a body part during cyclical motions using body-worn inertial sensors. We performed the Fourier analysis of the stride-by-stride estimates of the linear acceleration, which were obtained by transposing the specific forces measured by the tri-axial accelerometer into the global frame using a quaternion-based orientation estimation algorithm and detecting when each stride began using a gait-segmentation algorithm. The time integration was performed analytically using the Fourier series coefficients; the inverse Fourier series was then taken for reconstructing the displacement over each single stride. The displacement traces were concatenated and spline-interpolated to obtain the entire trace. The method was applied to estimate the motion of the lower trunk of healthy subjects that walked on a treadmill and it was validated using OMCS reference 3D displacement data; different approaches were tested for transposing the measured specific force into the global frame, segmenting the gait and performing time integration (numerically and analytically). The width of the limits of agreements were computed between each tested method and the OMCS reference method for each anatomical direction: Medio-Lateral (ML), VerTical (VT) and Antero-Posterior (AP); using the proposed method, it was observed that the vertical component of displacement (VT) was within ±4 mm (±1.96 standard deviation) of OMCS data and each component of horizontal displacement (ML and AP) was within ±9 mm of OMCS data. Fourier harmonic analysis was applied to model stride-by-stride linear accelerations during walking and to perform their analytical integration. Our results showed that analytical integration based on Fourier series coefficients was a useful approach to accurately estimate 3D displacement from noisy acceleration data.

Estimating orientation using magnetic and inertial sensors and different sensor fusion approaches: accuracy assessment in manual and locomotion tasks.

PubMed

Bergamini, Elena; Ligorio, Gabriele; Summa, Aurora; Vannozzi, Giuseppe; Cappozzo, Aurelio; Sabatini, Angelo Maria

2014-10-09

Magnetic and inertial measurement units are an emerging technology to obtain 3D orientation of body segments in human movement analysis. In this respect, sensor fusion is used to limit the drift errors resulting from the gyroscope data integration by exploiting accelerometer and magnetic aiding sensors. The present study aims at investigating the effectiveness of sensor fusion methods under different experimental conditions. Manual and locomotion tasks, differing in time duration, measurement volume, presence/absence of static phases, and out-of-plane movements, were performed by six subjects, and recorded by one unit located on the forearm or the lower trunk, respectively. Two sensor fusion methods, representative of the stochastic (Extended Kalman Filter) and complementary (Non-linear observer) filtering, were selected, and their accuracy was assessed in terms of attitude (pitch and roll angles) and heading (yaw angle) errors using stereophotogrammetric data as a reference. The sensor fusion approaches provided significantly more accurate results than gyroscope data integration. Accuracy improved mostly for heading and when the movement exhibited stationary phases, evenly distributed 3D rotations, it occurred in a small volume, and its duration was greater than approximately 20 s. These results were independent from the specific sensor fusion method used. Practice guidelines for improving the outcome accuracy are provided.

Real and virtual explorations of the environment and interactive tracking of movable objects for the blind on the basis of tactile-acoustical maps and 3D environment models.

PubMed

Hub, Andreas; Hartter, Tim; Kombrink, Stefan; Ertl, Thomas

2008-01-01

PURPOSE.: This study describes the development of a multi-functional assistant system for the blind which combines localisation, real and virtual navigation within modelled environments and the identification and tracking of fixed and movable objects. The approximate position of buildings is determined with a global positioning sensor (GPS), then the user establishes exact position at a specific landmark, like a door. This location initialises indoor navigation, based on an inertial sensor, a step recognition algorithm and map. Tracking of movable objects is provided by another inertial sensor and a head-mounted stereo camera, combined with 3D environmental models. This study developed an algorithm based on shape and colour to identify objects and used a common face detection algorithm to inform the user of the presence and position of others. The system allows blind people to determine their position with approximately 1 metre accuracy. Virtual exploration of the environment can be accomplished by moving one's finger on a touch screen of a small portable tablet PC. The name of rooms, building features and hazards, modelled objects and their positions are presented acoustically or in Braille. Given adequate environmental models, this system offers blind people the opportunity to navigate independently and safely, even within unknown environments. Additionally, the system facilitates education and rehabilitation by providing, in several languages, object names, features and relative positions.

Physical Human Activity Recognition Using Wearable Sensors

PubMed Central

Attal, Ferhat; Mohammed, Samer; Dedabrishvili, Mariam; Chamroukhi, Faicel; Oukhellou, Latifa; Amirat, Yacine

2015-01-01

This paper presents a review of different classification techniques used to recognize human activities from wearable inertial sensor data. Three inertial sensor units were used in this study and were worn by healthy subjects at key points of upper/lower body limbs (chest, right thigh and left ankle). Three main steps describe the activity recognition process: sensors’ placement, data pre-processing and data classification. Four supervised classification techniques namely, k-Nearest Neighbor (k-NN), Support Vector Machines (SVM), Gaussian Mixture Models (GMM), and Random Forest (RF) as well as three unsupervised classification techniques namely, k-Means, Gaussian mixture models (GMM) and Hidden Markov Model (HMM), are compared in terms of correct classification rate, F-measure, recall, precision, and specificity. Raw data and extracted features are used separately as inputs of each classifier. The feature selection is performed using a wrapper approach based on the RF algorithm. Based on our experiments, the results obtained show that the k-NN classifier provides the best performance compared to other supervised classification algorithms, whereas the HMM classifier is the one that gives the best results among unsupervised classification algorithms. This comparison highlights which approach gives better performance in both supervised and unsupervised contexts. It should be noted that the obtained results are limited to the context of this study, which concerns the classification of the main daily living human activities using three wearable accelerometers placed at the chest, right shank and left ankle of the subject. PMID:26690450

GPS-aided inertial technology and navigation-based photogrammetry for aerial mapping the San Andreas fault system

USGS Publications Warehouse

Sanchez, Richard D.; Hudnut, Kenneth W.

2004-01-01

Aerial mapping of the San Andreas Fault System can be realized more efficiently and rapidly without ground control and conventional aerotriangulation. This is achieved by the direct geopositioning of the exterior orientation of a digital imaging sensor by use of an integrated Global Positioning System (GPS) receiver and an Inertial Navigation System (INS). A crucial issue to this particular type of aerial mapping is the accuracy, scale, consistency, and speed achievable by such a system. To address these questions, an Applanix Digital Sensor System (DSS) was used to examine its potential for near real-time mapping. Large segments of vegetation along the San Andreas and Cucamonga faults near the foothills of the San Bernardino and San Gabriel Mountains were burned to the ground in the California wildfires of October-November 2003. A 175 km corridor through what once was a thickly vegetated and hidden fault surface was chosen for this study. Both faults pose a major hazard to the greater Los Angeles metropolitan area and a near real-time mapping system could provide information vital to a post-disaster response.

Angular rate optimal design for the rotary strapdown inertial navigation system.

PubMed

Yu, Fei; Sun, Qian

2014-04-22

Due to the characteristics of high precision for a long duration, the rotary strapdown inertial navigation system (RSINS) has been widely used in submarines and surface ships. Nowadays, the core technology, the rotating scheme, has been studied by numerous researchers. It is well known that as one of the key technologies, the rotating angular rate seriously influences the effectiveness of the error modulating. In order to design the optimal rotating angular rate of the RSINS, the relationship between the rotating angular rate and the velocity error of the RSINS was analyzed in detail based on the Laplace transform and the inverse Laplace transform in this paper. The analysis results showed that the velocity error of the RSINS depends on not only the sensor error, but also the rotating angular rate. In order to minimize the velocity error, the rotating angular rate of the RSINS should match the sensor error. One optimal design method for the rotating rate of the RSINS was also proposed in this paper. Simulation and experimental results verified the validity and superiority of this optimal design method for the rotating rate of the RSINS.

A low-cost inertial smoothing system for landing approach guidance

NASA Technical Reports Server (NTRS)

Niessen, F. R.

1973-01-01

Accurate position and velocity information with low noise content for instrument approaches and landings is required for both control and display applications. In a current VTOL automatic instrument approach and landing research program, radar-derived landing guidance position reference signals, which are noisy, have been mixed with acceleration information derived from low-cost onboard sensors to provide high-quality position and velocity information. An in-flight comparison of signal quality and accuracy has shown good agreement between the low-cost inertial smoothing system and an aided inertial navigation system. Furthermore, the low-cost inertial smoothing system has been proven to be satisfactory in control and display system applications for both automatic and pilot-in-the-loop instrument approaches and landings.

Pose Estimation of a Mobile Robot Based on Fusion of IMU Data and Vision Data Using an Extended Kalman Filter.

PubMed

Alatise, Mary B; Hancke, Gerhard P

2017-09-21

Using a single sensor to determine the pose estimation of a device cannot give accurate results. This paper presents a fusion of an inertial sensor of six degrees of freedom (6-DoF) which comprises the 3-axis of an accelerometer and the 3-axis of a gyroscope, and a vision to determine a low-cost and accurate position for an autonomous mobile robot. For vision, a monocular vision-based object detection algorithm speeded-up robust feature (SURF) and random sample consensus (RANSAC) algorithms were integrated and used to recognize a sample object in several images taken. As against the conventional method that depend on point-tracking, RANSAC uses an iterative method to estimate the parameters of a mathematical model from a set of captured data which contains outliers. With SURF and RANSAC, improved accuracy is certain; this is because of their ability to find interest points (features) under different viewing conditions using a Hessain matrix. This approach is proposed because of its simple implementation, low cost, and improved accuracy. With an extended Kalman filter (EKF), data from inertial sensors and a camera were fused to estimate the position and orientation of the mobile robot. All these sensors were mounted on the mobile robot to obtain an accurate localization. An indoor experiment was carried out to validate and evaluate the performance. Experimental results show that the proposed method is fast in computation, reliable and robust, and can be considered for practical applications. The performance of the experiments was verified by the ground truth data and root mean square errors (RMSEs).

Pose Estimation of a Mobile Robot Based on Fusion of IMU Data and Vision Data Using an Extended Kalman Filter

PubMed Central

Hancke, Gerhard P.

2017-01-01

Using a single sensor to determine the pose estimation of a device cannot give accurate results. This paper presents a fusion of an inertial sensor of six degrees of freedom (6-DoF) which comprises the 3-axis of an accelerometer and the 3-axis of a gyroscope, and a vision to determine a low-cost and accurate position for an autonomous mobile robot. For vision, a monocular vision-based object detection algorithm speeded-up robust feature (SURF) and random sample consensus (RANSAC) algorithms were integrated and used to recognize a sample object in several images taken. As against the conventional method that depend on point-tracking, RANSAC uses an iterative method to estimate the parameters of a mathematical model from a set of captured data which contains outliers. With SURF and RANSAC, improved accuracy is certain; this is because of their ability to find interest points (features) under different viewing conditions using a Hessain matrix. This approach is proposed because of its simple implementation, low cost, and improved accuracy. With an extended Kalman filter (EKF), data from inertial sensors and a camera were fused to estimate the position and orientation of the mobile robot. All these sensors were mounted on the mobile robot to obtain an accurate localization. An indoor experiment was carried out to validate and evaluate the performance. Experimental results show that the proposed method is fast in computation, reliable and robust, and can be considered for practical applications. The performance of the experiments was verified by the ground truth data and root mean square errors (RMSEs). PMID:28934102

An Eulerian-Lagrangian description for fluvial coarse sediment transport: theory and verification with low-cost inertial sensors.

NASA Astrophysics Data System (ADS)

Maniatis, Georgios

2017-04-01

Fluvial sediment transport is controlled by hydraulics, sediment properties and arrangement, and flow history across a range of time scales. One reference frame descriptions (Eulerian or Lagrangian) yield useful results but restrict the theoretical understanding of the process as differences between the two phases (liquid and solid) are not explicitly accounted. Recently, affordable Inertial Measurement Units (IMUs) that can be embedded in coarse (100 mm diameter scale) natural or artificial particles became available. These sensors are subjected to technical limitations when deployed for natural sediment transport. However, they give us the ability to measure for the first time the inertial dynamics (acceleration and angular velocity) of moving sediment grains under fluvial transport. Theoretically, the assumption of an ideal (IMU), rigidly attached at the centre of the mass of a sediment particle can simplify greatly the derivation of a general Eulerian-Lagrangian (E-L) model. This approach accounts for inertial characteristics of particles in a Lagrangian (particle fixed) frame, and for the hydrodynamics in an independent Eulerian frame. Simplified versions of the E-L model have been evaluated in laboratory experiments using real-IMUs [Maniatis et. al 2015]. Here, experimental results are presented relevant to the evaluation of the complete E-L model. Artificial particles were deployed in a series of laboratory and field experiments. The particles are equipped with an IMU capable of recording acceleration at ± 400 g and angular velocities at ± 1200 rads/sec ranges. The sampling frequency ranges from 50 to 200 Hz for the total IMU measurement. Two sets of laboratory experiments were conducted in a 0.9m wide laboratory flume. The first is a set of entrainment threshold experiments using two artificial particles: a spherical of D=90mm (A) and an ellipsoid with axes of 100, 70 and 30 mm (B). For the second set of experiments, a spherical artificial enclosure of D=75 mm (C) was released to roll freely in a (> threshold for entrainment) flow and over surfaces of different roughness. Finally, the coarser spherical and elliptical sensor- assemblies (A and B) were deployed in a steep mountain stream during active sediment transport flow conditions. The results include the calculation of the inertial acceleration, the instantaneous particle velocity and the total kinetic energy of the mobile particle (including the rotational component using gyroscope measurements). The comparison of the field deployments with the laboratory experiments suggests that E-L model can be generalised from laboratory to natural conditions. Overall, the inertia of individual coarse particles is a statistically significant effect for all the modes of sediment transport (entrainment, translation, deposition) in both natural and laboratory regimes. Maniatis et. al 2015: "Calculating the Explicit Probability of Entrainment Based on Inertial Acceleration Measurements", J. Hydraulic Engineering, 04016097

Precision Landing and Hazard Avoidance Doman

NASA Technical Reports Server (NTRS)

Robertson, Edward A.; Carson, John M., III

2016-01-01

The Precision Landing and Hazard Avoidance (PL&HA) domain addresses the development, integration, testing, and spaceflight infusion of sensing, processing, and GN&C functions critical to the success and safety of future human and robotic exploration missions. PL&HA sensors also have applications to other mission events, such as rendezvous and docking. Autonomous PL&HA builds upon the core GN&C capabilities developed to enable soft, controlled landings on the Moon, Mars, and other solar system bodies. Through the addition of a Terrain Relative Navigation (TRN) function, precision landing within tens of meters of a map-based target is possible. The addition of a 3-D terrain mapping lidar sensor improves the probability of a safe landing via autonomous, real-time Hazard Detection and Avoidance (HDA). PL&HA significantly improves the probability of mission success and enhances access to sites of scientific interest located in challenging terrain. PL&HA can also utilize external navigation aids, such as navigation satellites and surface beacons. Advanced Lidar Sensors High precision ranging, velocimetry, and 3-D terrain mapping Terrain Relative Navigation (TRN) TRN compares onboard reconnaissance data with real-time terrain imaging data to update the S/C position estimate Hazard Detection and Avoidance (HDA) Generates a high-resolution, 3-D terrain map in real-time during the approach trajectory to identify safe landing targets Inertial Navigation During Terminal Descent High precision surface relative sensors enable accurate inertial navigation during terminal descent and a tightly controlled touchdown within meters of the selected safe landing target.

Sprint mechanics return to competition follow-up after hamstring injury on a professional soccer player: A case study with an inertial sensor unit based methodological approach.

PubMed

Setuain, Igor; Lecumberri, Pablo; Izquierdo, Mikel

2017-10-03

The present research aimed to describe an inertial unit (IU)-based sprint mechanics evaluation model for assessing players' readiness to return to competition after suffering a grade I hamstring injury. A professional male football player (age 19years; height 177cm; weight 70kg, midfielder, Spanish, 3° Division) with a grade 1 biceps femoris injury was evaluated at pre-season, at return to play after injury and at the end of the competitive season. Sprint mechanics were analyzed via the use of an inertial orientation tracker (Xsens Technologies B.V. Enschede, Netherlands) attached over the L3-L4 region of the subject's lumbar spine. Sprint mechanics such as horizontal components of ground reaction force were assessed in both legs during sprinting actions. Findings and interpretation: Both the coefficient of the horizontal force application (SFV) and the ratio of forces (DRF) applied at increasing velocity were decreased in the injured limb compared with the contralateral healthy limb at the return to play evaluation (73% and 76% reductions, respectively) and returned to symmetrical levels at the end-season evaluation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of inertial devices for the control of large, flexible, space-based telerobotic arms

NASA Technical Reports Server (NTRS)

Montgomery, Raymond C.; Kenny, Sean P.; Ghosh, Dave; Shenhar, Joram

1993-01-01

Inertial devices, including sensors and actuators, offer the potential of improving the tracking of telerobotic commands for space-based robots by smoothing payload motions and suppressing vibrations. In this paper, inertial actuators (specifically, torque-wheels and reaction-masses) are studied for that potential application. Batch simulation studies are presented which show that torque-wheels can reduce the overshoot in abrupt stop commands by 82 percent for a two-link arm. For man-in-the-loop evaluation, a real-time simulator has been developed which samples a hand-controller, solves the nonlinear equations of motion, and graphically displays the resulting motion on a computer workstation. Currently, two manipulator models, a two-link, rigid arm and a single-link, flexible arm, have been studied. Results are presented which show that, for a single-link arm, a reaction-mass/torque-wheel combination at the payload end can yield a settling time of 3 s for disturbances in the first flexible mode as opposed to 10 s using only a hub motor. A hardware apparatus, which consists of a single-link, highly flexible arm with a hub motor and a torque-wheel, has been assembled to evaluate the concept and is described herein.

Evaluation of inertial devices for the control of large, flexible, space-based telerobotic arms

NASA Astrophysics Data System (ADS)

Montgomery, Raymond C.; Kenny, Sean P.; Ghosh, Dave; Shenhar, Joram

1993-02-01

Inertial devices, including sensors and actuators, offer the potential of improving the tracking of telerobotic commands for space-based robots by smoothing payload motions and suppressing vibrations. In this paper, inertial actuators (specifically, torque-wheels and reaction-masses) are studied for that potential application. Batch simulation studies are presented which show that torque-wheels can reduce the overshoot in abrupt stop commands by 82 percent for a two-link arm. For man-in-the-loop evaluation, a real-time simulator has been developed which samples a hand-controller, solves the nonlinear equations of motion, and graphically displays the resulting motion on a computer workstation. Currently, two manipulator models, a two-link, rigid arm and a single-link, flexible arm, have been studied. Results are presented which show that, for a single-link arm, a reaction-mass/torque-wheel combination at the payload end can yield a settling time of 3 s for disturbances in the first flexible mode as opposed to 10 s using only a hub motor. A hardware apparatus, which consists of a single-link, highly flexible arm with a hub motor and a torque-wheel, has been assembled to evaluate the concept and is described herein.

Realization of LOS (Line of Sight) stabilization based on reflector using carrier attitude compensation method

NASA Astrophysics Data System (ADS)

Mao, Yao; Tian, Jing; Ma, Jia-guang

2015-02-01

The techonology of LOS stabilization is widely applicated in moving carrier photoelectric systems such as shipborne, airborne and so on. In application situations with compact structure, such as LOS stabilization system of unmanned aerial vehicle, LOS stabilization based on reflector is adopted, and the detector is installed on the carrier to reduce the volume of stabilized platform and loading weight. However, the LOS deflection angle through reflector and the rotation angle of the reflector has a ratio relation of 2:1, simple reflector of stable inertial space can not make the optical axis stable. To eliminate the limitation of mirror stabilizing method, this article puts forward the carrier attitude compensation method, which uses the inertial sensor installed on the carrier to measure the attitude change of the carrier, and the stabilized platform rotating half of the carrier turbulence angle to realize the LOS stabilization.

Vibration Noise Modeling for Measurement While Drilling System Based on FOGs

PubMed Central

Zhang, Chunxi; Wang, Lu; Gao, Shuang; Lin, Tie; Li, Xianmu

2017-01-01

Aiming to improve survey accuracy of Measurement While Drilling (MWD) based on Fiber Optic Gyroscopes (FOGs) in the long period, the external aiding sources are fused into the inertial navigation by the Kalman filter (KF) method. The KF method needs to model the inertial sensors’ noise as the system noise model. The system noise is modeled as white Gaussian noise conventionally. However, because of the vibration while drilling, the noise in gyros isn’t white Gaussian noise any more. Moreover, an incorrect noise model will degrade the accuracy of KF. This paper developed a new approach for noise modeling on the basis of dynamic Allan variance (DAVAR). In contrast to conventional white noise models, the new noise model contains both the white noise and the color noise. With this new noise model, the KF for the MWD was designed. Finally, two vibration experiments have been performed. Experimental results showed that the proposed vibration noise modeling approach significantly improved the estimated accuracies of the inertial sensor drifts. Compared the navigation results based on different noise model, with the DAVAR noise model, the position error and the toolface angle error are reduced more than 90%. The velocity error is reduced more than 65%. The azimuth error is reduced more than 50%. PMID:29039815

Method of producing an inertial sensor

NASA Technical Reports Server (NTRS)

Shcheglov, Kirill V. (Inventor); Challoner, A. Dorian (Inventor)

2008-01-01

The present invention discloses an inertial sensor comprising a planar mechanical resonator with embedded sensing and actuation for substantially in-plane vibration and having a central rigid support for the resonator. At least one excitation or torquer electrode is disposed within an interior of the resonator to excite in-plane vibration of the resonator and at least one sensing or pickoff electrode is disposed within the interior of the resonator for sensing the motion of the excited resonator. In one embodiment, the planar resonator includes a plurality of slots in an annular pattern; in another embodiment, the planar mechanical resonator comprises four masses; each embodiment having a simple degenerate pair of in-plane vibration modes.

