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

Science.gov (United States)

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

Inertial navigation sensor integrated motion analysis for autonomous vehicle navigation

Science.gov (United States)

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.

Vision-aided inertial navigation system for robotic mobile mapping

Science.gov (United States)

Bayoud, Fadi; Skaloud, Jan

2008-04-01

A mapping system by vision-aided inertial navigation was developed for areas where GNSS signals are unreachable. In this framework, a methodology on the integration of vision and inertial sensors is presented, analysed and tested. The system employs the method of “SLAM: Simultaneous Localisation And Mapping” where the only external input available to the system at the beginning of the mapping mission is a number of features with known coordinates. SLAM is a term used in the robotics community to describe the problem of mapping the environment and at the same time using this map to determine the location of the mapping device. Differing from the robotics approach, the presented development stems from the frameworks of photogrammetry and kinematic geodesy that are merged in two filters that run in parallel: the Least-Squares Adjustment (LSA) for features coordinates determination and the Kalman filter (KF) for navigation correction. To test this approach, a mapping system-prototype comprising two CCD cameras and one Inertial Measurement Unit (IMU) is introduced. Conceptually, the outputs of the LSA photogrammetric resection are used as the external measurements for the KF that corrects the inertial navigation. The filtered position and orientation are subsequently employed in the photogrammetric intersection to map the surrounding features that are used as control points for the resection in the next epoch. We confirm empirically the dependency of navigation performance on the quality of the images and the number of tracked features, as well as on the geometry of the stereo-pair. Due to its autonomous nature, the SLAM's performance is further affected by the quality of IMU initialisation and the a-priory assumptions on error distribution. Using the example of the presented system we show that centimetre accuracy can be achieved in both navigation and mapping when the image geometry is optimal.

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

Directory of Open Access Journals (Sweden)

Guohu Feng

2012-06-01

Full Text Available 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.

INTEGRATION OF DISTRIBUTED INERTIAL NAVIGATION SYSTEMS BUILT AROUND FIBER-OPTIC AND MICROELECTROMECHANICAL SENSORS

Directory of Open Access Journals (Sweden)

A. V. Chernodarov

2017-01-01

Full Text Available The current state of airborne measuring-and-computing complexes (MCCs is characterized by the inclusion of distributed strapdown inertial navigation systems (SINSs as components of these complexes. This is associated with the necessity of the provision of navigational support not only for aircraft (Acft, but also for airborne Earth surface surveillance systems in which the SINSs are included as components. Among such systems are radar systems, video monitors, laser scanners (lidars, and other surveillance devices. At the same time, when the DSINSs are united into a single structure, new functional possibilities for such integrated navigation systems appear, namely: redundancy and mutual support of SINSs, and also an increase in MCC information reliability on this basis; mutual monitoring and mutual diagnosis of SINSs; optimization of DSINS structure for providing the required accuracy of navigation and attitude control under severe conditions of Acft operation. Such conditions are connected with Acft maneuvering, with a loss of the signals of satellite navigation systems (SNSs. The purpose of this paper is to study the capabilities of DSINS which are built around fiberoptic and micromechanical sensors when they are united into a closely connected information-measuring structure. In the solution of the problem formulated above