Multi-rate cubature Kalman filter based data fusion method with residual compensation to adapt to sampling rate discrepancy in attitude measurement system.

PubMed

Guo, Xiaoting; Sun, Changku; Wang, Peng

2017-08-01

This paper investigates the multi-rate inertial and vision data fusion problem in nonlinear attitude measurement systems, where the sampling rate of the inertial sensor is much faster than that of the vision sensor. To fully exploit the high frequency inertial data and obtain favorable fusion results, a multi-rate CKF (Cubature Kalman Filter) algorithm with estimated residual compensation is proposed in order to adapt to the problem of sampling rate discrepancy. During inter-sampling of slow observation data, observation noise can be regarded as infinite. The Kalman gain is unknown and approaches zero. The residual is also unknown. Therefore, the filter estimated state cannot be compensated. To obtain compensation at these moments, state error and residual formulas are modified when compared with the observation data available moments. Self-propagation equation of the state error is established to propagate the quantity from the moments with observation to the moments without observation. Besides, a multiplicative adjustment factor is introduced as Kalman gain, which acts on the residual. Then the filter estimated state can be compensated even when there are no visual observation data. The proposed method is tested and verified in a practical setup. Compared with multi-rate CKF without residual compensation and single-rate CKF, a significant improvement is obtained on attitude measurement by using the proposed multi-rate CKF with inter-sampling residual compensation. The experiment results with superior precision and reliability show the effectiveness of the proposed method.

Absolute marine gravimetry with matter-wave interferometry.

PubMed

Bidel, Y; Zahzam, N; Blanchard, C; Bonnin, A; Cadoret, M; Bresson, A; Rouxel, D; Lequentrec-Lalancette, M F

2018-02-12

Measuring gravity from an aircraft or a ship is essential in geodesy, geophysics, mineral and hydrocarbon exploration, and navigation. Today, only relative sensors are available for onboard gravimetry. This is a major drawback because of the calibration and drift estimation procedures which lead to important operational constraints. Atom interferometry is a promising technology to obtain onboard absolute gravimeter. But, despite high performances obtained in static condition, no precise measurements were reported in dynamic. Here, we present absolute gravity measurements from a ship with a sensor based on atom interferometry. Despite rough sea conditions, we obtained precision below 10 -5  m s -2 . The atom gravimeter was also compared with a commercial spring gravimeter and showed better performances. This demonstration opens the way to the next generation of inertial sensors (accelerometer, gyroscope) based on atom interferometry which should provide high-precision absolute measurements from a moving platform.

Towards the Development of a Smart Flying Sensor: Illustration in the Field of Precision Agriculture.

PubMed

Hernandez, Andres; Murcia, Harold; Copot, Cosmin; De Keyser, Robin

2015-07-10

Sensing is an important element to quantify productivity, product quality and to make decisions. Applications, such as mapping, surveillance, exploration and precision agriculture, require a reliable platform for remote sensing. This paper presents the first steps towards the development of a smart flying sensor based on an unmanned aerial vehicle (UAV). The concept of smart remote sensing is illustrated and its performance tested for the task of mapping the volume of grain inside a trailer during forage harvesting. Novelty lies in: (1) the development of a position-estimation method with time delay compensation based on inertial measurement unit (IMU) sensors and image processing; (2) a method to build a 3D map using information obtained from a regular camera; and (3) the design and implementation of a path-following control algorithm using model predictive control (MPC). Experimental results on a lab-scale system validate the effectiveness of the proposed methodology.

Towards the Development of a Smart Flying Sensor: Illustration in the Field of Precision Agriculture

PubMed Central

Hernandez, Andres; Murcia, Harold; Copot, Cosmin; De Keyser, Robin

2015-01-01

Sensing is an important element to quantify productivity, product quality and to make decisions. Applications, such as mapping, surveillance, exploration and precision agriculture, require a reliable platform for remote sensing. This paper presents the first steps towards the development of a smart flying sensor based on an unmanned aerial vehicle (UAV). The concept of smart remote sensing is illustrated and its performance tested for the task of mapping the volume of grain inside a trailer during forage harvesting. Novelty lies in: (1) the development of a position-estimation method with time delay compensation based on inertial measurement unit (IMU) sensors and image processing; (2) a method to build a 3D map using information obtained from a regular camera; and (3) the design and implementation of a path-following control algorithm using model predictive control (MPC). Experimental results on a lab-scale system validate the effectiveness of the proposed methodology. PMID:26184205

A Self-Alignment Algorithm for SINS Based on Gravitational Apparent Motion and Sensor Data Denoising

PubMed Central

Liu, Yiting; Xu, Xiaosu; Liu, Xixiang; Yao, Yiqing; Wu, Liang; Sun, Jin

2015-01-01

Initial alignment is always a key topic and difficult to achieve in an inertial navigation system (INS). In this paper a novel self-initial alignment algorithm is proposed using gravitational apparent motion vectors at three different moments and vector-operation. Simulation and analysis showed that this method easily suffers from the random noise contained in accelerometer measurements which are used to construct apparent motion directly. Aiming to resolve this problem, an online sensor data denoising method based on a Kalman filter is proposed and a novel reconstruction method for apparent motion is designed to avoid the collinearity among vectors participating in the alignment solution. Simulation, turntable tests and vehicle tests indicate that the proposed alignment algorithm can fulfill initial alignment of strapdown INS (SINS) under both static and swinging conditions. The accuracy can either reach or approach the theoretical values determined by sensor precision under static or swinging conditions. PMID:25923932

Human Activity Recognition by Combining a Small Number of Classifiers.

PubMed

Nazabal, Alfredo; Garcia-Moreno, Pablo; Artes-Rodriguez, Antonio; Ghahramani, Zoubin

2016-09-01

We consider the problem of daily human activity recognition (HAR) using multiple wireless inertial sensors, and specifically, HAR systems with a very low number of sensors, each one providing an estimation of the performed activities. We propose new Bayesian models to combine the output of the sensors. The models are based on a soft outputs combination of individual classifiers to deal with the small number of sensors. We also incorporate the dynamic nature of human activities as a first-order homogeneous Markov chain. We develop both inductive and transductive inference methods for each model to be employed in supervised and semisupervised situations, respectively. Using different real HAR databases, we compare our classifiers combination models against a single classifier that employs all the signals from the sensors. Our models exhibit consistently a reduction of the error rate and an increase of robustness against sensor failures. Our models also outperform other classifiers combination models that do not consider soft outputs and an Markovian structure of the human activities.

Georeferencing in Gnss-Challenged Environment: Integrating Uwb and Imu Technologies

NASA Astrophysics Data System (ADS)

Toth, C. K.; Koppanyi, Z.; Navratil, V.; Grejner-Brzezinska, D.

2017-05-01

Acquiring geospatial data in GNSS compromised environments remains a problem in mapping and positioning in general. Urban canyons, heavily vegetated areas, indoor environments represent different levels of GNSS signal availability from weak to no signal reception. Even outdoors, with multiple GNSS systems, with an ever-increasing number of satellites, there are many situations with limited or no access to GNSS signals. Independent navigation sensors, such as IMU can provide high-data rate information but their initial accuracy degrades quickly, as the measurement data drift over time unless positioning fixes are provided from another source. At The Ohio State University's Satellite Positioning and Inertial Navigation (SPIN) Laboratory, as one feasible solution, Ultra- Wideband (UWB) radio units are used to aid positioning and navigating in GNSS compromised environments, including indoor and outdoor scenarios. Here we report about experiences obtained with georeferencing a pushcart based sensor system under canopied areas. The positioning system is based on UWB and IMU sensor integration, and provides sensor platform orientation for an electromagnetic inference (EMI) sensor. Performance evaluation results are provided for various test scenarios, confirming acceptable results for applications where high accuracy is not required.

Wearable Device-Based Gait Recognition Using Angle Embedded Gait Dynamic Images and a Convolutional Neural Network.

PubMed

Zhao, Yongjia; Zhou, Suiping

2017-02-28

The widespread installation of inertial sensors in smartphones and other wearable devices provides a valuable opportunity to identify people by analyzing their gait patterns, for either cooperative or non-cooperative circumstances. However, it is still a challenging task to reliably extract discriminative features for gait recognition with noisy and complex data sequences collected from casually worn wearable devices like smartphones. To cope with this problem, we propose a novel image-based gait recognition approach using the Convolutional Neural Network (CNN) without the need to manually extract discriminative features. The CNN's input image, which is encoded straightforwardly from the inertial sensor data sequences, is called Angle Embedded Gait Dynamic Image (AE-GDI). AE-GDI is a new two-dimensional representation of gait dynamics, which is invariant to rotation and translation. The performance of the proposed approach in gait authentication and gait labeling is evaluated using two datasets: (1) the McGill University dataset, which is collected under realistic conditions; and (2) the Osaka University dataset with the largest number of subjects. Experimental results show that the proposed approach achieves competitive recognition accuracy over existing approaches and provides an effective parametric solution for identification among a large number of subjects by gait patterns.

Wearable Device-Based Gait Recognition Using Angle Embedded Gait Dynamic Images and a Convolutional Neural Network

PubMed Central

Zhao, Yongjia; Zhou, Suiping

2017-01-01

The widespread installation of inertial sensors in smartphones and other wearable devices provides a valuable opportunity to identify people by analyzing their gait patterns, for either cooperative or non-cooperative circumstances. However, it is still a challenging task to reliably extract discriminative features for gait recognition with noisy and complex data sequences collected from casually worn wearable devices like smartphones. To cope with this problem, we propose a novel image-based gait recognition approach using the Convolutional Neural Network (CNN) without the need to manually extract discriminative features. The CNN’s input image, which is encoded straightforwardly from the inertial sensor data sequences, is called Angle Embedded Gait Dynamic Image (AE-GDI). AE-GDI is a new two-dimensional representation of gait dynamics, which is invariant to rotation and translation. The performance of the proposed approach in gait authentication and gait labeling is evaluated using two datasets: (1) the McGill University dataset, which is collected under realistic conditions; and (2) the Osaka University dataset with the largest number of subjects. Experimental results show that the proposed approach achieves competitive recognition accuracy over existing approaches and provides an effective parametric solution for identification among a large number of subjects by gait patterns. PMID:28264503

Mastication Evaluation With Unsupervised Learning: Using an Inertial Sensor-Based System

PubMed Central

Lucena, Caroline Vieira; Lacerda, Marcelo; Caldas, Rafael; De Lima Neto, Fernando Buarque

2018-01-01

There is a direct relationship between the prevalence of musculoskeletal disorders of the temporomandibular joint and orofacial disorders. A well-elaborated analysis of the jaw movements provides relevant information for healthcare professionals to conclude their diagnosis. Different approaches have been explored to track jaw movements such that the mastication analysis is getting less subjective; however, all methods are still highly subjective, and the quality of the assessments depends much on the experience of the health professional. In this paper, an accurate and non-invasive method based on a commercial low-cost inertial sensor (MPU6050) to measure jaw movements is proposed. The jaw-movement feature values are compared to the obtained with clinical analysis, showing no statistically significant difference between both methods. Moreover, We propose to use unsupervised paradigm approaches to cluster mastication patterns of healthy subjects and simulated patients with facial trauma. Two techniques were used in this paper to instantiate the method: Kohonen’s Self-Organizing Maps and K-Means Clustering. Both algorithms have excellent performances to process jaw-movements data, showing encouraging results and potential to bring a full assessment of the masticatory function. The proposed method can be applied in real-time providing relevant dynamic information for health-care professionals. PMID:29651365

Improving Inertial Pedestrian Dead-Reckoning by Detecting Unmodified Switched-on Lamps in Buildings

PubMed Central

Jiménez, Antonio R.; Zampella, Francisco; Seco, Fernando

2014-01-01

This paper explores how inertial Pedestrian Dead-Reckoning (PDR) location systems can be improved with the use of a light sensor to measure the illumination gradients created when a person walks under ceiling-mounted unmodified indoor lights. The process of updating the inertial PDR estimates with the information provided by light detections is a new concept that we have named Light-matching (LM). The displacement and orientation change of a person obtained by inertial PDR is used by the LM method to accurately propagate the location hypothesis, and vice versa; the LM approach benefits the PDR approach by obtaining an absolute localization and reducing the PDR-alone drift. Even from an initially unknown location and orientation, whenever the person passes below a switched-on light spot, the location likelihood is iteratively updated until it potentially converges to a unimodal probability density function. The time to converge to a unimodal position hypothesis depends on the number of lights detected and the asymmetries/irregularities of the spatial distribution of lights. The proposed LM method does not require any intensity illumination calibration, just the pre-storage of the position and size of all lights in a building, irrespective of their current on/off state. This paper presents a detailed description of the light-matching concept, the implementation details of the LM-assisted PDR fusion scheme using a particle filter, and several simulated and experimental tests, using a light sensor-equipped Galaxy S3 smartphone and an external foot-mounted inertial sensor. The evaluation includes the LM-assisted PDR approach as well as the fusion with other signals of opportunity (WiFi, RFID, Magnetometers or Map-matching) in order to compare their contribution in obtaining high accuracy indoor localization. The integrated solution achieves a localization error lower than 1 m in most of the cases. PMID:24394599

Ambulatory estimation of foot placement during walking using inertial sensors.

PubMed

Martin Schepers, H; van Asseldonk, Edwin H F; Baten, Chris T M; Veltink, Peter H

2010-12-01

This study proposes a method to assess foot placement during walking using an ambulatory measurement system consisting of orthopaedic sandals equipped with force/moment sensors and inertial sensors (accelerometers and gyroscopes). Two parameters, lateral foot placement (LFP) and stride length (SL), were estimated for each foot separately during walking with eyes open (EO), and with eyes closed (EC) to analyze if the ambulatory system was able to discriminate between different walking conditions. For validation, the ambulatory measurement system was compared to a reference optical position measurement system (Optotrak). LFP and SL were obtained by integration of inertial sensor signals. To reduce the drift caused by integration, LFP and SL were defined with respect to an average walking path using a predefined number of strides. By varying this number of strides, it was shown that LFP and SL could be best estimated using three consecutive strides. LFP and SL estimated from the instrumented shoe signals and with the reference system showed good correspondence as indicated by the RMS difference between both measurement systems being 6.5 ± 1.0 mm (mean ± standard deviation) for LFP, and 34.1 ± 2.7 mm for SL. Additionally, a statistical analysis revealed that the ambulatory system was able to discriminate between the EO and EC condition, like the reference system. It is concluded that the ambulatory measurement system was able to reliably estimate foot placement during walking. Copyright © 2010 Elsevier Ltd. All rights reserved.

Recent machine learning advancements in sensor-based mobility analysis: Deep learning for Parkinson's disease assessment.

PubMed

Eskofier, Bjoern M; Lee, Sunghoon I; Daneault, Jean-Francois; Golabchi, Fatemeh N; Ferreira-Carvalho, Gabriela; Vergara-Diaz, Gloria; Sapienza, Stefano; Costante, Gianluca; Klucken, Jochen; Kautz, Thomas; Bonato, Paolo

2016-08-01

The development of wearable sensors has opened the door for long-term assessment of movement disorders. However, there is still a need for developing methods suitable to monitor motor symptoms in and outside the clinic. The purpose of this paper was to investigate deep learning as a method for this monitoring. Deep learning recently broke records in speech and image classification, but it has not been fully investigated as a potential approach to analyze wearable sensor data. We collected data from ten patients with idiopathic Parkinson's disease using inertial measurement units. Several motor tasks were expert-labeled and used for classification. We specifically focused on the detection of bradykinesia. For this, we compared standard machine learning pipelines with deep learning based on convolutional neural networks. Our results showed that deep learning outperformed other state-of-the-art machine learning algorithms by at least 4.6 % in terms of classification rate. We contribute a discussion of the advantages and disadvantages of deep learning for sensor-based movement assessment and conclude that deep learning is a promising method for this field.

Distributed and Modular CAN-Based Architecture for Hardware Control and Sensor Data Integration

PubMed Central

Losada, Diego P.; Fernández, Joaquín L.; Paz, Enrique; Sanz, Rafael

2017-01-01

In this article, we present a CAN-based (Controller Area Network) distributed system to integrate sensors, actuators and hardware controllers in a mobile robot platform. With this work, we provide a robust, simple, flexible and open system to make hardware elements or subsystems communicate, that can be applied to different robots or mobile platforms. Hardware modules can be connected to or disconnected from the CAN bus while the system is working. It has been tested in our mobile robot Rato, based on a RWI (Real World Interface) mobile platform, to replace the old sensor and motor controllers. It has also been used in the design of two new robots: BellBot and WatchBot. Currently, our hardware integration architecture supports different sensors, actuators and control subsystems, such as motor controllers and inertial measurement units. The integration architecture was tested and compared with other solutions through a performance analysis of relevant parameters such as transmission efficiency and bandwidth usage. The results conclude that the proposed solution implements a lightweight communication protocol for mobile robot applications that avoids transmission delays and overhead. PMID:28467381

Distributed and Modular CAN-Based Architecture for Hardware Control and Sensor Data Integration.

PubMed

Losada, Diego P; Fernández, Joaquín L; Paz, Enrique; Sanz, Rafael

2017-05-03

In this article, we present a CAN-based (Controller Area Network) distributed system to integrate sensors, actuators and hardware controllers in a mobile robot platform. With this work, we provide a robust, simple, flexible and open system to make hardware elements or subsystems communicate, that can be applied to different robots or mobile platforms. Hardware modules can be connected to or disconnected from the CAN bus while the system is working. It has been tested in our mobile robot Rato, based on a RWI (Real World Interface) mobile platform, to replace the old sensor and motor controllers. It has also been used in the design of two new robots: BellBot and WatchBot. Currently, our hardware integration architecture supports different sensors, actuators and control subsystems, such as motor controllers and inertial measurement units. The integration architecture was tested and compared with other solutions through a performance analysis of relevant parameters such as transmission efficiency and bandwidth usage. The results conclude that the proposed solution implements a lightweight communication protocol for mobile robot applications that avoids transmission delays and overhead.

Gait Analysis Methods: An Overview of Wearable and Non-Wearable Systems, Highlighting Clinical Applications

PubMed Central

Muro-de-la-Herran, Alvaro; Garcia-Zapirain, Begonya; Mendez-Zorrilla, Amaia

2014-01-01

This article presents a review of the methods used in recognition and analysis of the human gait from three different approaches: image processing, floor sensors and sensors placed on the body. Progress in new technologies has led the development of a series of devices and techniques which allow for objective evaluation, making measurements more efficient and effective and providing specialists with reliable information. Firstly, an introduction of the key gait parameters and semi-subjective methods is presented. Secondly, technologies and studies on the different objective methods are reviewed. Finally, based on the latest research, the characteristics of each method are discussed. 40% of the reviewed articles published in late 2012 and 2013 were related to non-wearable systems, 37.5% presented inertial sensor-based systems, and the remaining 22.5% corresponded to other wearable systems. An increasing number of research works demonstrate that various parameters such as precision, conformability, usability or transportability have indicated that the portable systems based on body sensors are promising methods for gait analysis. PMID:24556672

Local Observability Analysis of Star Sensor Installation Errors in a SINS/CNS Integration System for Near-Earth Flight Vehicles.

PubMed

Yang, Yanqiang; Zhang, Chunxi; Lu, Jiazhen

2017-01-16

Strapdown inertial navigation system/celestial navigation system (SINS/CNS) integrated navigation is a fully autonomous and high precision method, which has been widely used to improve the hitting accuracy and quick reaction capability of near-Earth flight vehicles. The installation errors between SINS and star sensors have been one of the main factors that restrict the actual accuracy of SINS/CNS. In this paper, an integration algorithm based on the star vector observations is derived considering the star sensor installation error. Then, the star sensor installation error is accurately estimated based on Kalman Filtering (KF). Meanwhile, a local observability analysis is performed on the rank of observability matrix obtained via linearization observation equation, and the observable conditions are presented and validated. The number of star vectors should be greater than or equal to 2, and the times of posture adjustment also should be greater than or equal to 2. Simulations indicate that the star sensor installation error could be readily observable based on the maneuvering condition; moreover, the attitude errors of SINS are less than 7 arc-seconds. This analysis method and conclusion are useful in the ballistic trajectory design of near-Earth flight vehicles.

A heterodyne interferometer for high resolution translation and tilt measurement as optical readout for the LISA inertial sensor

NASA Astrophysics Data System (ADS)

Schuldt, Thilo; Kraus, Hans-Jürgen; Weise, Dennis; Braxmaier, Claus; Peters, Achim; Johann, Ulrich

2017-11-01

The space-based gravitational wave detector LISA (Laser Interferometer Space Antenna) requires a high performance position sensor in order to measure the translation and tilt of the free flying test mass with respect to the LISA optical bench. Here, we present a mechanically highly stable and compact setup of a heterodyne interferometer combined with differential wavefront sensing for the tilt measurement which serves as a demonstrator for an optical readout of the LISA test mass position. First results show noise levels below 1 nm/√Hz and 1 μrad/√Hz, respectively, for frequencies < 10-3 Hz.

A Novel Kalman Filter for Human Motion Tracking With an Inertial-Based Dynamic Inclinometer.

PubMed

Ligorio, Gabriele; Sabatini, Angelo M

2015-08-01

Design and development of a linear Kalman filter to create an inertial-based inclinometer targeted to dynamic conditions of motion. The estimation of the body attitude (i.e., the inclination with respect to the vertical) was treated as a source separation problem to discriminate the gravity and the body acceleration from the specific force measured by a triaxial accelerometer. The sensor fusion between triaxial gyroscope and triaxial accelerometer data was performed using a linear Kalman filter. Wrist-worn inertial measurement unit data from ten participants were acquired while performing two dynamic tasks: 60-s sequence of seven manual activities and 90 s of walking at natural speed. Stereophotogrammetric data were used as a reference. A statistical analysis was performed to assess the significance of the accuracy improvement over state-of-the-art approaches. The proposed method achieved, on an average, a root mean square attitude error of 3.6° and 1.8° in manual activities and locomotion tasks (respectively). The statistical analysis showed that, when compared to few competing methods, the proposed method improved the attitude estimation accuracy. A novel Kalman filter for inertial-based attitude estimation was presented in this study. A significant accuracy improvement was achieved over state-of-the-art approaches, due to a filter design that better matched the basic optimality assumptions of Kalman filtering. Human motion tracking is the main application field of the proposed method. Accurately discriminating the two components present in the triaxial accelerometer signal is well suited for studying both the rotational and the linear body kinematics.

On the Use of Sensor Fusion to Reduce the Impact of Rotational and Additive Noise in Human Activity Recognition

PubMed Central

Banos, Oresti; Damas, Miguel; Pomares, Hector; Rojas, Ignacio

2012-01-01

The main objective of fusion mechanisms is to increase the individual reliability of the systems through the use of the collectivity knowledge. Moreover, fusion models are also intended to guarantee a certain level of robustness. This is particularly required for problems such as human activity recognition where runtime changes in the sensor setup seriously disturb the reliability of the initial deployed systems. For commonly used recognition systems based on inertial sensors, these changes are primarily characterized as sensor rotations, displacements or faults related to the batteries or calibration. In this work we show the robustness capabilities of a sensor-weighted fusion model when dealing with such disturbances under different circumstances. Using the proposed method, up to 60% outperformance is obtained when a minority of the sensors are artificially rotated or degraded, independent of the level of disturbance (noise) imposed. These robustness capabilities also apply for any number of sensors affected by a low to moderate noise level. The presented fusion mechanism compensates the poor performance that otherwise would be obtained when just a single sensor is considered. PMID:22969386

On the use of sensor fusion to reduce the impact of rotational and additive noise in human activity recognition.

PubMed

Banos, Oresti; Damas, Miguel; Pomares, Hector; Rojas, Ignacio

2012-01-01

The main objective of fusion mechanisms is to increase the individual reliability of the systems through the use of the collectivity knowledge. Moreover, fusion models are also intended to guarantee a certain level of robustness. This is particularly required for problems such as human activity recognition where runtime changes in the sensor setup seriously disturb the reliability of the initial deployed systems. For commonly used recognition systems based on inertial sensors, these changes are primarily characterized as sensor rotations, displacements or faults related to the batteries or calibration. In this work we show the robustness capabilities of a sensor-weighted fusion model when dealing with such disturbances under different circumstances. Using the proposed method, up to 60% outperformance is obtained when a minority of the sensors are artificially rotated or degraded, independent of the level of disturbance (noise) imposed. These robustness capabilities also apply for any number of sensors affected by a low to moderate noise level. The presented fusion mechanism compensates the poor performance that otherwise would be obtained when just a single sensor is considered.

Improvement of walking speed and gait symmetry in older patients after hip arthroplasty: a prospective cohort study.

PubMed

Rapp, Walter; Brauner, Torsten; Weber, Linda; Grau, Stefan; Mündermann, Annegret; Horstmann, Thomas

2015-10-12

Retraining walking in patients after hip or knee arthroplasty is an important component of rehabilitation especially in older persons whose social interactions are influenced by their level of mobility. The objective of this study was to test the effect of an intensive inpatient rehabilitation program on walking speed and gait symmetry in patients after hip arthroplasty (THA) using inertial sensor technology. Twenty-nine patients undergoing a 4-week inpatient rehabilitation program following THA and 30 age-matched healthy subjects participated in this study. Walking speed and gait symmetry parameters were measured using inertial sensor device for standardized walking trials (2*20.3 m in a gym) at their self-selected normal and fast walking speeds on postoperative days 15, 21, and 27 in patients and in a single session in control subjects. Walking speed was measured using timing lights. Gait symmetry was determined using autocorrelation calculation of the cranio-caudal (CC) acceleration signals from an inertial sensor placed at the lower spine. Walking speed and gait symmetry improved from postoperative days 15-27 (speed, female: 3.2 and 4.5 m/s; male: 4.2 and 5.2 m/s; autocorrelation, female: 0.77 and 0.81; male: 0.70 and 0.79; P <0.001 for all). After the 4-week rehabilitation program, walking speed and gait symmetry were still lower than those in control subjects (speed, female 4.5 m/s vs. 5.7 m/s; male: 5.2 m/s vs. 5.3 m/s; autocorrelation, female: 0.81 vs. 0.88; male: 0.79 vs. 0.90; P <0.001 for all). While patients with THA improved their walking capacity during a 4-week inpatient rehabilitation program, subsequent intensive gait training is warranted for achieving normal gait symmetry. Inertial sensor technology may be a useful tool for evaluating the rehabilitation process during the post-inpatient period.

Assessment and Rehabilitation of Central Sensory Impairments for Balance in mTBI

DTIC Science & Technology

2016-10-01

place; 95% complete. ● Purchasing and testing software of Opals ; awaiting release of newer, updated sensor from APDM to determine need for more sensors...2016. ● Develop new algorithm to automatically quantify head movements from Opal sensor; 100% complete 23-Sep-2016. ● Set up and test gait paradigm...Interaction in Balance (mCTSIB), Modified Balance Error Scoring System (mBESS) and walking tests, subjects wear five Opal inertial sensors (APDM, Inc

Rotigotine for nocturnal hypokinesia in Parkinson's disease: Quantitative analysis of efficacy from a randomized, placebo-controlled trial using an axial inertial sensor.

PubMed

Bhidayasiri, Roongroj; Sringean, Jirada; Chaiwong, Suchapit; Anan, Chanawat; Penkeaw, Nuntiwat; Leaknok, Amarinee; Boonpang, Kamolwan; Saksornchai, Karn; Rattanachaisit, Watchara; Thanawattano, Chusak; Jagota, Priya

2017-11-01

Nocturnal hypokinesia is a common symptom in Parkinson's disease (PD), negatively affecting quality of life of both patients and caregivers. However, evidence-based treatment strategies are limited. To evaluate the efficacy of rotigotine transdermal patch, using a wearable sensor, in the management of nocturnal immobility. 34 PD subjects with nocturnal immobility were randomized to receive rotigotine transdermal patch (mean ± SD of 10.46 ± 4.63 mg/24 h, n = 17) or placebo patch (n = 17). Treatment was titrated to an optimal dose over 1-8 weeks, then maintained for 4 weeks. Primary endpoints were objective parameters assessing axial rotation measured using an axial inertial sensor (the NIGHT-Recorder) over two nights at the patients' home. Scale-based assessments were also performed. There was a significant difference, in favor of rotigotine, in change from baseline score in the number of turns in bed (ANCOVA, p = 0.001), and degree of axial turn (p = 0.042). These objective improvements were mirrored by significantly greater improvements in clinical scale-based assessments, including the Unified Parkinson's Disease Rating Scale (UPDRS) total scores (p = 0.009), UPDRS-motor scores (p < 0.001), UPDRS-axial scores (p = 0.01), the Modified Parkinson's Disease Sleep Scale (p < 0.001), the Nocturnal Akinesia Dystonia and Cramp Scale (p = 0.003) and the eight-item PD Questionnaire (PDQ-8) scores (p = 0.01) from baseline to end of treatment in patients given rotigotine compared to placebo. We show that the rotigotine patch provides a significant improvement in nocturnal symptoms as assessed using both objective measures and clinical rating scales. The study demonstrates the feasibility of using wearable sensors to record objective outcomes in PD-related clinical trials. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1

NASA Technical Reports Server (NTRS)

Park, Thomas; Smith, Austin; Oliver, T. Emerson

2018-01-01

The NASA Space Launch System Block 1 launch vehicle is equipped with an Inertial Navigation System (INS) and multiple Rate Gyro Assemblies (RGA) that are used in the Guidance, Navigation, and Control (GN&C) algorithms. The INS provides the inertial position, velocity, and attitude of the vehicle along with both angular rate and specific force measurements. Additionally, multiple sets of co-located rate gyros supply angular rate data. The collection of angular rate data, taken along the launch vehicle, is used to separate out vehicle motion from flexible body dynamics. Since the system architecture uses redundant sensors, the capability was developed to evaluate the health (or validity) of the independent measurements. A suite of Sensor Data Quality (SDQ) algorithms is responsible for assessing the angular rate data from the redundant sensors. When failures are detected, SDQ will take the appropriate action and disqualify or remove faulted sensors from forward processing. Additionally, the SDQ algorithms contain logic for down-selecting the angular rate data used by the GNC software from the set of healthy measurements. This paper explores the trades and analyses that were performed in selecting a set of robust fault-detection algorithms included in the GN&C flight software. These trades included both an assessment of hardware-provided health and status data as well as an evaluation of different algorithms based on time-to-detection, type of failures detected, and probability of detecting false positives. We then provide an overview of the algorithms used for both fault-detection and measurement down selection. We next discuss the role of trajectory design, flexible-body models, and vehicle response to off-nominal conditions in setting the detection thresholds. Lastly, we present lessons learned from software integration and hardware-in-the-loop testing.

A compact, large-range interferometer for precision measurement and inertial sensing

NASA Astrophysics Data System (ADS)

Cooper, S. J.; Collins, C. J.; Green, A. C.; Hoyland, D.; Speake, C. C.; Freise, A.; Mow-Lowry, C. M.

2018-05-01

We present a compact, fibre-coupled interferometer with high sensitivity and a large working range. We propose to use this interferometer as a readout mechanism for future inertial sensors, removing a major limiting noise source, and in precision positioning systems. The interferometer’s peak sensitivity is 2 × 10-{14} m \\sqrt{Hz-1} at 70 Hz and 7 × 10-{11} m \\sqrt{Hz-1} at 10 mHz. If deployed on a GS-13 geophone, the resulting inertial sensing output will be limited by the suspension thermal noise of the reference mass from 10 mHz to 2 Hz.

Bioinspired optical sensors for unmanned aerial systems

NASA Astrophysics Data System (ADS)

Chahl, Javaan; Rosser, Kent; Mizutani, Akiko

2011-04-01

Insects are dependant on the spatial, spectral and temporal distributions of light in the environment for flight control and navigation. This paper reports on flight trials of implementations of insect inspired behaviors on unmanned aerial vehicles. Optical flow methods for maintaining a constant height above ground and a constant course have been demonstrated to provide navigation capabilities that are impossible using conventional avionics sensors. Precision control of height above ground and ground course were achieved over long distances. Other vision based techniques demonstrated include a biomimetic stabilization sensor that uses the ultraviolet and green bands of the spectrum, and a sky polarization compass. Both of these sensors were tested over long trajectories in different directions, in each case showing performance similar to low cost inertial heading and attitude systems. The behaviors demonstrate some of the core functionality found in the lower levels of the sensorimotor system of flying insects and shows promise for more integrated solutions in the future.

A Solar Position Sensor Based on Image Vision.

PubMed

Ruelas, Adolfo; Velázquez, Nicolás; Villa-Angulo, Carlos; Acuña, Alexis; Rosales, Pedro; Suastegui, José

2017-07-29

Solar collector technologies operate with better performance when the Sun beam direction is normal to the capturing surface, and for that to happen despite the relative movement of the Sun, solar tracking systems are used, therefore, there are rules and standards that need minimum accuracy for these tracking systems to be used in solar collectors' evaluation. Obtaining accuracy is not an easy job, hence in this document the design, construction and characterization of a sensor based on a visual system that finds the relative azimuth error and height of the solar surface of interest, is presented. With these characteristics, the sensor can be used as a reference in control systems and their evaluation. The proposed sensor is based on a microcontroller with a real-time clock, inertial measurement sensors, geolocation and a vision sensor, that obtains the angle of incidence from the sunrays' direction as well as the tilt and sensor position. The sensor's characterization proved how a measurement of a focus error or a Sun position can be made, with an accuracy of 0.0426° and an uncertainty of 0.986%, which can be modified to reach an accuracy under 0.01°. The validation of this sensor was determined showing the focus error on one of the best commercial solar tracking systems, a Kipp & Zonen SOLYS 2. To conclude, the solar tracking sensor based on a vision system meets the Sun detection requirements and components that meet the accuracy conditions to be used in solar tracking systems and their evaluation or, as a tracking and orientation tool, on photovoltaic installations and solar collectors.

Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1

NASA Technical Reports Server (NTRS)

Park, Thomas; Oliver, Emerson; Smith, Austin

2018-01-01

The NASA Space Launch System Block 1 launch vehicle is equipped with an Inertial Navigation System (INS) and multiple Rate Gyro Assemblies (RGA) that are used in the Guidance, Navigation, and Control (GN&C) algorithms. The INS provides the inertial position, velocity, and attitude of the vehicle along with both angular rate and specific force measurements. Additionally, multiple sets of co-located rate gyros supply angular rate data. The collection of angular rate data, taken along the launch vehicle, is used to separate out vehicle motion from flexible body dynamics. Since the system architecture uses redundant sensors, the capability was developed to evaluate the health (or validity) of the independent measurements. A suite of Sensor Data Quality (SDQ) algorithms is responsible for assessing the angular rate data from the redundant sensors. When failures are detected, SDQ will take the appropriate action and disqualify or remove faulted sensors from forward processing. Additionally, the SDQ algorithms contain logic for down-selecting the angular rate data used by the GN&C software from the set of healthy measurements. This paper provides an overview of the algorithms used for both fault-detection and measurement down selection.

Extraction and Analysis of Respiratory Motion Using Wearable Inertial Sensor System during Trunk Motion

PubMed Central

Gaidhani, Apoorva; Moon, Kee S.; Ozturk, Yusuf; Lee, Sung Q.; Youm, Woosub

2017-01-01

Respiratory activity is an essential vital sign of life that can indicate changes in typical breathing patterns and irregular body functions such as asthma and panic attacks. Many times, there is a need to monitor breathing activity while performing day-to-day functions such as standing, bending, trunk stretching or during yoga exercises. A single IMU (inertial measurement unit) can be used in measuring respiratory motion; however, breathing motion data may be influenced by a body trunk movement that occurs while recording respiratory activity. This research employs a pair of wireless, wearable IMU sensors custom-made by the Department of Electrical Engineering at San Diego State University. After appropriate sensor placement for data collection, this research applies principles of robotics, using the Denavit-Hartenberg convention, to extract relative angular motion between the two sensors. One of the obtained relative joint angles in the “Sagittal” plane predominantly yields respiratory activity. An improvised version of the proposed method and wearable, wireless sensors can be suitable to extract respiratory information while performing sports or exercises, as they do not restrict body motion or the choice of location to gather data. PMID:29258214

Estimation of Attitude and External Acceleration Using Inertial Sensor Measurement During Various Dynamic Conditions

PubMed Central

Lee, Jung Keun; Park, Edward J.; Robinovitch, Stephen N.

2012-01-01

This paper proposes a Kalman filter-based attitude (i.e., roll and pitch) estimation algorithm using an inertial sensor composed of a triaxial accelerometer and a triaxial gyroscope. In particular, the proposed algorithm has been developed for accurate attitude estimation during dynamic conditions, in which external acceleration is present. Although external acceleration is the main source of the attitude estimation error and despite the need for its accurate estimation in many applications, this problem that can be critical for the attitude estimation has not been addressed explicitly in the literature. Accordingly, this paper addresses the combined estimation problem of the attitude and external acceleration. Experimental tests were conducted to verify the performance of the proposed algorithm in various dynamic condition settings and to provide further insight into the variations in the estimation accuracy. Furthermore, two different approaches for dealing with the estimation problem during dynamic conditions were compared, i.e., threshold-based switching approach versus acceleration model-based approach. Based on an external acceleration model, the proposed algorithm was capable of estimating accurate attitudes and external accelerations for short accelerated periods, showing its high effectiveness during short-term fast dynamic conditions. Contrariwise, when the testing condition involved prolonged high external accelerations, the proposed algorithm exhibited gradually increasing errors. However, as soon as the condition returned to static or quasi-static conditions, the algorithm was able to stabilize the estimation error, regaining its high estimation accuracy. PMID:22977288

Strategy quantification using body worn inertial sensors in a reactive agility task.

PubMed

Eke, Chika U; Cain, Stephen M; Stirling, Leia A

2017-11-07

Agility performance is often evaluated using time-based metrics, which provide little information about which factors aid or limit success. The objective of this study was to better understand agility strategy by identifying biomechanical metrics that were sensitive to performance speed, which were calculated with data from an array of body-worn inertial sensors. Five metrics were defined (normalized number of foot contacts, stride length variance, arm swing variance, mean normalized stride frequency, and number of body rotations) that corresponded to agility terms defined by experts working in athletic, clinical, and military environments. Eighteen participants donned 13 sensors to complete a reactive agility task, which involved navigating a set of cones in response to a vocal cue. Participants were grouped into fast, medium, and slow performance based on their completion time. Participants in the fast group had the smallest number of foot contacts (normalizing by height), highest stride length variance (normalizing by height), highest forearm angular velocity variance, and highest stride frequency (normalizing by height). The number of body rotations was not sensitive to speed and may have been determined by hand and foot dominance while completing the agility task. The results of this study have the potential to inform the development of a composite agility score constructed from the list of significant metrics. By quantifying the agility terms previously defined by expert evaluators through an agility score, this study can assist in strategy development for training and rehabilitation across athletic, clinical, and military domains. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Smartphone Application Suite for Assessing Mobility.

PubMed

Madhushri, Priyanka; Dzhagaryan, Armen A; Jovanov, Emil; Milenkovic, Aleksandar

2016-08-01

Modern smartphones integrate a growing number of inertial and environmental sensors that can enable the development of new mobile health applications. In this paper we introduce a suite of smartphone applications for assessing mobility in elderly population. The suite currently includes applications that automate and quantify the following standardized medical tests for assessing mobility: Timed-Up-and-Go (TUG), 30 Seconds Chair Stand Test (30SCS), and a 4-stage Balance Test (4SBT). For each smartphone application we describe its functionality and a list of parameters extracted by processing signals from smartphone's inertial sensors. The paper shows the results from studies conducted on geriatric patients for TUG tests and from studies conducted in the laboratory on healthy subjects for 30SCS and 4SBT tests.

Suggested notation conventions for rotational seismology

USGS Publications Warehouse

Evans, J.R.

2009-01-01

We note substantial inconsistency among authors discussing rotational motions observed with inertial seismic sensors (and much more so in the broader topic of rotational phenomena). Working from physics and other precedents, we propose standard terminology and a preferred reference frame for inertial sensors (Fig. 1) that may be consistently used in discussions of both finite and infinitesimal observed rotational and translational motions in seismology and earthquake engineering. The scope of this article is limited to observations because there are significant differences in the analysis of finite and infinitesimal rotations, though such discussions should remain compatible with those presented here where possible. We recommend the general use of the notation conventions presented in this tutorial, and we recommend that any deviations or alternatives be explicitly defined.

Atom interferometric gravity gradiometer: Disturbance compensation and mobile gradiometry

NASA Astrophysics Data System (ADS)

Mahadeswaraswamy, Chetan

First ever mobile gravity gradient measurement based on Atom Interferometric sensors has been demonstrated. Mobile gravity gradiometers play a significant role in high accuracy inertial navigation systems in order to distinguish inertial acceleration and acceleration due to gravity. The gravity gradiometer consists of two atom interferometric accelerometers. In each of the accelerometer an ensemble of laser cooled Cesium atoms is dropped and using counter propagating Raman pulses (pi/2-pi-pi/2) the ensemble is split into two states for carrying out atom interferometry. The interferometer phase is proportional to the specific force experienced by the atoms which is a combination of inertial acceleration and acceleration due to gravity. The difference in phase between the two atom interferometric sensors is proportional to gravity gradient if the platform does not undergo any rotational motion. However, any rotational motion of the platform induces spurious gravity gradient measurements. This apparent gravity gradient due to platform rotation is considerably different for an atom interferometric sensor compared to a conventional force rebalance type sensor. The atoms are in free fall and are not influenced by the motion of the case except at the instants of Raman pulses. A model for determining apparent gravity gradient due to rotation of platform was developed and experimentally verified for different frequencies. This transfer function measurement also lead to the development of a new technique for aligning the Raman laser beams with the atom clusters to within 20 mu rad. This gravity gradiometer is situated in a truck for the purpose of undertaking mobile surveys. A disturbance compensation system was designed and built in order to compensate for the rotational disturbances experienced on the floor of a truck. An electric drive system was also designed specifically to be able to move the truck in a uniform motion at very low speeds of about 1cm/s. A 250 x10-9 s-2 gravity gradient signature due to an underground void at Hansen Experimental Physics Building at Stanford was successfully measured using this mobile gradiometer.

Registering Ground and Satellite Imagery for Visual Localization

DTIC Science & Technology

2012-08-01

reckoning, inertial, stereo, light detection and ranging ( LIDAR ), cellular radio, and visual. As no sensor or algorithm provides perfect localization in...by metric localization approaches to confine the region of a map that needs to be searched. Simultaneous Localization and Mapping ( SLAM ) (5, 6), using...estimate the metric location of the camera. Se et al. (7) use SIFT features for both appearance-based global localization and incremental 3D SLAM . Johns and

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.

Pushbroom Stereo for High-Speed Navigation in Cluttered Environments

DTIC Science & Technology

2014-09-01

inertial measurement sensors such as Achtelik et al .’s implemention of PTAM (parallel tracking and mapping) [15] with a barometric altimeter, stable flights...in indoor and outdoor environments are possible [1]. With a full vison- aided inertial navigation system (VINS), Li et al . have shown remarkable...avoidance on small UAVs. Stereo systems suffer from a similar speed issue, with most modern systems running at or below 30 Hz [8], [27]. Honegger et

Detailed Test Plan Redundant Sensor Strapdown IMU Evaluation Program

NASA Technical Reports Server (NTRS)

Hartwell, T.; Miyatake, Y.; Wedekind, D. E.

1971-01-01

The test plan for a redundant sensor strapdown inertial measuring unit evaluation program is presented. The subjects discussed are: (1) test philosophy and limitations, (2) test sequence, (3) equipment specifications, (4) general operating procedures, (5) calibration procedures, (6) alignment test phase, and (7) navigation test phase. The data and analysis requirements are analyzed.

Enhancing Autonomy of Aerial Systems Via Integration of Visual Sensors into Their Avionics Suite

DTIC Science & Technology

2016-09-01

aerial platform for subsequent visual sensor integration. 14. SUBJECT TERMS autonomous system, quadrotors, direct method, inverse ...CONTROLLER ARCHITECTURE .....................................................43 B. INVERSE DYNAMICS IN THE VIRTUAL DOMAIN ......................45 1...control station GPS Global-Positioning System IDVD inverse dynamics in the virtual domain ILP integer linear program INS inertial-navigation system

Modeling and sensory feedback control for space manipulators

NASA Technical Reports Server (NTRS)

Masutani, Yasuhiro; Miyazaki, Fumio; Arimoto, Suguru

1989-01-01

The positioning control problem of the endtip of space manipulators whose base are uncontrolled is examined. In such a case, the conventional control method for industrial robots based on a local feedback at each joint is not applicable, because a solution of the joint displacements that satisfies a given position and orientation of the endtip is not decided uniquely. A sensory feedback control scheme for space manipulators based on an artificial potential defined in a task-oriented coordinates is proposed. Using this scheme, the controller can easily determine the input torque of each joint from the data of an external sensor such as a visual device. Since the external sensor is mounted on the unfixed base, the manipulator must track the moving image of the target in sensor coordinates. Moreover the dynamics of the base and the manipulator are interactive. However, the endtip is proven to asymptotically approach the stationary target in an inertial coordinate frame by the Liapunov's method. Finally results of computer simulation for a 6-link space manipulator model show the effectiveness of the proposed scheme.

Dynamic Accuracy of Inertial Magnetic Sensor Modules

DTIC Science & Technology

2016-12-01

and the cost of the YEI 3-space data-logging sensor was justified. C. PREVIOUS WORK In [7], Jeremy Cookson built a low-cost pendulum with an optical...encoder to test the dynamic accuracy of MARG sensor modules. The pendulum was designed in order to execute dynamic, repeatable tests in a single...3DM-GX1 and 3DM-GX3-25 sensors. In [8], Leslie Landry developed similar repeatable tests and utilized the pendulum to test the dynamic accuracy of

A new method for determining which stars are near a star sensor field-of-view

NASA Technical Reports Server (NTRS)

Yates, Russell E., Jr.; Vedder, John D.

1991-01-01

A new method is described for determining which stars in a navigation star catalog are near a star sensor field of view (FOV). This method assumes that an estimate of spacecraft inertial attitude is known. Vector component ranges for the star sensor FOV are computed, so that stars whose vector components lie within these ranges are near the star sensor FOV. This method requires no presorting of the navigation star catalog, and is more efficient than tradition methods.

Investigation of Anticipatory Postural Adjustments during One-Leg Stance Using Inertial Sensors: Evidence from Subjects with Parkinsonism

PubMed Central

Bonora, Gianluca; Mancini, Martina; Carpinella, Ilaria; Chiari, Lorenzo; Ferrarin, Maurizio; Nutt, John G.; Horak, Fay B.

2017-01-01

The One-Leg Stance (OLS) test is a widely adopted tool for the clinical assessment of balance in the elderly and in subjects with neurological disorders. It was previously showed that the ability to control anticipatory postural adjustments (APAs) prior to lifting one leg is significantly impaired by idiopathic Parkinson’s disease (iPD). However, it is not known how APAs are affected by other types of parkinsonism, such as frontal gait disorders (FGD). In this study, an instrumented OLS test based on wearable inertial sensors is proposed to investigate both the initial anticipatory phase and the subsequent unipedal balance. The sensitivity and the validity of the test have been evaluated. Twenty-five subjects with iPD presenting freezing of gait (FOG), 33 with iPD without FOG, 13 with FGD, and 32 healthy elderly controls were recruited. All subjects wore three inertial sensors positioned on the posterior trunk (L4–L5), and on the left and right frontal face of the tibias. Participants were asked to lift a foot and stand on a single leg as long as possible with eyes open, as proposed by the mini-BESTest. Temporal parameters and trunk acceleration were extracted from sensors and compared among groups. The results showed that, regarding the anticipatory phase, the peak of mediolateral trunk acceleration was significantly reduced compared to healthy controls (p < 0.05) in subjects with iPD with and without FOG, but not in FGD group (p = 0.151). Regarding the balance phase duration, a significant shortening was found in the three parkinsonian groups compared to controls (p < 0.001). Moreover, balance was significantly longer (p < 0.001) in iPD subjects without FOG compared to subjects with FGD and iPD subjects presenting FOG. Strong correlations between balance duration extracted by sensors and clinical mini-BESTest scores were found (ρ > 0.74), demonstrating the method’s validity. Our findings support the validity of the proposed method for assessing the OLS test and its sensitivity in distinguishing among the tested groups. The instrumented test discriminated between healthy controls and people with parkinsonism and among the three groups with parkinsonism. The objective characterization of the initial anticipatory phase represents an interesting improvement compared to most clinical OLS tests. PMID:28790972

Investigation of Anticipatory Postural Adjustments during One-Leg Stance Using Inertial Sensors: Evidence from Subjects with Parkinsonism.

PubMed

Bonora, Gianluca; Mancini, Martina; Carpinella, Ilaria; Chiari, Lorenzo; Ferrarin, Maurizio; Nutt, John G; Horak, Fay B

2017-01-01

The One-Leg Stance (OLS) test is a widely adopted tool for the clinical assessment of balance in the elderly and in subjects with neurological disorders. It was previously showed that the ability to control anticipatory postural adjustments (APAs) prior to lifting one leg is significantly impaired by idiopathic Parkinson's disease (iPD). However, it is not known how APAs are affected by other types of parkinsonism, such as frontal gait disorders (FGD). In this study, an instrumented OLS test based on wearable inertial sensors is proposed to investigate both the initial anticipatory phase and the subsequent unipedal balance. The sensitivity and the validity of the test have been evaluated. Twenty-five subjects with iPD presenting freezing of gait (FOG), 33 with iPD without FOG, 13 with FGD, and 32 healthy elderly controls were recruited. All subjects wore three inertial sensors positioned on the posterior trunk (L4-L5), and on the left and right frontal face of the tibias. Participants were asked to lift a foot and stand on a single leg as long as possible with eyes open, as proposed by the mini-BESTest. Temporal parameters and trunk acceleration were extracted from sensors and compared among groups. The results showed that, regarding the anticipatory phase, the peak of mediolateral trunk acceleration was significantly reduced compared to healthy controls ( p  < 0.05) in subjects with iPD with and without FOG, but not in FGD group ( p  = 0.151). Regarding the balance phase duration, a significant shortening was found in the three parkinsonian groups compared to controls ( p  < 0.001). Moreover, balance was significantly longer ( p  < 0.001) in iPD subjects without FOG compared to subjects with FGD and iPD subjects presenting FOG. Strong correlations between balance duration extracted by sensors and clinical mini-BESTest scores were found (ρ > 0.74), demonstrating the method's validity. Our findings support the validity of the proposed method for assessing the OLS test and its sensitivity in distinguishing among the tested groups. The instrumented test discriminated between healthy controls and people with parkinsonism and among the three groups with parkinsonism. The objective characterization of the initial anticipatory phase represents an interesting improvement compared to most clinical OLS tests.

Novel Hybrid of LS-SVM and Kalman Filter for GPS/INS Integration

NASA Astrophysics Data System (ADS)

Xu, Zhenkai; Li, Yong; Rizos, Chris; Xu, Xiaosu

Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) technologies can overcome the drawbacks of the individual systems. One of the advantages is that the integrated solution can provide continuous navigation capability even during GPS outages. However, bridging the GPS outages is still a challenge when Micro-Electro-Mechanical System (MEMS) inertial sensors are used. Methods being currently explored by the research community include applying vehicle motion constraints, optimal smoother, and artificial intelligence (AI) techniques. In the research area of AI, the neural network (NN) approach has been extensively utilised up to the present. In an NN-based integrated system, a Kalman filter (KF) estimates position, velocity and attitude errors, as well as the inertial sensor errors, to output navigation solutions while GPS signals are available. At the same time, an NN is trained to map the vehicle dynamics with corresponding KF states, and to correct INS measurements when GPS measurements are unavailable. To achieve good performance it is critical to select suitable quality and an optimal number of samples for the NN. This is sometimes too rigorous a requirement which limits real world application of NN-based methods.The support vector machine (SVM) approach is based on the structural risk minimisation principle, instead of the minimised empirical error principle that is commonly implemented in an NN. The SVM can avoid local minimisation and over-fitting problems in an NN, and therefore potentially can achieve a higher level of global performance. This paper focuses on the least squares support vector machine (LS-SVM), which can solve highly nonlinear and noisy black-box modelling problems. This paper explores the application of the LS-SVM to aid the GPS/INS integrated system, especially during GPS outages. The paper describes the principles of the LS-SVM and of the KF hybrid method, and introduces the LS-SVM regression algorithm. Field test data is processed to evaluate the performance of the proposed approach.

Development of a facility using robotics for testing automation of inertial instruments

NASA Technical Reports Server (NTRS)

Greig, Joy Y.; Lamont, Gary B.; Biezad, Daniel J.; Lewantowicz, Zdsislaw H.; Greig, Joy Y.

1987-01-01

The Integrated Robotics System Simulation (ROBSIM) was used to evaluate the performance of the PUMA 560 arm as applied to testing of inertial sensors. Results of this effort were used in the design and development of a feasibility test environment using a PUMA 560 arm. The implemented facility demonstrated the ability to perform conventional static inertial instrument tests (rotation and tumble). The facility included an efficient data acquisitions capability along with a precision test servomechanism function resulting in various data presentations which are included in the paper. Analysis of inertial instrument testing accuracy, repeatability and noise characteristics are provided for the PUMA 560 as well as for other possible commercial arm configurations. Another integral aspect of the effort was an in-depth economic analysis and comparison of robot arm testing versus use of contemporary precision test equipment.

The Homogeneity of Optimal Sensor Placement Across Multiple Winged Insect Species

NASA Astrophysics Data System (ADS)

Jenkins, Abigail L.

Taking inspiration from biology, control algorithms can be implemented to imitate the naturally occurring control systems present in nature. This research is primarily concerned with insect flight and optimal wing sensor placement. Many winged insects with halteres are equipped with mechanoreceptors termed campaniform sensilla. Although the exact information these receptors provide to the insect's nervous system is unknown, it is thought to have the capability of measuring inertial rotation forces. During flight, when the wing bends, the information measured by the campaniform sensilla is received by the central nervous system, and provides the insect necessary data to control flight. This research compares three insect species - the hawkmoth Manduca sexta, the honeybee Apis mellifera, and the fruit fly Drosophila melanogaster. Using an observability-based sensor placement algorithm, the optimal sensor placement for these three species is determined. Simulations resolve if this optimal sensor placement corresponds to the insect's campaniform sensilla, as well as if placement is homogeneous across species.

A Highly Miniaturized, Wireless Inertial Measurement Unit for Characterizing the Dynamics of Pitched Baseballs and Softballs

PubMed Central

McGinnis, Ryan S.; Perkins, Noel C.

2012-01-01

Baseball and softball pitch types are distinguished by the path and speed of the ball which, in turn, are determined by the angular velocity of the ball and the velocity of the ball center at the instant of release from the pitcher's hand. While radar guns and video-based motion capture (mocap) resolve ball speed, they provide little information about how the angular velocity of the ball and the velocity of the ball center develop and change during the throwing motion. Moreover, mocap requires measurements in a controlled lab environment and by a skilled technician. This study addresses these shortcomings by introducing a highly miniaturized, wireless inertial measurement unit (IMU) that is embedded in both baseballs and softballs. The resulting “ball-embedded” sensor resolves ball dynamics right on the field of play. Experimental results from ten pitches, five thrown by one softball pitcher and five by one baseball pitcher, demonstrate that this sensor technology can deduce the magnitude and direction of the ball's velocity at release to within 4.6% of measurements made using standard mocap. Moreover, the IMU directly measures the angular velocity of the ball, which further enables the analysis of different pitch types.

3D indoor modeling using a hand-held embedded system with multiple laser range scanners

NASA Astrophysics Data System (ADS)

Hu, Shaoxing; Wang, Duhu; Xu, Shike

2016-10-01

Accurate three-dimensional perception is a key technology for many engineering applications, including mobile mapping, obstacle detection and virtual reality. In this article, we present a hand-held embedded system designed for constructing 3D representation of structured indoor environments. Different from traditional vehicle-borne mobile mapping methods, the system presented here is capable of efficiently acquiring 3D data while an operator carrying the device traverses through the site. It consists of a simultaneous localization and mapping(SLAM) module, a 3D attitude estimate module and a point cloud processing module. The SLAM is based on a scan matching approach using a modern LIDAR system, and the 3D attitude estimate is generated by a navigation filter using inertial sensors. The hardware comprises three 2D time-flight laser range finders and an inertial measurement unit(IMU). All the sensors are rigidly mounted on a body frame. The algorithms are developed on the frame of robot operating system(ROS). The 3D model is constructed using the point cloud library(PCL). Multiple datasets have shown robust performance of the presented system in indoor scenarios.

Angular Rate Optimal Design for the Rotary Strapdown Inertial Navigation System

PubMed Central

Yu, Fei; Sun, Qian

2014-01-01

Due to the characteristics of high precision for a long duration, the rotary strapdown inertial navigation system (RSINS) has been widely used in submarines and surface ships. Nowadays, the core technology, the rotating scheme, has been studied by numerous researchers. It is well known that as one of the key technologies, the rotating angular rate seriously influences the effectiveness of the error modulating. In order to design the optimal rotating angular rate of the RSINS, the relationship between the rotating angular rate and the velocity error of the RSINS was analyzed in detail based on the Laplace transform and the inverse Laplace transform in this paper. The analysis results showed that the velocity error of the RSINS depends on not only the sensor error, but also the rotating angular rate. In order to minimize the velocity error, the rotating angular rate of the RSINS should match the sensor error. One optimal design method for the rotating rate of the RSINS was also proposed in this paper. Simulation and experimental results verified the validity and superiority of this optimal design method for the rotating rate of the RSINS. PMID:24759115

An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database.

PubMed

Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang

2016-01-28

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m.

An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database

PubMed Central

Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang

2016-01-01

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m. PMID:26828496

A Solar Position Sensor Based on Image Vision

PubMed Central

Ruelas, Adolfo; Velázquez, Nicolás; Villa-Angulo, Carlos; Rosales, Pedro; Suastegui, José

2017-01-01

Solar collector technologies operate with better performance when the Sun beam direction is normal to the capturing surface, and for that to happen despite the relative movement of the Sun, solar tracking systems are used, therefore, there are rules and standards that need minimum accuracy for these tracking systems to be used in solar collectors’ evaluation. Obtaining accuracy is not an easy job, hence in this document the design, construction and characterization of a sensor based on a visual system that finds the relative azimuth error and height of the solar surface of interest, is presented. With these characteristics, the sensor can be used as a reference in control systems and their evaluation. The proposed sensor is based on a microcontroller with a real-time clock, inertial measurement sensors, geolocation and a vision sensor, that obtains the angle of incidence from the sunrays’ direction as well as the tilt and sensor position. The sensor’s characterization proved how a measurement of a focus error or a Sun position can be made, with an accuracy of 0.0426° and an uncertainty of 0.986%, which can be modified to reach an accuracy under 0.01°. The validation of this sensor was determined showing the focus error on one of the best commercial solar tracking systems, a Kipp & Zonen SOLYS 2. To conclude, the solar tracking sensor based on a vision system meets the Sun detection requirements and components that meet the accuracy conditions to be used in solar tracking systems and their evaluation or, as a tracking and orientation tool, on photovoltaic installations and solar collectors. PMID:28758935

Natural locomotion based on a reduced set of inertial sensors: Decoupling body and head directions indoors

PubMed Central

Diaz-Estrella, Antonio; Reyes-Lecuona, Arcadio; Langley, Alyson; Brown, Michael; Sharples, Sarah

2018-01-01

Inertial sensors offer the potential for integration into wireless virtual reality systems that allow the users to walk freely through virtual environments. However, owing to drift errors, inertial sensors cannot accurately estimate head and body orientations in the long run, and when walking indoors, this error cannot be corrected by magnetometers, due to the magnetic field distortion created by ferromagnetic materials present in buildings. This paper proposes a technique, called EHBD (Equalization of Head and Body Directions), to address this problem using two head- and shoulder-located magnetometers. Due to their proximity, their distortions are assumed to be similar and the magnetometer measurements are used to detect when the user is looking straight forward. Then, the system corrects the discrepancies between the estimated directions of the head and the shoulder, which are provided by gyroscopes and consequently are affected by drift errors. An experiment is conducted to evaluate the performance of this technique in two tasks (navigation and navigation plus exploration) and using two different locomotion techniques: (1) gaze-directed mode (GD) in which the walking direction is forced to be the same as the head direction, and (2) decoupled direction mode (DD) in which the walking direction can be different from the viewing direction. The obtained results show that both locomotion modes show similar matching of the target path during the navigation task, while DD’s path matches the target path more closely than GD in the navigation plus exploration task. These results validate the EHBD technique especially when allowing different walking and viewing directions in the navigation plus exploration tasks, as expected. While the proposed method does not reach the accuracy of optical tracking (ideal case), it is an acceptable and satisfactory solution for users and is much more compact, portable and economical. PMID:29621298

Evaluation of Smartphone Inertial Sensor Performance for Cross-Platform Mobile Applications

PubMed Central

Kos, Anton; Tomažič, Sašo; Umek, Anton

2016-01-01

Smartphone sensors are being increasingly used in mobile applications. The performance of sensors varies considerably among different smartphone models and the development of a cross-platform mobile application might be a very complex and demanding task. A publicly accessible resource containing real-life-situation smartphone sensor parameters could be of great help for cross-platform developers. To address this issue we have designed and implemented a pilot participatory sensing application for measuring, gathering, and analyzing smartphone sensor parameters. We start with smartphone accelerometer and gyroscope bias and noise parameters. The application database presently includes sensor parameters of more than 60 different smartphone models of different platforms. It is a modest, but important start, offering information on several statistical parameters of the measured smartphone sensors and insights into their performance. The next step, a large-scale cloud-based version of the application, is already planned. The large database of smartphone sensor parameters may prove particularly useful for cross-platform developers. It may also be interesting for individual participants who would be able to check-up and compare their smartphone sensors against a large number of similar or identical models. PMID:27049391

Assessment of modern smartphone sensors performance on vehicle localization in urban environments

NASA Astrophysics Data System (ADS)

Lazarou, Theodoros; Danezis, Chris

2017-09-01

The advent of Global Navigation Satellite Systems (GNSS) initiated a revolution in Positioning, Navigation and Timing (PNT) applications. Besides the enormous impact on geospatial data acquisition and reality capture, satellite navigation has penetrated everyday life, a fact which is proved by the increasing degree of human reliance on GNSS-enabled smart devices to perform casual activities. Nevertheless, GNSS does not perform well in all cases. Specifically, in GNSS-challenging environments, such as urban canyons or forested areas, navigation performance may be significantly degraded or even nullified. Consequently, positioning is achieved by combining GNSS with additional heterogeneous information or sensors, such as inertial sensors. To date, most smartphones are equipped with at least accelerometers and gyroscopes, besides GNSS chipsets. In the frame of this research, difficult localization scenarios were investigated to assess the performance of these low-cost inertial sensors with respect to higher grade GNSS and IMU systems. Four state-of-the-art smartphones were mounted on a specifically designed on-purpose build platform along with reference equipment. The platform was installed on top of a vehicle, which was driven by a predefined trajectory that included several GNSS-challenging parts. Consequently, positioning and inertial readings were acquired by smartphones and compared to the information collected by the reference equipment. The results indicated that although the smartphone GNSS receivers have increased sensitivity, they were unable to produce an acceptable solution for more than 30% of the driven course. However, all smartphones managed to identify, up to a satisfactory degree, distinct driving features, such as curves or bumps.

Assessing locomotor skills development in childhood using wearable inertial sensor devices: the running paradigm.

PubMed

Masci, Ilaria; Vannozzi, Giuseppe; Bergamini, Elena; Pesce, Caterina; Getchell, Nancy; Cappozzo, Aurelio

2013-04-01

Objective quantitative evaluation of motor skill development is of increasing importance to carefully drive physical exercise programs in childhood. Running is a fundamental motor skill humans adopt to accomplish locomotion, which is linked to physical activity levels, although the assessment is traditionally carried out using qualitative evaluation tests. The present study aimed at investigating the feasibility of using inertial sensors to quantify developmental differences in the running pattern of young children. Qualitative and quantitative assessment tools were adopted to identify a skill-sensitive set of biomechanical parameters for running and to further our understanding of the factors that determine progression to skilled running performance. Running performances of 54 children between the ages of 2 and 12 years were submitted to both qualitative and quantitative analysis, the former using sequences of developmental level, the latter estimating temporal and kinematic parameters from inertial sensor measurements. Discriminant analysis with running developmental level as dependent variable allowed to identify a set of temporal and kinematic parameters, within those obtained with the sensor, that best classified children into the qualitative developmental levels (accuracy higher than 67%). Multivariate analysis of variance with the quantitative parameters as dependent variables allowed to identify whether and which specific parameters or parameter subsets were differentially sensitive to specific transitions between contiguous developmental levels. The findings showed that different sets of temporal and kinematic parameters are able to tap all steps of the transitional process in running skill described through qualitative observation and can be prospectively used for applied diagnostic and sport training purposes. Copyright © 2012 Elsevier B.V. All rights reserved.

A Robust Self-Alignment Method for Ship's Strapdown INS Under Mooring Conditions

PubMed Central

Sun, Feng; Lan, Haiyu; Yu, Chunyang; El-Sheimy, Naser; Zhou, Guangtao; Cao, Tong; Liu, Hang

2013-01-01

Strapdown inertial navigation systems (INS) need an alignment process to determine the initial attitude matrix between the body frame and the navigation frame. The conventional alignment process is to compute the initial attitude matrix using the gravity and Earth rotational rate measurements. However, under mooring conditions, the inertial measurement unit (IMU) employed in a ship's strapdown INS often suffers from both the intrinsic sensor noise components and the external disturbance components caused by the motions of the sea waves and wind waves, so a rapid and precise alignment of a ship's strapdown INS without any auxiliary information is hard to achieve. A robust solution is given in this paper to solve this problem. The inertial frame based alignment method is utilized to adapt the mooring condition, most of the periodical low-frequency external disturbance components could be removed by the mathematical integration and averaging characteristic of this method. A novel prefilter named hidden Markov model based Kalman filter (HMM-KF) is proposed to remove the relatively high-frequency error components. Different from the digital filters, the HMM-KF barely cause time-delay problem. The turntable, mooring and sea experiments favorably validate the rapidness and accuracy of the proposed self-alignment method and the good de-noising performance of HMM-KF. PMID:23799492

Impact Assessment of GNSS Spoofing Attacks on INS/GNSS Integrated Navigation System.

PubMed

Liu, Yang; Li, Sihai; Fu, Qiangwen; Liu, Zhenbo

2018-05-04

In the face of emerging Global Navigation Satellite System (GNSS) spoofing attacks, there is a need to give a comprehensive analysis on how the inertial navigation system (INS)/GNSS integrated navigation system responds to different kinds of spoofing attacks. A better understanding of the integrated navigation system’s behavior with spoofed GNSS measurements gives us valuable clues to develop effective spoofing defenses. This paper focuses on an impact assessment of GNSS spoofing attacks on the integrated navigation system Kalman filter’s error covariance, innovation sequence and inertial sensor bias estimation. A simple and straightforward measurement-level trajectory spoofing simulation framework is presented, serving as the basis for an impact assessment of both unsynchronized and synchronized spoofing attacks. Recommendations are given for spoofing detection and mitigation based on our findings in the impact assessment process.

Loose and Tight GNSS/INS Integrations: Comparison of Performance Assessed in Real Urban Scenarios.

PubMed

Falco, Gianluca; Pini, Marco; Marucco, Gianluca

2017-01-29

Global Navigation Satellite Systems (GNSSs) remain the principal mean of positioning in many applications and systems, but in several types of environment, the performance of standalone receivers is degraded. Although many works show the benefits of the integration between GNSS and Inertial Navigation Systems (INSs), tightly-coupled architectures are mainly implemented in professional devices and are based on high-grade Inertial Measurement Units (IMUs). This paper investigates the performance improvements enabled by the tight integration, using low-cost sensors and a mass-market GNSS receiver. Performance is assessed through a series of tests carried out in real urban scenarios and is compared against commercial modules, operating in standalone mode or featuring loosely-coupled integrations. The paper describes the developed tight-integration algorithms with a terse mathematical model and assesses their efficacy from a practical perspective.

Analysis of several methods and inertial sensors locations to assess gait parameters in able-bodied subjects.

PubMed

Ben Mansour, Khaireddine; Rezzoug, Nasser; Gorce, Philippe

2015-10-01

The purpose of this paper was to determine which types of inertial sensors and which advocated locations should be used for reliable and accurate gait event detection and temporal parameter assessment in normal adults. In addition, we aimed to remove the ambiguity found in the literature of the definition of the initial contact (IC) from the lumbar accelerometer. Acceleration and angular velocity data was gathered from the lumbar region and the distal edge of each shank. This data was evaluated in comparison to an instrumented treadmill and an optoelectronic system during five treadmill speed sessions. The lumbar accelerometer showed that the peak of the anteroposterior component was the most accurate for IC detection. Similarly, the valley that followed the peak of the vertical component was the most precise for terminal contact (TC) detection. Results based on ANOVA and Tukey tests showed that the set of inertial methods was suitable for temporal gait assessment and gait event detection in able-bodied subjects. For gait event detection, an exception was found with the shank accelerometer. The tool was suitable for temporal parameters assessment, despite the high root mean square error on the detection of IC (RMSEIC) and TC (RMSETC). The shank gyroscope was found to be as accurate as the kinematic method since the statistical tests revealed no significant difference between the two techniques for the RMSE off all gait events and temporal parameters. The lumbar and shank accelerometers were the most accurate alternative to the shank gyroscope for gait event detection and temporal parameters assessment, respectively. Copyright © 2015. Published by Elsevier B.V.

A Motion Tracking and Sensor Fusion Module for Medical Simulation.

PubMed

Shen, Yunhe; Wu, Fan; Tseng, Kuo-Shih; Ye, Ding; Raymond, John; Konety, Badrinath; Sweet, Robert

2016-01-01

Here we introduce a motion tracking or navigation module for medical simulation systems. Our main contribution is a sensor fusion method for proximity or distance sensors integrated with inertial measurement unit (IMU). Since IMU rotation tracking has been widely studied, we focus on the position or trajectory tracking of the instrument moving freely within a given boundary. In our experiments, we have found that this module reliably tracks instrument motion.

Autonomous On-Board Calibration of Attitude Sensors and Gyros

NASA Technical Reports Server (NTRS)

Pittelkau, Mark E.

2007-01-01

This paper presents the state of the art and future prospects for autonomous real-time on-orbit calibration of gyros and attitude sensors. The current practice in ground-based calibration is presented briefly to contrast it with on-orbit calibration. The technical and economic benefits of on-orbit calibration are discussed. Various algorithms for on-orbit calibration are evaluated, including some that are already operating on board spacecraft. Because Redundant Inertial Measurement Units (RIMUs, which are IMUs that have more than three sense axes) are almost ubiquitous on spacecraft, special attention will be given to calibration of RIMUs. In addition, we discuss autonomous on board calibration and how it may be implemented.

Localization Using Visual Odometry and a Single Downward-Pointing Camera

NASA Technical Reports Server (NTRS)

Swank, Aaron J.

2012-01-01

Stereo imaging is a technique commonly employed for vision-based navigation. For such applications, two images are acquired from different vantage points and then compared using transformations to extract depth information. The technique is commonly used in robotics for obstacle avoidance or for Simultaneous Localization And Mapping, (SLAM). Yet, the process requires a number of image processing steps and therefore tends to be CPU-intensive, which limits the real-time data rate and use in power-limited applications. Evaluated here is a technique where a monocular camera is used for vision-based odometry. In this work, an optical flow technique with feature recognition is performed to generate odometry measurements. The visual odometry sensor measurements are intended to be used as control inputs or measurements in a sensor fusion algorithm using low-cost MEMS based inertial sensors to provide improved localization information. Presented here are visual odometry results which demonstrate the challenges associated with using ground-pointing cameras for visual odometry. The focus is for rover-based robotic applications for localization within GPS-denied environments.

Online Phase Detection Using Wearable Sensors for Walking with a Robotic Prosthesis

PubMed Central

Goršič, Maja; Kamnik, Roman; Ambrožič, Luka; Vitiello, Nicola; Lefeber, Dirk; Pasquini, Guido; Munih, Marko

2014-01-01

This paper presents a gait phase detection algorithm for providing feedback in walking with a robotic prosthesis. The algorithm utilizes the output signals of a wearable wireless sensory system incorporating sensorized shoe insoles and inertial measurement units attached to body segments. The principle of detecting transitions between gait phases is based on heuristic threshold rules, dividing a steady-state walking stride into four phases. For the evaluation of the algorithm, experiments with three amputees, walking with the robotic prosthesis and wearable sensors, were performed. Results show a high rate of successful detection for all four phases (the average success rate across all subjects >90%). A comparison of the proposed method to an off-line trained algorithm using hidden Markov models reveals a similar performance achieved without the need for learning dataset acquisition and previous model training. PMID:24521944

Human-motion energy harvester for autonomous body area sensors

NASA Astrophysics Data System (ADS)

Geisler, M.; Boisseau, S.; Perez, M.; Gasnier, P.; Willemin, J.; Ait-Ali, I.; Perraud, S.

2017-03-01

This paper reports on a method to optimize an electromagnetic energy harvester converting the low-frequency body motion and aimed at powering wireless body area sensors. This method is based on recorded accelerations, and mechanical and transduction models that enable an efficient joint optimization of the structural parameters. An optimized prototype of 14.8 mmØ × 52 mm, weighting 20 g, has generated up to 4.95 mW in a resistive load when worn at the arm during a run, and 6.57 mW when hand-shaken. Among the inertial electromagnetic energy harvesters reported so far, this one exhibits one of the highest power densities (up to 730 μW cm-3). The energy harvester was finally used to power a bluetooth low energy wireless sensor node with accelerations measurements at 25 Hz.

LISA pathfinder optical interferometry

NASA Astrophysics Data System (ADS)

Braxmaier, Claus; Heinzel, Gerhard; Middleton, Kevin F.; Caldwell, Martin E.; Konrad, W.; Stockburger, H.; Lucarelli, S.; te Plate, Maurice B.; Wand, V.; Garcia, A. C.; Draaisma, F.; Pijnenburg, J.; Robertson, D. I.; Killow, Christian; Ward, Harry; Danzmann, Karsten; Johann, Ulrich A.

2004-09-01

The LISA Technology Package (LTP) aboard of LISA pathfinder mission is dedicated to demonstrate and verify key technologies for LISA, in particular drag free control, ultra-precise laser interferometry and gravitational sensor. Two inertial sensor, the optical interferometry in between combined with the dimensional stable Glass ceramic Zerodur structure are setting up the LTP. The validation of drag free operation of the spacecraft is planned by measuring laser interferometrically the relative displacement and tilt between two test masses (and the optical bench) with a noise levels of 10pm/√Hz and 10 nrad/√Hz between 3mHz and 30mHz. This performance and additionally overall environmental tests was currently verified on EM level. The OB structure is able to support two inertial sensors (≍17kg each) and to withstand 25 g design loads as well as 0...40°C temperature range. Optical functionality was verified successfully after environmental tests. The engineering model development and manufacturing of the optical bench and interferometry hardware and their verification tests will be presented.

Failure detection and isolation investigation for strapdown skew redundant tetrad laser gyro inertial sensor arrays

NASA Technical Reports Server (NTRS)

Eberlein, A. J.; Lahm, T. G.

1976-01-01

The degree to which flight-critical failures in a strapdown laser gyro tetrad sensor assembly can be isolated in short-haul aircraft after a failure occurrence has been detected by the skewed sensor failure-detection voting logic is investigated along with the degree to which a failure in the tetrad computer can be detected and isolated at the computer level, assuming a dual-redundant computer configuration. The tetrad system was mechanized with two two-axis inertial navigation channels (INCs), each containing two gyro/accelerometer axes, computer, control circuitry, and input/output circuitry. Gyro/accelerometer data is crossfed between the two INCs to enable each computer to independently perform the navigation task. Computer calculations are synchronized between the computers so that calculated quantities are identical and may be compared. Fail-safe performance (identification of the first failure) is accomplished with a probability approaching 100 percent of the time, while fail-operational performance (identification and isolation of the first failure) is achieved 93 to 96 percent of the time.

Autonomous Flight Safety System - Phase III

NASA Technical Reports Server (NTRS)

2008-01-01

The Autonomous Flight Safety System (AFSS) is a joint KSC and Wallops Flight Facility project that uses tracking and attitude data from onboard Global Positioning System (GPS) and inertial measurement unit (IMU) sensors and configurable rule-based algorithms to make flight termination decisions. AFSS objectives are to increase launch capabilities by permitting launches from locations without range safety infrastructure, reduce costs by eliminating some downrange tracking and communication assets, and reduce the reaction time for flight termination decisions.

Two-Dimensional Stochastic Projections for Tight Integration of Optical and Inertial Sensors for Navigation

DTIC Science & Technology

2007-01-01

Intelligent Robots and Systems, vol- ume 1, pp. 123–128, September 2002. [2] R. G. Brown and P. Y. Hwang . Introduction to Ran- dom Signals and Applied... Kalman Filter-based) method for calculat- ing a trajectory by tracking features at an unknown location on the Earth’s surface, provided the topography...Extended Kalman Filter (EKF) and an automatic target tracking algorithm. In the following section, the integration architecture is presented, which in

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.

Gain-Scheduled Complementary Filter Design for a MEMS Based Attitude and Heading Reference System

PubMed Central

Yoo, Tae Suk; Hong, Sung Kyung; Yoon, Hyok Min; Park, Sungsu

2011-01-01

This paper describes a robust and simple algorithm for an attitude and heading reference system (AHRS) based on low-cost MEMS inertial and magnetic sensors. The proposed approach relies on a gain-scheduled complementary filter, augmented by an acceleration-based switching architecture to yield robust performance, even when the vehicle is subject to strong accelerations. Experimental results are provided for a road captive test during which the vehicle dynamics are in high-acceleration mode and the performance of the proposed filter is evaluated against the output from a conventional linear complementary filter. PMID:22163824

Ginger

NASA Astrophysics Data System (ADS)

di Virgilio, Angela D. V.

Gyroscopes IN General Relativity (GINGER) is a proposal of an Earth-base experiment to measure the Lense-Thirring effect. GINGER uses an array of ring lasers, which are the most sensitive inertial sensors to measure the rotation rate of the Earth. GINGER is based on a three-dimensional array of large size ring lasers, able to measure the de Sitter and Lense-Thirring effects. The instrument will be located in the INFN Gran Sasso underground laboratory, in Italy. We describe preliminary developments and measurements. Earlier prototypes based in Italy, GP2, GINGERino, and G-LAS are also described and their preliminary results reported.

A Short Tutorial on Inertial Navigation System and Global Positioning System Integration

NASA Technical Reports Server (NTRS)

Smalling, Kyle M.; Eure, Kenneth W.

2015-01-01

The purpose of this document is to describe a simple method of integrating Inertial Navigation System (INS) information with Global Positioning System (GPS) information for an improved estimate of vehicle attitude and position. A simple two dimensional (2D) case is considered. The attitude estimates are derived from sensor data and used in the estimation of vehicle position and velocity through dead reckoning within the INS. The INS estimates are updated with GPS estimates using a Kalman filter. This tutorial is intended for the novice user with a focus on bringing the reader from raw sensor measurements to an integrated position and attitude estimate. An application is given using a remotely controlled ground vehicle operating in assumed 2D environment. The theory is developed first followed by an illustrative example.

Local Observability Analysis of Star Sensor Installation Errors in a SINS/CNS Integration System for Near-Earth Flight Vehicles

PubMed Central

Yang, Yanqiang; Zhang, Chunxi; Lu, Jiazhen

2017-01-01

Strapdown inertial navigation system/celestial navigation system (SINS/CNS) integrated navigation is a fully autonomous and high precision method, which has been widely used to improve the hitting accuracy and quick reaction capability of near-Earth flight vehicles. The installation errors between SINS and star sensors have been one of the main factors that restrict the actual accuracy of SINS/CNS. In this paper, an integration algorithm based on the star vector observations is derived considering the star sensor installation error. Then, the star sensor installation error is accurately estimated based on Kalman Filtering (KF). Meanwhile, a local observability analysis is performed on the rank of observability matrix obtained via linearization observation equation, and the observable conditions are presented and validated. The number of star vectors should be greater than or equal to 2, and the times of posture adjustment also should be greater than or equal to 2. Simulations indicate that the star sensor installation error could be readily observable based on the maneuvering condition; moreover, the attitude errors of SINS are less than 7 arc-seconds. This analysis method and conclusion are useful in the ballistic trajectory design of near-Earth flight vehicles. PMID:28275211

Zero velocity interval detection based on a continuous hidden Markov model in micro inertial pedestrian navigation

NASA Astrophysics Data System (ADS)

Sun, Wei; Ding, Wei; Yan, Huifang; Duan, Shunli

2018-06-01

Shoe-mounted pedestrian navigation systems based on micro inertial sensors rely on zero velocity updates to correct their positioning errors in time, which effectively makes determining the zero velocity interval play a key role during normal walking. However, as walking gaits are complicated, and vary from person to person, it is difficult to detect walking gaits with a fixed threshold method. This paper proposes a pedestrian gait classification method based on a hidden Markov model. Pedestrian gait data are collected with a micro inertial measurement unit installed at the instep. On the basis of analyzing the characteristics of the pedestrian walk, a single direction angular rate gyro output is used to classify gait features. The angular rate data are modeled into a univariate Gaussian mixture model with three components, and a four-state left–right continuous hidden Markov model (CHMM) is designed to classify the normal walking gait. The model parameters are trained and optimized using the Baum–Welch algorithm and then the sliding window Viterbi algorithm is used to decode the gait. Walking data are collected through eight subjects walking along the same route at three different speeds; the leave-one-subject-out cross validation method is conducted to test the model. Experimental results show that the proposed algorithm can accurately detect different walking gaits of zero velocity interval. The location experiment shows that the precision of CHMM-based pedestrian navigation improved by 40% when compared to the angular rate threshold method.

Measuring Gait Quality in Parkinson’s Disease through Real-Time Gait Phase Recognition

PubMed Central

Mileti, Ilaria; Germanotta, Marco; Di Sipio, Enrica; Imbimbo, Isabella; Pacilli, Alessandra; Erra, Carmen; Petracca, Martina; Del Prete, Zaccaria; Bentivoglio, Anna Rita; Padua, Luca

2018-01-01

Monitoring gait quality in daily activities through wearable sensors has the potential to improve medical assessment in Parkinson’s Disease (PD). In this study, four gait partitioning methods, two based on thresholds and two based on a machine learning approach, considering the four-phase model, were compared. The methods were tested on 26 PD patients, both in OFF and ON levodopa conditions, and 11 healthy subjects, during walking tasks. All subjects were equipped with inertial sensors placed on feet. Force resistive sensors were used to assess reference time sequence of gait phases. Goodness Index (G) was evaluated to assess accuracy in gait phases estimation. A novel synthetic index called Gait Phase Quality Index (GPQI) was proposed for gait quality assessment. Results revealed optimum performance (G < 0.25) for three tested methods and good performance (0.25 < G < 0.70) for one threshold method. The GPQI resulted significantly higher in PD patients than in healthy subjects, showing a moderate correlation with clinical scales score. Furthermore, in patients with severe gait impairment, GPQI was found higher in OFF than in ON state. Our results unveil the possibility of monitoring gait quality in PD through real-time gait partitioning based on wearable sensors. PMID:29558410

Fast Markerless Tracking for Augmented Reality in Planar Environment

NASA Astrophysics Data System (ADS)

Basori, Ahmad Hoirul; Afif, Fadhil Noer; Almazyad, Abdulaziz S.; AbuJabal, Hamza Ali S.; Rehman, Amjad; Alkawaz, Mohammed Hazim

2015-12-01

Markerless tracking for augmented reality should not only be accurate but also fast enough to provide a seamless synchronization between real and virtual beings. Current reported methods showed that a vision-based tracking is accurate but requires high computational power. This paper proposes a real-time hybrid-based method for tracking unknown environments in markerless augmented reality. The proposed method provides collaboration of vision-based approach with accelerometers and gyroscopes sensors as camera pose predictor. To align the augmentation relative to camera motion, the tracking method is done by substituting feature-based camera estimation with combination of inertial sensors with complementary filter to provide more dynamic response. The proposed method managed to track unknown environment with faster processing time compared to available feature-based approaches. Moreover, the proposed method can sustain its estimation in a situation where feature-based tracking loses its track. The collaboration of sensor tracking managed to perform the task for about 22.97 FPS, up to five times faster than feature-based tracking method used as comparison. Therefore, the proposed method can be used to track unknown environments without depending on amount of features on scene, while requiring lower computational cost.

Effect of control surface mass unbalance on the stability of a closed-loop active control system

NASA Technical Reports Server (NTRS)

Nissim, E.

1989-01-01

The effects on stability of inertial forces arising from closed-loop activation of mass-unbalanced control surfaces are studied analytically using inertial energy approach, similar to the aerodynamic energy approach used for flutter suppression. The limitations of a single control surface like a leading-edge (LE) control or a trailing-edge (TE) control are demonstrated and compared to the superior combined LE-TE mass unbalanced system. It is shown that a spanwise section for sensor location can be determined which ensures minimum sensitivity to the mode shapes of the aircraft. It is shown that an LE control exhibits compatibility between inertial stabilization and aerodynamic stabilization, and that a TE control lacks such compatibility. The results of the present work should prove valuable, both for the purpose of flutter suppression using mass unbalanced control surfaces, or for the stabilization of structural modes of large space structures by means of inertial forces.

Inflight redesign of the IUE attitude control system

NASA Technical Reports Server (NTRS)

Femiano, M. D.

1986-01-01

The one- and two-gyro system designs of the International Ultraviolet Explorer (IUE) attitude control system (ACS) are examined. The inertial reference assembly that provides the primary attitude reference for IUE consists of six rate sensors which are single-axis rate integrating gyros. The gyros operate in a pulse rebalanced mode that produces an output pulse for 0.01 arcsec of motion about the input axis. The functions of the fine error sensor, fine sun sensor (FSS), the IUE reaction wheels, the onboard computer, and the hold/slew algorithm are described. The use of the hold/slew algorithm to compute the control voltage for the ACS based on the Kalman filter is studied. A two-gyro system was incorporated into IUE following gyro failure. The procedures for establishing attitude control with the two-gyro design based on the FSS is analyzed. The performance of the two-gyro system is evaluated; it is observed that the pitch and yaw gyro control is 0.24 arcsec and the control is sufficient to permit extended periods of observation.

Orion MPCV GN and C End-to-End Phasing Tests

NASA Technical Reports Server (NTRS)

Neumann, Brian C.

2013-01-01

End-to-end integration tests are critical risk reduction efforts for any complex vehicle. Phasing tests are an end-to-end integrated test that validates system directional phasing (polarity) from sensor measurement through software algorithms to end effector response. Phasing tests are typically performed on a fully integrated and assembled flight vehicle where sensors are stimulated by moving the vehicle and the effectors are observed for proper polarity. Orion Multi-Purpose Crew Vehicle (MPCV) Pad Abort 1 (PA-1) Phasing Test was conducted from inertial measurement to Launch Abort System (LAS). Orion Exploration Flight Test 1 (EFT-1) has two end-to-end phasing tests planned. The first test from inertial measurement to Crew Module (CM) reaction control system thrusters uses navigation and flight control system software algorithms to process commands. The second test from inertial measurement to CM S-Band Phased Array Antenna (PAA) uses navigation and communication system software algorithms to process commands. Future Orion flights include Ascent Abort Flight Test 2 (AA-2) and Exploration Mission 1 (EM-1). These flights will include additional or updated sensors, software algorithms and effectors. This paper will explore the implementation of end-to-end phasing tests on a flight vehicle which has many constraints, trade-offs and compromises. Orion PA-1 Phasing Test was conducted at White Sands Missile Range (WSMR) from March 4-6, 2010. This test decreased the risk of mission failure by demonstrating proper flight control system polarity. Demonstration was achieved by stimulating the primary navigation sensor, processing sensor data to commands and viewing propulsion response. PA-1 primary navigation sensor was a Space Integrated Inertial Navigation System (INS) and Global Positioning System (GPS) (SIGI) which has onboard processing, INS (3 accelerometers and 3 rate gyros) and no GPS receiver. SIGI data was processed by GN&C software into thrust magnitude and direction commands. The processing changes through three phases of powered flight: pitchover, downrange and reorientation. The primary inputs to GN&C are attitude position, attitude rates, angle of attack (AOA) and angle of sideslip (AOS). Pitch and yaw attitude and attitude rate responses were verified by using a flight spare SIGI mounted to a 2-axis rate table. AOA and AOS responses were verified by using a data recorded from SIGI movements on a robotic arm located at NASA Johnson Space Center. The data was consolidated and used in an open-loop data input to the SIGI. Propulsion was the Launch Abort System (LAS) Attitude Control Motor (ACM) which consisted of a solid motor with 8 nozzles. Each nozzle has active thrust control by varying throat area with a pintle. LAS ACM pintles are observable through optically transparent nozzle covers. SIGI movements on robot arm, SIGI rate table movements and LAS ACM pintle responses were video recorded as test artifacts for analysis and evaluation. The PA-1 Phasing Test design was determined based on test performance requirements, operational restrictions and EGSE capabilities. This development progressed during different stages. For convenience these development stages are initial, working group, tiger team, Engineering Review Team (ERT) and final.

Multifuctional integrated sensors (MFISES).

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

Homeijer, Brian D.; Roozeboom, Clifton

2015-10-01

Many emerging IoT applications require sensing of multiple physical and environmental parameters for: completeness of information, measurement validation, unexpected demands, improved performance. For example, a typical outdoor weather station measures temperature, humidity, barometric pressure, light intensity, rainfall, wind speed and direction. Existing sensor technologies do not directly address the demand for cost, size, and power reduction in multi-paramater sensing applications. Industry sensor manufacturers have developed integrated sensor systems for inertial measurements that combine accelerometers, gyroscopes, and magnetometers, but do not address environmental sensing functionality. In existing research literature, a technology gap exists between the functionality of MEMS sensors and themore » real world applications of the sensors systems.« less

Postural strategies assessed with inertial sensors in healthy and parkinsonian subjects

PubMed Central

Baston, Chiara; Mancini, Martina; Schoneburg, Bernadette; Horak, Fay; Rocchi, Laura

2015-01-01

The present study introduces a novel instrumented method to characterize postural movement strategies to maintain balance during stance (ankle and hip strategy), by means of inertial sensors, positioned on the legs and on the trunk. We evaluated postural strategies in subjects with2 types of parkinsonism: idiopathic Parkinson's disease (PD) and Progressive Supranuclear Palsy (PSP),and inage-matched control subjects standing under perturbed conditions implementedby the Sensory Organization Test (SOT).Coordination between the upper and lower segments of the body during postural sway was measured using a covariance index over time, by a sliding-window algorithm. Afterwards, a postural strategy index was computed. We also measuredthe amount of postural sway, as adjunctive information to characterize balance, by the root mean square of the horizontal trunk acceleration signal (RMS). Results showed that control subjects were able to change their postural strategy, whilst PSP and PD subjects persisted in use of an ankle strategy in all conditions.PD subjects had RMS values similar to control subjects even without changing postural strategy appropriately, whereas PSP subjects showed much larger RMS values than controls, resulting in several falls during the most challenging SOT conditions (5 and 6). Results are in accordance with the corresponding clinical literature describing postural behavior in the same kind of subjects. The proposed strategy index, based on the use ofinertial sensors on the upper and lower body segments, isa promising and unobtrusive toolto characterize postural strategies performed to attain balance. PMID:24656713

University of Florida Torsion Pendulum for Testing Key LISA Technology

NASA Astrophysics Data System (ADS)

Apple, Stephen; Chilton, Andrew; Olatunde, Taiwo Janet; Hillsberry, Daniel; Parry, Samantha; Ciani, Giacomo; Wass, Peter; Mueller, Guido; Conklin, John

2018-01-01

This presentation will describe the design and performance of a new torsion pendulum at the University of Florida used for testing inertial sensors and associated technologies for use in space – based gravitational wave observatories and geodesy missions. In particular this new torsion pendulum facility is testing inertial sensors and associated technology for the upcoming LISA (laser interferometer space antenna) space-based gravitational wave observatory mission. The torsion pendulum apparatus is comprised of a suspended cross bar assembly that has LISA test mass mockups at each of its ends. Two of the test mass mockups are enclosed by capacitive sensors which provide actuation and position sensing. The entire assembly is housed in a vacuum chamber. The pendulum cross-bar converts rotational motion of the test masses about the suspension fiber axis into translational motion. The 22 cm cross bar arm length along with the extremely small torsional spring constant of the suspension fiber results in a near free fall condition in the translational degree-of-freedom orthogonal to both the member and the suspension fiber. The test masses are electrically isolated from the pendulum assembly and their charge is controlled via photoemission using fiber coupled UV LEDS. Position of the test masses is measured using both capacitive and interferometric readout. The broadband sensitivity of the capacitive readout and laser interferometer readout is 30 nm/√Hz and 0.5 nm/√Hz respectively. The performance of the pendulum measured in equivalent acceleration noise acting on a LISA test mass is approximately 3 × 10-13 ms-2/√Hz at 2 mHz. This presentation will also discuss the design and fabrication of a flight-like gravitational reference sensor that will soon be integrated into the torsion pendulum facility. This flight-like GRS will allow for noise performance measurements in a more LISA-like configuration.

Ambulatory measurement of the scapulohumeral rhythm: intra- and inter-operator agreement of a protocol based on inertial and magnetic sensors.

PubMed

Parel, I; Cutti, A G; Fiumana, G; Porcellini, G; Verni, G; Accardo, A P

2012-04-01

To measure the scapulohumeral rhythm (SHR) in outpatient settings, the motion analysis protocol named ISEO (INAIL Shoulder and Elbow Outpatient protocol) was developed, based on inertial and magnetic sensors. To complete the sensor-to-segment calibration, ISEO requires the involvement of an operator for sensor placement and for positioning the patient's arm in a predefined posture. Since this can affect the measure, this study aimed at quantifying ISEO intra- and inter-operator agreement. Forty subjects were considered, together with two operators, A and B. Three measurement sessions were completed for each subject: two by A and one by B. In each session, the humerus and scapula rotations were measured during sagittal and scapular plane elevation movements. ISEO intra- and inter-operator agreement were assessed by computing, between sessions, the: (1) similarity of the scapulohumeral patterns through the Coefficient of Multiple Correlation (CMC(2)), both considering and excluding the difference of the initial value of the scapula rotations between two sessions (inter-session offset); (2) 95% Smallest Detectable Difference (SDD(95)) in scapula range of motion. Results for CMC(2) showed that the intra- and inter-operator agreement is acceptable (median≥0.85, lower-whisker ≥ 0.75) for most of the scapula rotations, independently from the movement and the inter-session offset. The only exception is the agreement for scapula protraction-retraction and for scapula medio-lateral rotation during abduction (inter-operator), which is acceptable only if the inter-session offset is removed. SDD(95) values ranged from 4.4° to 8.6° for the inter-operator and between 4.9° and 8.5° for the intra-operator agreement. In conclusion, ISEO presents a high intra- and inter-operator agreement, particularly with the scapula inter-session offset removed. Copyright © 2011 Elsevier B.V. All rights reserved.

Feature extraction of performance variables in elite half-pipe snowboarding using body mounted inertial sensors

NASA Astrophysics Data System (ADS)

Harding, J. W.; Small, J. W.; James, D. A.

2007-12-01

Recent analysis of elite-level half-pipe snowboard competition has revealed a number of sport specific key performance variables (KPV's) that correlate well to score. Information on these variables is difficult to acquire and analyse, relying on collection and labour intensive manual post processing of video data. This paper presents the use of inertial sensors as a user-friendly alternative and subsequently implements signal processing routines to ultimately provide automated, sport specific feedback to coaches and athletes. The author has recently shown that the key performance variables (KPV's) of total air-time (TAT) and average degree of rotation (ADR) achieved during elite half-pipe snowboarding competition show strong correlation with an athlete's subjectively judged score. Utilising Micro-Electrochemical System (MEMS) sensors (tri-axial accelerometers) this paper demonstrates that air-time (AT) achieved during half-pipe snowboarding can be detected and calculated accurately using basic signal processing techniques. Characterisation of the variations in aerial acrobatic manoeuvres and the associated calculation of exact degree of rotation (DR) achieved is a likely extension of this research. The technique developed used a two-pass method to detect locations of half-pipe snowboard runs using power density in the frequency domain and subsequently utilises a threshold based search algorithm in the time domain to calculate air-times associated with individual aerial acrobatic manoeuvres. This technique correctly identified the air-times of 100 percent of aerial acrobatic manoeuvres within each half-pipe snowboarding run (n = 92 aerial acrobatic manoeuvres from 4 subjects) and displayed a very strong correlation with a video based reference standard for air-time calculation (r = 0.78 +/- 0.08; p value < 0.0001; SEE = 0.08 ×/÷ 1.16; mean bias = -0.03 +/- 0.02s) (value +/- or ×/÷ 95% CL).

Underground atom gradiometer array for mass distribution monitoring and advanced geodesy

NASA Astrophysics Data System (ADS)

Canuel, B.

2015-12-01

After more than 20 years of fundamental research, atom interferometers have reached sensitivity and accuracy levels competing with or beating inertial sensors based on different technologies. Atom interferometers offer interesting applications in geophysics (gravimetry, gradiometry, Earth rotation rate measurements), inertial sensing (submarine or aircraft autonomous positioning), metrology (new definition of the kilogram) and fundamental physics (tests of the standard model, tests of general relativity). Atom interferometers already contributed significantly to fundamental physics by, for example, providing stringent constraints on quantum-electrodynamics through measurements of the hyperfine structure constant, testing the Equivalence Principle with cold atoms, or providing new measurements for the Newtonian gravitational constant. Cold atom sensors have moreover been established as key instruments in metrology for the new definition of the kilogram or through international comparisons of gravimeters. The field of atom interferometry (AI) is now entering a new phase where very high sensitivity levels must be demonstrated, in order to enlarge the potential applications outside atomic physics laboratories. These applications range from gravitational wave (GW) detection in the [0.1-10 Hz] frequency band to next generation ground and space-based Earth gravity field studies to precision gyroscopes and accelerometers. The Matter-wave laser Interferometric Gravitation Antenna (MIGA) presented here is a large-scale matter-wave sensor which will open new applications in geoscience and fundamental physics. The MIGA consortium gathers 18 expert French laboratories and companies in atomic physics, metrology, optics, geosciences and gravitational physics, with the aim to build a large-scale underground atom-interferometer instrument by 2018 and operate it till at least 2023. In this paper, we present the main objectives of the project, the status of the construction of the instrument and the motivation for the applications of MIGA in geosciences

Acute Sport-Related Concussion Screening for Collegiate Athletes Using an Instrumented Balance Assessment.

PubMed

Baracks, Joshua; Casa, Douglas J; Covassin, Tracey; Sacko, Ryan; Scarneo, Samantha E; Schnyer, David; Yeargin, Susan W; Neville, Christopher

2018-06-13

  Without a true criterion standard assessment, the sport-related concussion (SRC) diagnosis remains subjective. Inertial balance sensors have been proposed to improve acute SRC assessment, but few researchers have studied their clinical utility.   To determine if group differences exist when using objective measures of balance in a sample of collegiate athletes with recent SRCs and participants serving as the control group and to calculate sensitivity and specificity to determine the diagnostic utility of the inertial balance sensor for acute SRC injuries.   Cohort study.   Multicenter clinical trial.   We enrolled 48 participants with SRC (age = 20.62 ± 1.52 years, height = 179.76 ± 10.00 cm, mass = 83.92 ± 23.22 kg) and 45 control participants (age = 20.85 ± 1.42 years, height = 177.02 ± 9.59 cm, mass = 74.61 ± 14.92 kg) at 7 clinical sites in the United States. All were varsity or club collegiate athletes, and all participants with SRC were tested within 72 hours of SRC.   Balance performance was assessed using an inertial balance sensor. Two measures (root mean square [RMS] sway and 95% ellipse sway area) were analyzed to represent a range of general balance measures. Balance assessments were conducted in double-legged, single-legged, and tandem stances.   A main effect for group was associated with the root mean square sway measure ( F 1,91 = 11.75, P = .001), with the SRC group demonstrating balance deficits compared with the control group. We observed group differences in the 95% ellipse sway area measure for the double-legged ( F 1,91 = 11.59, P = .001), single-legged ( F 1,91 = 6.91, P = .01), and tandem ( F 1,91 = 7.54, P = .007) stances. Sensitivity was greatest using a cutoff value of 0.5 standard deviations (54% [specificity = 71%]), whereas specificity was greatest using a cutoff value of 2 standard deviations (98% [sensitivity = 33%]).   Inertial balance sensors may be useful tools for objectively measuring balance during acute SRC evaluation. However, low sensitivity suggests that they may be best used in conjunction with other assessments to form a comprehensive screening that may improve sensitivity.

A Coarse-Alignment Method Based on the Optimal-REQUEST Algorithm

PubMed Central

Zhu, Yongyun

2018-01-01

In this paper, we proposed a coarse-alignment method for strapdown inertial navigation systems based on attitude determination. The observation vectors, which can be obtained by inertial sensors, usually contain various types of noise, which affects the convergence rate and the accuracy of the coarse alignment. Given this drawback, we studied an attitude-determination method named optimal-REQUEST, which is an optimal method for attitude determination that is based on observation vectors. Compared to the traditional attitude-determination method, the filtering gain of the proposed method is tuned autonomously; thus, the convergence rate of the attitude determination is faster than in the traditional method. Within the proposed method, we developed an iterative method for determining the attitude quaternion. We carried out simulation and turntable tests, which we used to validate the proposed method’s performance. The experiment’s results showed that the convergence rate of the proposed optimal-REQUEST algorithm is faster and that the coarse alignment’s stability is higher. In summary, the proposed method has a high applicability to practical systems. PMID:29337895

Marker-Based Multi-Sensor Fusion Indoor Localization System for Micro Air Vehicles.

PubMed

Xing, Boyang; Zhu, Quanmin; Pan, Feng; Feng, Xiaoxue

2018-05-25

A novel multi-sensor fusion indoor localization algorithm based on ArUco marker is designed in this paper. The proposed ArUco mapping algorithm can build and correct the map of markers online with Grubbs criterion and K-mean clustering, which avoids the map distortion due to lack of correction. Based on the conception of multi-sensor information fusion, the federated Kalman filter is utilized to synthesize the multi-source information from markers, optical flow, ultrasonic and the inertial sensor, which can obtain a continuous localization result and effectively reduce the position drift due to the long-term loss of markers in pure marker localization. The proposed algorithm can be easily implemented in a hardware of one Raspberry Pi Zero and two STM32 micro controllers produced by STMicroelectronics (Geneva, Switzerland). Thus, a small-size and low-cost marker-based localization system is presented. The experimental results show that the speed estimation result of the proposed system is better than Px4flow, and it has the centimeter accuracy of mapping and positioning. The presented system not only gives satisfying localization precision, but also has the potential to expand other sensors (such as visual odometry, ultra wideband (UWB) beacon and lidar) to further improve the localization performance. The proposed system can be reliably employed in Micro Aerial Vehicle (MAV) visual localization and robotics control.

Observing Migration and Burial of Unexploded Ordnance in the Nearshore Environment with Instrumented Surrogates

NASA Astrophysics Data System (ADS)

Bruder, B. L.; Cristaudo, D.; Puleo, J. A.

2016-12-01

Prior to 1972, it was legal and common practice to unload unexploded ordnance (UXO) into the ocean. Only 60-100 miles off the US coast alone there are 72 dumping sites where it is estimated 31 million pounds of UXO lie. As recently as 2015, UXO have been found not only in the nearshore environment, but on populated beaches. Thus, understanding the migration and burial of these objects is not only of oceanographic interest, but a matter of public safety. The presented project evaluates the efficacy of instrumented UXO surrogates for observing munition migration and burial. Instrumented surrogates were exposed to near prototype scale wave conditions over a mobile bed at the Littoral Warfare Environment at Aberdeen Test Center, MD. Surrogates were deployed in the swash zone, inner and outer surf zones. Dependent on munition size, surrogates housed multiple suites of self-logging sensors. Sensor suites included different combinations of inertial motion units, ultra-wideband tracking tags, pressure transducers, shock recorders, and photocells. Preliminary results show sensor suites can resolve various types of surrogate movement. Pressure transducers accurately record ambient wave conditions as well as changes in mean depth due to surrogate migration. Inertial motion units resolve munition accelerations for rolling and translational motion. Inertial motion unit data is used to estimate trajectory as well when coupled with mean depth and bathymetric data. Photocells, which measure ambient light, resolve munition burial as well as serve as proxies for surrounding environmental conditions such as suspended sediment and water depth. The presented project will continue to utilize and couple surrogate sensor data to resolve munition movement and burial under different conditions. Knowledge of munition migration helps focus UXO detection and recovery, conserving US military and coastal resources.

Development of a head impact monitoring "Intelligent Mouthguard".

PubMed

Hedin, Daniel S; Gibson, Paul L; Bartsch, Adam J; Samorezov, Sergey

2016-08-01

The authors present the development and laboratory system-level testing of an impact monitoring "Intelligent Mouthguard" intended to help with identification of potentially concussive head impacts and cumulative head impact dosage. The goal of Intelligent Mouthguard is to provide an indicator of potential concussion risk, and help caregiver identify athletes needing sideline concussion protocol testing. Intelligent Mouthguard may also help identify individuals who are at higher risk based on historical dosage. Intelligent Mouthguard integrates inertial sensors to provide 3-degree of freedom linear and rotational kinematics. The electronics are fully integrated into a custom mouthguard that couples tightly to the upper teeth. The combination of tight coupling and highly accurate sensor data means the Intelligent Mouthguard meets the National Football League (NFL) Level I validity specification based on laboratory system-level test data presented in this study.

Multiple nodes transfer alignment for airborne missiles based on inertial sensor network

NASA Astrophysics Data System (ADS)

Si, Fan; Zhao, Yan

2017-09-01

Transfer alignment is an important initialization method for airborne missiles because the alignment accuracy largely determines the performance of the missile. However, traditional alignment methods are limited by complicated and unknown flexure angle, and cannot meet the actual requirement when wing flexure deformation occurs. To address this problem, we propose a new method that uses the relative navigation parameters between the weapons and fighter to achieve transfer alignment. First, in the relative inertial navigation algorithm, the relative attitudes and positions are constantly computed in wing flexure deformation situations. Secondly, the alignment results of each weapon are processed using a data fusion algorithm to improve the overall performance. Finally, the feasibility and performance of the proposed method were evaluated under two typical types of deformation, and the simulation results demonstrated that the new transfer alignment method is practical and has high-precision.

A novel navigation method used in a ballistic missile

NASA Astrophysics Data System (ADS)

Qian, Hua-ming; Sun, Long; Cai, Jia-nan; Peng, Yu

2013-10-01

The traditional strapdown inertial/celestial integrated navigation method used in a ballistic missile cannot accurately estimate the accelerometer bias. It might cause a divergence of navigation errors. To solve this problem, a new navigation method named strapdown inertial/starlight refractive celestial integrated navigation is proposed. To verify the feasibility of the proposed method, a simulated program of a ballistic missile is presented. The simulation results indicated that, when multiple refraction stars are used, the proposed method can accurately estimate the accelerometer bias, and suppress the divergence of navigation errors completely. Specifically, in order to apply this method to a ballistic missile, a novel measurement equation based on stellar refraction was developed. Furthermore a method to calculate the number of refraction stars observed by the stellar sensor was given. Finally, the relationship between the number of refraction stars used and the navigation accuracy is analysed.

Filtering Methods for Error Reduction in Spacecraft Attitude Estimation Using Quaternion Star Trackers

NASA Technical Reports Server (NTRS)

Calhoun, Philip C.; Sedlak, Joseph E.; Superfin, Emil

2011-01-01

Precision attitude determination for recent and planned space missions typically includes quaternion star trackers (ST) and a three-axis inertial reference unit (IRU). Sensor selection is based on estimates of knowledge accuracy attainable from a Kalman filter (KF), which provides the optimal solution for the case of linear dynamics with measurement and process errors characterized by random Gaussian noise with white spectrum. Non-Gaussian systematic errors in quaternion STs are often quite large and have an unpredictable time-varying nature, particularly when used in non-inertial pointing applications. Two filtering methods are proposed to reduce the attitude estimation error resulting from ST systematic errors, 1) extended Kalman filter (EKF) augmented with Markov states, 2) Unscented Kalman filter (UKF) with a periodic measurement model. Realistic assessments of the attitude estimation performance gains are demonstrated with both simulation and flight telemetry data from the Lunar Reconnaissance Orbiter.

Wireless inertial measurement unit with GPS (WIMU-GPS)--wearable monitoring platform for ecological assessment of lifespace and mobility in aging and disease.

PubMed

Boissy, Patrick; Brière, Simon; Hamel, Mathieu; Jog, Mandar; Speechley, Mark; Karelis, Antony; Frank, James; Vincent, Claude; Edwards, Rodrick; Duval, Christian

2011-01-01

This paper proposes an innovative ambulatory mobility and activity monitoring approach based on a wearable datalogging platform that combines inertial sensing with GPS tracking to assess the lifespace and mobility profile of individuals in their home and community environments. The components, I/O architecture, sensors and functions of the WIMU-GPS are presented. Outcome variables that can be measured with it are described and illustrated. Data on the power usage, operating autonomy of the WIMU-GPS and the GPS tracking performances and time to first fix of the unit are presented. The study of lifespace and mobility with the WIMU-GPS can potentially provide unique insights into intrapersonal and environmental factors contributing to mobility restriction. On-going studies are underway to establish the validity and reliability of the WIMU-GPS in characterizing the lifespace and mobility profile of older adults.

A Sensor Fusion Method Based on an Integrated Neural Network and Kalman Filter for Vehicle Roll Angle Estimation.

PubMed

Vargas-Meléndez, Leandro; Boada, Beatriz L; Boada, María Jesús L; Gauchía, Antonio; Díaz, Vicente

2016-08-31

This article presents a novel estimator based on sensor fusion, which combines the Neural Network (NN) with a Kalman filter in order to estimate the vehicle roll angle. The NN estimates a "pseudo-roll angle" through variables that are easily measured from Inertial Measurement Unit (IMU) sensors. An IMU is a device that is commonly used for vehicle motion detection, and its cost has decreased during recent years. The pseudo-roll angle is introduced in the Kalman filter in order to filter noise and minimize the variance of the norm and maximum errors' estimation. The NN has been trained for J-turn maneuvers, double lane change maneuvers and lane change maneuvers at different speeds and road friction coefficients. The proposed method takes into account the vehicle non-linearities, thus yielding good roll angle estimation. Finally, the proposed estimator has been compared with one that uses the suspension deflections to obtain the pseudo-roll angle. Experimental results show the effectiveness of the proposed NN and Kalman filter-based estimator.

Attitude Control System Design for the Solar Dynamics Observatory

NASA Technical Reports Server (NTRS)

Starin, Scott R.; Bourkland, Kristin L.; Kuo-Chia, Liu; Mason, Paul A. C.; Vess, Melissa F.; Andrews, Stephen F.; Morgenstern, Wendy M.

2005-01-01

The Solar Dynamics Observatory mission, part of the Living With a Star program, will place a geosynchronous satellite in orbit to observe the Sun and relay data to a dedicated ground station at all times. SDO remains Sun- pointing throughout most of its mission for the instruments to take measurements of the Sun. The SDO attitude control system is a single-fault tolerant design. Its fully redundant attitude sensor complement includes 16 coarse Sun sensors, a digital Sun sensor, 3 two-axis inertial reference units, 2 star trackers, and 4 guide telescopes. Attitude actuation is performed using 4 reaction wheels and 8 thrusters, and a single main engine nominally provides velocity-change thrust. The attitude control software has five nominal control modes-3 wheel-based modes and 2 thruster-based modes. A wheel-based Safehold running in the attitude control electronics box improves the robustness of the system as a whole. All six modes are designed on the same basic proportional-integral-derivative attitude error structure, with more robust modes setting their integral gains to zero. The paper details the mode designs and their uses.

Optimization-Based Sensor Fusion of GNSS and IMU Using a Moving Horizon Approach

PubMed Central

Girrbach, Fabian; Hol, Jeroen D.; Bellusci, Giovanni; Diehl, Moritz

2017-01-01

The rise of autonomous systems operating close to humans imposes new challenges in terms of robustness and precision on the estimation and control algorithms. Approaches based on nonlinear optimization, such as moving horizon estimation, have been shown to improve the accuracy of the estimated solution compared to traditional filter techniques. This paper introduces an optimization-based framework for multi-sensor fusion following a moving horizon scheme. The framework is applied to the often occurring estimation problem of motion tracking by fusing measurements of a global navigation satellite system receiver and an inertial measurement unit. The resulting algorithm is used to estimate position, velocity, and orientation of a maneuvering airplane and is evaluated against an accurate reference trajectory. A detailed study of the influence of the horizon length on the quality of the solution is presented and evaluated against filter-like and batch solutions of the problem. The versatile configuration possibilities of the framework are finally used to analyze the estimated solutions at different evaluation times exposing a nearly linear behavior of the sensor fusion problem. PMID:28534857

A Sensor Fusion Method Based on an Integrated Neural Network and Kalman Filter for Vehicle Roll Angle Estimation

PubMed Central

Vargas-Meléndez, Leandro; Boada, Beatriz L.; Boada, María Jesús L.; Gauchía, Antonio; Díaz, Vicente

2016-01-01

This article presents a novel estimator based on sensor fusion, which combines the Neural Network (NN) with a Kalman filter in order to estimate the vehicle roll angle. The NN estimates a “pseudo-roll angle” through variables that are easily measured from Inertial Measurement Unit (IMU) sensors. An IMU is a device that is commonly used for vehicle motion detection, and its cost has decreased during recent years. The pseudo-roll angle is introduced in the Kalman filter in order to filter noise and minimize the variance of the norm and maximum errors’ estimation. The NN has been trained for J-turn maneuvers, double lane change maneuvers and lane change maneuvers at different speeds and road friction coefficients. The proposed method takes into account the vehicle non-linearities, thus yielding good roll angle estimation. Finally, the proposed estimator has been compared with one that uses the suspension deflections to obtain the pseudo-roll angle. Experimental results show the effectiveness of the proposed NN and Kalman filter-based estimator. PMID:27589763

Optimization-Based Sensor Fusion of GNSS and IMU Using a Moving Horizon Approach.

PubMed

Girrbach, Fabian; Hol, Jeroen D; Bellusci, Giovanni; Diehl, Moritz

2017-05-19

The rise of autonomous systems operating close to humans imposes new challenges in terms of robustness and precision on the estimation and control algorithms. Approaches based on nonlinear optimization, such as moving horizon estimation, have been shown to improve the accuracy of the estimated solution compared to traditional filter techniques. This paper introduces an optimization-based framework for multi-sensor fusion following a moving horizon scheme. The framework is applied to the often occurring estimation problem of motion tracking by fusing measurements of a global navigation satellite system receiver and an inertial measurement unit. The resulting algorithm is used to estimate position, velocity, and orientation of a maneuvering airplane and is evaluated against an accurate reference trajectory. A detailed study of the influence of the horizon length on the quality of the solution is presented and evaluated against filter-like and batch solutions of the problem. The versatile configuration possibilities of the framework are finally used to analyze the estimated solutions at different evaluation times exposing a nearly linear behavior of the sensor fusion problem.

Precision enhancement of pavement roughness localization with connected vehicles

NASA Astrophysics Data System (ADS)

Bridgelall, R.; Huang, Y.; Zhang, Z.; Deng, F.

2016-02-01

Transportation agencies rely on the accurate localization and reporting of roadway anomalies that could pose serious hazards to the traveling public. However, the cost and technical limitations of present methods prevent their scaling to all roadways. Connected vehicles with on-board accelerometers and conventional geospatial position receivers offer an attractive alternative because of their potential to monitor all roadways in real-time. The conventional global positioning system is ubiquitous and essentially free to use but it produces impractically large position errors. This study evaluated the improvement in precision achievable by augmenting the conventional geo-fence system with a standard speed bump or an existing anomaly at a pre-determined position to establish a reference inertial marker. The speed sensor subsequently generates position tags for the remaining inertial samples by computing their path distances relative to the reference position. The error model and a case study using smartphones to emulate connected vehicles revealed that the precision in localization improves from tens of metres to sub-centimetre levels, and the accuracy of measuring localized roughness more than doubles. The research results demonstrate that transportation agencies will benefit from using the connected vehicle method to achieve precision and accuracy levels that are comparable to existing laser-based inertial profilers.

Estimation of Human Foot Motion During Normal Walking Using Inertial and Magnetic Sensor Measurements

DTIC Science & Technology

2012-07-01

and foot dynamics,” IEEE Trans. Biomed. Eng., vol. 54, no. 5, pp. 895–902, May 2007. [25] R. G. Brown and P. Y. C. Hwang , Introduction to Random Signals...the direction of displacement or position. In [18], Sabatini described a quaternion-based extended Kalman filter for determining the orientation of a...position. In [19], Foxlin used a foot-mounted IMMU from Inter- Sense incorporating the ZVU and an extended Kalman filter to achieve error performance

Research on the Forward and Reverse Calculation Based on the Adaptive Zero-Velocity Interval Adjustment for the Foot-Mounted Inertial Pedestrian-Positioning System

PubMed Central

Wang, Qiuying; Guo, Zheng; Sun, Zhiguo; Cui, Xufei; Liu, Kaiyue

2018-01-01

Pedestrian-positioning technology based on the foot-mounted micro inertial measurement unit (MIMU) plays an important role in the field of indoor navigation and has received extensive attention in recent years. However, the positioning accuracy of the inertial-based pedestrian-positioning method is rapidly reduced because of the relatively low measurement accuracy of the measurement sensor. The zero-velocity update (ZUPT) is an error correction method which was proposed to solve the cumulative error because, on a regular basis, the foot is stationary during the ordinary gait; this is intended to reduce the position error growth of the system. However, the traditional ZUPT has poor performance because the time of foot touchdown is short when the pedestrians move faster, which decreases the positioning accuracy. Considering these problems, a forward and reverse calculation method based on the adaptive zero-velocity interval adjustment for the foot-mounted MIMU location method is proposed in this paper. To solve the inaccuracy of the zero-velocity interval detector during fast pedestrian movement where the contact time of the foot on the ground is short, an adaptive zero-velocity interval detection algorithm based on fuzzy logic reasoning is presented in this paper. In addition, to improve the effectiveness of the ZUPT algorithm, forward and reverse multiple solutions are presented. Finally, with the basic principles and derivation process of this method, the MTi-G710 produced by the XSENS company is used to complete the test. The experimental results verify the correctness and applicability of the proposed method. PMID:29883399

Flight test results of the strapdown ring laser gyro tetrad inertial navigation system

NASA Technical Reports Server (NTRS)

Carestia, R. A.; Hruby, R. J.; Bjorkman, W. S.

1983-01-01

A helicopter flight test program undertaken to evaluate the performance of Tetrad (a strap down, laser gyro, inertial navigation system) is described. The results of 34 flights show a mean final navigational velocity error of 5.06 knots, with a standard deviation of 3.84 knots; a corresponding mean final position error of 2.66 n. mi., with a standard deviation of 1.48 n. mi.; and a modeled mean position error growth rate for the 34 tests of 1.96 knots, with a standard deviation of 1.09 knots. No laser gyro or accelerometer failures were detected during the flight tests. Off line parity residual studies used simulated failures with the prerecorded flight test and laboratory test data. The airborne Tetrad system's failure--detection logic, exercised during the tests, successfully demonstrated the detection of simulated ""hard'' failures and the system's ability to continue successfully to navigate by removing the simulated faulted sensor from the computations. Tetrad's four ring laser gyros provided reliable and accurate angular rate sensing during the 4 yr of the test program, and no sensor failures were detected during the evaluation of free inertial navigation performance.

Improved Correction System for Vibration Sensitive Inertial Angle of Attack Measurement Devices

NASA Technical Reports Server (NTRS)

Crawford, Bradley L.; Finley, Tom D.

2000-01-01

Inertial angle of attack (AoA) devices currently in use at NASA Langley Research Center (LaRC) are subject to inaccuracies due to centrifugal accelerations caused by model dynamics, also known as sting whip. Recent literature suggests that these errors can be as high as 0.25 deg. With the current AoA accuracy target at LaRC being 0.01 deg., there is a dire need for improvement. With other errors in the inertial system (temperature, rectification, resolution, etc.) having been reduced to acceptable levels, a system is currently being developed at LaRC to measure and correct for the sting-whip-induced errors. By using miniaturized piezoelectric accelerometers and magnetohydrodynamic rate sensors, not only can the total centrifugal acceleration be measured, but yaw and pitch dynamics in the tunnel can also be characterized. These corrections can be used to determine a tunnel's past performance and can also indicate where efforts need to be concentrated to reduce these dynamics. Included in this paper are data on individual sensors, laboratory testing techniques, package evaluation, and wind tunnel test results on a High Speed Research (HSR) model in the Langley 16-Foot Transonic Wind Tunnel.

Advanced Pedestrian Positioning System to Smartphones and Smartwatches.

PubMed

Correa, Alejandro; Munoz Diaz, Estefania; Bousdar Ahmed, Dina; Morell, Antoni; Lopez Vicario, Jose

2016-11-11

In recent years, there has been an increasing interest in the development of pedestrian navigation systems for satellite-denied scenarios. The popularization of smartphones and smartwatches is an interesting opportunity for reducing the infrastructure cost of the positioning systems. Nowadays, smartphones include inertial sensors that can be used in pedestrian dead-reckoning (PDR) algorithms for the estimation of the user's position. Both smartphones and smartwatches include WiFi capabilities allowing the computation of the received signal strength (RSS). We develop a new method for the combination of RSS measurements from two different receivers using a Gaussian mixture model. We also analyze the implication of using a WiFi network designed for communication purposes in an indoor positioning system when the designer cannot control the network configuration. In this work, we design a hybrid positioning system that combines inertial measurements, from low-cost inertial sensors embedded in a smartphone, with RSS measurements through an extended Kalman filter. The system has been validated in a real scenario, and results show that our system improves the positioning accuracy of the PDR system thanks to the use of two WiFi receivers. The designed system obtains an accuracy up to 1.4 m in a scenario of 6000 m 2 .

Monitoring Hitting Load in Tennis Using Inertial Sensors and Machine Learning.

PubMed

Whiteside, David; Cant, Olivia; Connolly, Molly; Reid, Machar

2017-10-01

Quantifying external workload is fundamental to training prescription in sport. In tennis, global positioning data are imprecise and fail to capture hitting loads. The current gold standard (manual notation) is time intensive and often not possible given players' heavy travel schedules. To develop an automated stroke-classification system to help quantify hitting load in tennis. Nineteen athletes wore an inertial measurement unit (IMU) on their wrist during 66 video-recorded training sessions. Video footage was manually notated such that known shot type (serve, rally forehand, slice forehand, forehand volley, rally backhand, slice backhand, backhand volley, smash, or false positive) was associated with the corresponding IMU data for 28,582 shots. Six types of machine-learning models were then constructed to classify true shot type from the IMU signals. Across 10-fold cross-validation, a cubic-kernel support vector machine classified binned shots (overhead, forehand, or backhand) with an accuracy of 97.4%. A second cubic-kernel support vector machine achieved 93.2% accuracy when classifying all 9 shot types. With a view to monitoring external load, the combination of miniature inertial sensors and machine learning offers a practical and automated method of quantifying shot counts and discriminating shot types in elite tennis players.

An objective comparison of commercially-available cavitation meters.

PubMed

Sarno, Daniel; Hodnett, Mark; Wang, Lian; Zeqiri, Bajram

2017-01-01

With a number of cavitation meters on the market which claim to characterise fields in ultrasonic cleaning baths, this paper provides an objective comparison of a selection of these devices and establishes the extent to which their claims are met. The National Physical Laboratory's multi-frequency ultrasonic reference vessel provided the stable 21.06kHz field, above and below the inertial cavitation threshold, as a test bed for the sensor comparison. Measurements from these devices were evaluated in relation to the known acoustic pressure distribution in the cavitating vessel as a means of identifying the mode of operation of the sensors and to examine the particular indicator of cavitation activity which they deliver. Through the comparison with megahertz filtered acoustic signals generated by inertial cavitation, it was determined that the majority of the cavitation meters used in this study responded to acoustic pressure generated by the direct applied acoustic field and therefore tended to overestimate the occurrence of cavitation within the vessel, giving non-zero responses under conditions when there was known to be no inertial cavitation occurring with the reference vessel. This has implications for interpreting the data they provide in user applications. Copyright © 2016. Published by Elsevier B.V.

A Low-Visibility Force Multiplier: Assessing China’s Cruise Missile Ambitions

DTIC Science & Technology

2014-04-01

terminal sensor to achieve 10–15 meter (m) accuracy. • The second-generation DH-10 has a GPS/inertial guidance system but may also use terrain...contour mapping for redundant midcourse guidance and a digital scene-matching sensor to permit an accuracy of 10 m. • Development of the Chinese Beidou...pictures of the target as seen from different perspectives. DSMAC permits LACMs to achieve accuracies of about 1 m. Other (for example, thermal) sensors

Uniaxial angular accelerometers

NASA Astrophysics Data System (ADS)

Seleznev, A. V.; Shvab, I. A.

1985-05-01

The basic mechanical components of an angular accelerometer are the sensor, the damper, and the transducer. Penumatic dampers are simplest in construction, but the viscosity of air is very low and, therefore, dampers with special purpose oils having a high temperature stability (synthetic silicon or organosilicon oils) are most widely used. The most common types of viscous dampers are lamellar with meshed opposed arrays of fixed and movable vanes in the dashpot, piston dampers regulated by an adjustable-length capillary tube, and dampers with paddle wheel in closed tank. Another type of damper is an impact-inertial one with large masses absorbing the rotational energy upon collision with the sensor. Conventional measuring elements are resistive, capacitive, electromagnetic, photoelectric, and penumatic or hydraulic. Novel types of angular accelerometers are based on inertia of gas jets, electron beams, and ion beams, the piezoelectric effect in p-n junctions of diode and transistors, the electrokinetic effect in fluids, and cryogenic suspension of the sensor.

Improved motor control method with measurements of fiber optics gyro (FOG) for dual-axis rotational inertial navigation system (RINS).

PubMed

Song, Tianxiao; Wang, Xueyun; Liang, Wenwei; Xing, Li

2018-05-14

Benefiting from frame structure, RINS can improve the navigation accuracy by modulating the inertial sensor errors with proper rotation scheme. In the traditional motor control method, the measurements of the photoelectric encoder are always adopted to drive inertial measurement unit (IMU) to rotate. However, when carrier conducts heading motion, the inertial sensor errors may no longer be zero-mean in navigation coordinate. Meanwhile, some high-speed carriers like aircraft need to roll a certain angle to balance the centrifugal force during the heading motion, which may result in non-negligible coupling errors, caused by the FOG installation errors and scale factor errors. Moreover, the error parameters of FOG are susceptible to the temperature and magnetic field, and the pre-calibration is a time-consuming process which is difficult to completely suppress the FOG-related errors. In this paper, an improved motor control method with the measurements of FOG is proposed to address these problems, with which the outer frame can insulate the carrier's roll motion and the inner frame can simultaneously achieve the rotary modulation on the basis of insulating the heading motion. The results of turntable experiments indicate that the navigation performance of dual-axis RINS has been significantly improved over the traditional method, which could still be maintained even with large FOG installation errors and scale factor errors, proving that the proposed method can relax the requirements for the accuracy of FOG-related errors.

Wearable knee health rehabilitation assessment using acoustical emissions

NASA Astrophysics Data System (ADS)

Teague, Caitlin N.; Hersek, Sinan; Conant, Jordan L.; Gilliland, Scott M.; Inan, Omer T.

2017-02-01

We have developed a novel, wearable sensing system based on miniature piezoelectric contact microphones for measuring the acoustical emissions from the knee during movement. The system consists of two contact microphones, positioned on the medial and lateral sides of the patella, connected to custom, analog pre-amplifier circuits and a microcontroller for digitization and data storage on a secure digital card. Tn addition to the acoustical sensing, the system includes two integrated inertial measurement sensors including accelerometer and gyroscope modalities to enable joint angle calculations; these sensors, with digital outputs, are connected directly to the same microcontroller. The system provides low noise, accurate joint acoustical emission and angle measurements in a wearable form factor and has several hours of battery life.

Field Programmable Gate Array (FPGA) Respiratory Monitoring System Using a Flow Microsensor and an Accelerometer

NASA Astrophysics Data System (ADS)

Mellal, Idir; Laghrouche, Mourad; Bui, Hung Tien

2017-04-01

This paper describes a non-invasive system for respiratory monitoring using a Micro Electro Mechanical Systems (MEMS) flow sensor and an IMU (Inertial Measurement Unit) accelerometer. The designed system is intended to be wearable and used in a hospital or at home to assist people with respiratory disorders. To ensure the accuracy of our system, we proposed a calibration method based on ANN (Artificial Neural Network) to compensate the temperature drift of the silicon flow sensor. The sigmoid activation functions used in the ANN model were computed with the CORDIC (COordinate Rotation DIgital Computer) algorithm. This algorithm was also used to estimate the tilt angle in body position. The design was implemented on reconfigurable platform FPGA.

Machine learning algorithms based on signals from a single wearable inertial sensor can detect surface- and age-related differences in walking.

PubMed

Hu, B; Dixon, P C; Jacobs, J V; Dennerlein, J T; Schiffman, J M

2018-04-11

The aim of this study was to investigate if a machine learning algorithm utilizing triaxial accelerometer, gyroscope, and magnetometer data from an inertial motion unit (IMU) could detect surface- and age-related differences in walking. Seventeen older (71.5 ± 4.2 years) and eighteen young (27.0 ± 4.7 years) healthy adults walked over flat and uneven brick surfaces wearing an inertial measurement unit (IMU) over the L5 vertebra. IMU data were binned into smaller data segments using 4-s sliding windows with 1-s step lengths. Ninety percent of the data were used as training inputs and the remaining ten percent were saved for testing. A deep learning network with long short-term memory units was used for training (fully supervised), prediction, and implementation. Four models were trained using the following inputs: all nine channels from every sensor in the IMU (fully trained model), accelerometer signals alone, gyroscope signals alone, and magnetometer signals alone. The fully trained models for surface and age outperformed all other models (area under the receiver operator curve, AUC = 0.97 and 0.96, respectively; p ≤ .045). The fully trained models for surface and age had high accuracy (96.3, 94.7%), precision (96.4, 95.2%), recall (96.3, 94.7%), and f1-score (96.3, 94.6%). These results demonstrate that processing the signals of a single IMU device with machine-learning algorithms enables the detection of surface conditions and age-group status from an individual's walking behavior which, with further learning, may be utilized to facilitate identifying and intervening on fall risk. Copyright © 2018 Elsevier Ltd. All rights reserved.

Classifying Lower Extremity Muscle Fatigue during Walking using Machine Learning and Inertial Sensors

PubMed Central

Zhang, Jian; Lockhart, Thurmon E.; Soangra, Rahul

2013-01-01

Fatigue in lower extremity musculature is associated with decline in postural stability, motor performance and alters normal walking patterns in human subjects. Automated recognition of lower extremity muscle fatigue condition may be advantageous in early detection of fall and injury risks. Supervised machine learning methods such as Support Vector Machines (SVM) have been previously used for classifying healthy and pathological gait patterns and also for separating old and young gait patterns. In this study we explore the classification potential of SVM in recognition of gait patterns utilizing an inertial measurement unit associated with lower extremity muscular fatigue. Both kinematic and kinetic gait patterns of 17 participants (29±11 years) were recorded and analyzed in normal and fatigued state of walking. Lower extremities were fatigued by performance of a squatting exercise until the participants reached 60% of their baseline maximal voluntary exertion level. Feature selection methods were used to classify fatigue and no-fatigue conditions based on temporal and frequency information of the signals. Additionally, influences of three different kernel schemes (i.e., linear, polynomial, and radial basis function) were investigated for SVM classification. The results indicated that lower extremity muscle fatigue condition influenced gait and loading responses. In terms of the SVM classification results, an accuracy of 96% was reached in distinguishing the two gait patterns (fatigue and no-fatigue) within the same subject using the kinematic, time and frequency domain features. It is also found that linear kernel and RBF kernel were equally good to identify intra-individual fatigue characteristics. These results suggest that intra-subject fatigue classification using gait patterns from an inertial sensor holds considerable potential in identifying “at-risk” gait due to muscle fatigue. PMID:24081829

Unstructured Facility Navigation by Applying the NIST 4D/RCS Architecture

DTIC Science & Technology

2006-07-01

control, and the planner); wire- less data and emergency stop radios; GPS receiver; inertial navigation unit; dual stereo cameras; infrared sensors...current Actuators Wheel motors, camera controls Scale & filter signals status commands commands commands GPS Antenna Dual stereo cameras...used in the sensory processing module include the two pairs of stereo color cameras, the physical bumper and infrared bumper sensors, the motor

Quantum Gravity Gradiometer Development for Space

NASA Technical Reports Server (NTRS)

Kohel, James M.; Yu, Nan; Kellogg, James R.; Thompson, Robert J.; Aveline, David C.; Maleki, Lute

2006-01-01

Funded by the Advanced Technology Component Program, we have completed the development of a laboratory-based quantum gravity gradiometer based on atom interferometer technology. This is our first step towards a new spaceborne gradiometer instrument, which can significantly contribute to global gravity mapping and monitoring important in the understanding of the solid earth, ice and oceans, and dynamic processes. In this paper, we will briefly review the principles and technical benefits of atom-wave interferometer-based inertial sensors in space. We will then describe the technical implementation of the laboratory setup and report its status. We will also discuss our implementation plan for the next generation instrument.

Simulation-based evaluation of a cold atom interferometry gradiometer concept for gravity field recovery

NASA Astrophysics Data System (ADS)

Douch, Karim; Wu, Hu; Schubert, Christian; Müller, Jürgen; Pereira dos Santos, Franck

2018-03-01

The prospects of future satellite gravimetry missions to sustain a continuous and improved observation of the gravitational field have stimulated studies of new concepts of space inertial sensors with potentially improved precision and stability. This is in particular the case for cold-atom interferometry (CAI) gradiometry which is the object of this paper. The performance of a specific CAI gradiometer design is studied here in terms of quality of the recovered gravity field through a closed-loop numerical simulation of the measurement and processing workflow. First we show that mapping the time-variable field on a monthly basis would require a noise level below 5mE /√{Hz } . The mission scenarios are therefore focused on the static field, like GOCE. Second, the stringent requirement on the angular velocity of a one-arm gradiometer, which must not exceed 10-6 rad/s, leads to two possible modes of operation of the CAI gradiometer: the nadir and the quasi-inertial mode. In the nadir mode, which corresponds to the usual Earth-pointing satellite attitude, only the gradient Vyy , along the cross-track direction, is measured. In the quasi-inertial mode, the satellite attitude is approximately constant in the inertial reference frame and the 3 diagonal gradients Vxx,Vyy and Vzz are measured. Both modes are successively simulated for a 239 km altitude orbit and the error on the recovered gravity models eventually compared to GOCE solutions. We conclude that for the specific CAI gradiometer design assumed in this paper, only the quasi-inertial mode scenario would be able to significantly outperform GOCE results at the cost of technically challenging requirements on the orbit and attitude control.

Analysis of a Smartphone-Based Architecture with Multiple Mobility Sensors for Fall Detection with Supervised Learning

PubMed Central

Santoyo-Ramón, José Antonio

2018-01-01

This paper describes a wearable Fall Detection System (FDS) based on a body-area network consisting of four nodes provided with inertial sensors and Bluetooth wireless interfaces. The signals captured by the nodes are sent to a smartphone which simultaneously acts as another sensing point. In contrast to many FDSs proposed by the literature (which only consider a single sensor), the multisensory nature of the prototype is utilized to investigate the impact of the number and the positions of the sensors on the effectiveness of the production of the fall detection decision. In particular, the study assesses the capability of four popular machine learning algorithms to discriminate the dynamics of the Activities of Daily Living (ADLs) and falls generated by a set of experimental subjects, when the combined use of the sensors located on different parts of the body is considered. Prior to this, the election of the statistics that optimize the characterization of the acceleration signals and the efficacy of the FDS is also investigated. As another important methodological novelty in this field, the statistical significance of all the results (an aspect which is usually neglected by other works) is validated by an analysis of variance (ANOVA). PMID:29642638

Direct Sensor Orientation of a Land-Based Mobile Mapping System

PubMed Central

Rau, Jiann-Yeou; Habib, Ayman F.; Kersting, Ana P.; Chiang, Kai-Wei; Bang, Ki-In; Tseng, Yi-Hsing; Li, Yu-Hua

2011-01-01

A land-based mobile mapping system (MMS) is flexible and useful for the acquisition of road environment geospatial information. It integrates a set of imaging sensors and a position and orientation system (POS). The positioning quality of such systems is highly dependent on the accuracy of the utilized POS. This limitation is the major drawback due to the elevated cost associated with high-end GPS/INS units, particularly the inertial system. The potential accuracy of the direct sensor orientation depends on the architecture and quality of the GPS/INS integration process as well as the validity of the system calibration (i.e., calibration of the individual sensors as well as the system mounting parameters). In this paper, a novel single-step procedure using integrated sensor orientation with relative orientation constraint for the estimation of the mounting parameters is introduced. A comparative analysis between the proposed single-step and the traditional two-step procedure is carried out. Moreover, the estimated mounting parameters using the different methods are used in a direct geo-referencing procedure to evaluate their performance and the feasibility of the implemented system. Experimental results show that the proposed system using single-step system calibration method can achieve high 3D positioning accuracy. PMID:22164015

Structural action recognition in body sensor networks: distributed classification based on string matching.

PubMed

Ghasemzadeh, Hassan; Loseu, Vitali; Jafari, Roozbeh

2010-03-01

Mobile sensor-based systems are emerging as promising platforms for healthcare monitoring. An important goal of these systems is to extract physiological information about the subject wearing the network. Such information can be used for life logging, quality of life measures, fall detection, extraction of contextual information, and many other applications. Data collected by these sensor nodes are overwhelming, and hence, an efficient data processing technique is essential. In this paper, we present a system using inexpensive, off-the-shelf inertial sensor nodes that constructs motion transcripts from biomedical signals and identifies movements by taking collaboration between the nodes into consideration. Transcripts are built of motion primitives and aim to reduce the complexity of the original data. We then label each primitive with a unique symbol and generate a sequence of symbols, known as motion template, representing a particular action. This model leads to a distributed algorithm for action recognition using edit distance with respect to motion templates. The algorithm reduces the number of active nodes during every classification decision. We present our results using data collected from five normal subjects performing transitional movements. The results clearly illustrate the effectiveness of our framework. In particular, we obtain a classification accuracy of 84.13% with only one sensor node involved in the classification process.

Real-time inverse kinematics for the upper limb: a model-based algorithm using segment orientations.

PubMed

Borbély, Bence J; Szolgay, Péter

2017-01-17

Model based analysis of human upper limb movements has key importance in understanding the motor control processes of our nervous system. Various simulation software packages have been developed over the years to perform model based analysis. These packages provide computationally intensive-and therefore off-line-solutions to calculate the anatomical joint angles from motion captured raw measurement data (also referred as inverse kinematics). In addition, recent developments in inertial motion sensing technology show that it may replace large, immobile and expensive optical systems with small, mobile and cheaper solutions in cases when a laboratory-free measurement setup is needed. The objective of the presented work is to extend the workflow of measurement and analysis of human arm movements with an algorithm that allows accurate and real-time estimation of anatomical joint angles for a widely used OpenSim upper limb kinematic model when inertial sensors are used for movement recording. The internal structure of the selected upper limb model is analyzed and used as the underlying platform for the development of the proposed algorithm. Based on this structure, a prototype marker set is constructed that facilitates the reconstruction of model-based joint angles using orientation data directly available from inertial measurement systems. The mathematical formulation of the reconstruction algorithm is presented along with the validation of the algorithm on various platforms, including embedded environments. Execution performance tables of the proposed algorithm show significant improvement on all tested platforms. Compared to OpenSim's Inverse Kinematics tool 50-15,000x speedup is achieved while maintaining numerical accuracy. The proposed algorithm is capable of real-time reconstruction of standardized anatomical joint angles even in embedded environments, establishing a new way for complex applications to take advantage of accurate and fast model-based inverse kinematics calculations.

Autonomous Navigation of Small Uavs Based on Vehicle Dynamic Model

NASA Astrophysics Data System (ADS)

Khaghani, M.; Skaloud, J.

2016-03-01

This paper presents a novel approach to autonomous navigation for small UAVs, in which the vehicle dynamic model (VDM) serves as the main process model within the navigation filter. The proposed method significantly increases the accuracy and reliability of autonomous navigation, especially for small UAVs with low-cost IMUs on-board. This is achieved with no extra sensor added to the conventional INS/GNSS setup. This improvement is of special interest in case of GNSS outages, where inertial coasting drifts very quickly. In the proposed architecture, the solution to VDM equations provides the estimate of position, velocity, and attitude, which is updated within the navigation filter based on available observations, such as IMU data or GNSS measurements. The VDM is also fed with the control input to the UAV, which is available within the control/autopilot system. The filter is capable of estimating wind velocity and dynamic model parameters, in addition to navigation states and IMU sensor errors. Monte Carlo simulations reveal major improvements in navigation accuracy compared to conventional INS/GNSS navigation system during the autonomous phase, when satellite signals are not available due to physical obstruction or electromagnetic interference for example. In case of GNSS outages of a few minutes, position and attitude accuracy experiences improvements of orders of magnitude compared to inertial coasting. It means that during such scenario, the position-velocity-attitude (PVA) determination is sufficiently accurate to navigate the UAV to a home position without any signal that depends on vehicle environment.

LightDenseYOLO: A Fast and Accurate Marker Tracker for Autonomous UAV Landing by Visible Light Camera Sensor on Drone.

PubMed

Nguyen, Phong Ha; Arsalan, Muhammad; Koo, Ja Hyung; Naqvi, Rizwan Ali; Truong, Noi Quang; Park, Kang Ryoung

2018-05-24

Autonomous landing of an unmanned aerial vehicle or a drone is a challenging problem for the robotics research community. Previous researchers have attempted to solve this problem by combining multiple sensors such as global positioning system (GPS) receivers, inertial measurement unit, and multiple camera systems. Although these approaches successfully estimate an unmanned aerial vehicle location during landing, many calibration processes are required to achieve good detection accuracy. In addition, cases where drones operate in heterogeneous areas with no GPS signal should be considered. To overcome these problems, we determined how to safely land a drone in a GPS-denied environment using our remote-marker-based tracking algorithm based on a single visible-light-camera sensor. Instead of using hand-crafted features, our algorithm includes a convolutional neural network named lightDenseYOLO to extract trained features from an input image to predict a marker's location by visible light camera sensor on drone. Experimental results show that our method significantly outperforms state-of-the-art object trackers both using and not using convolutional neural network in terms of both accuracy and processing time.

An Enhanced Reservation-Based MAC Protocol for IEEE 802.15.4 Networks

PubMed Central

Afonso, José A.; Silva, Helder D.; Macedo, Pedro; Rocha, Luis A.

2011-01-01

The IEEE 802.15.4 Medium Access Control (MAC) protocol is an enabling standard for wireless sensor networks. In order to support applications requiring dedicated bandwidth or bounded delay, it provides a reservation-based scheme named Guaranteed Time Slot (GTS). However, the GTS scheme presents some drawbacks, such as inefficient bandwidth utilization and support to a maximum of only seven devices. This paper presents eLPRT (enhanced Low Power Real Time), a new reservation-based MAC protocol that introduces several performance enhancing features in comparison to the GTS scheme. This MAC protocol builds on top of LPRT (Low Power Real Time) and includes various mechanisms designed to increase data transmission reliability against channel errors, improve bandwidth utilization and increase the number of supported devices. A motion capture system based on inertial and magnetic sensors has been used to validate the protocol. The effectiveness of the performance enhancements introduced by each of the new features is demonstrated through the provision of both simulation and experimental results. PMID:22163826

Development of a vibration isolation prototype system for microgravity space experiments

NASA Technical Reports Server (NTRS)

Logsdon, Kirk A.; Grodsinsky, Carlos M.; Brown, Gerald V.

1990-01-01

The presence of small levels of low-frequency accelerations on the space shuttle orbiters has degraded the microgravity environment for the science community. Growing concern about this microgravity environment has generated interest in systems that can isolate microgravity science experiments from vibrations. This interest has resulted primarily in studies of isolation systems with active methods of compensation. The development of a magnetically suspended, six-degree-of-freedom active vibration isolation prototype system capable of providing the needed compensation to the orbital environment is presented. A design for the magnetic actuators is described, and the control law for the prototype system that gives a nonintrusive inertial isolation response to the system is also described. Relative and inertial sensors are used to provide an inertial reference for isolating the payload.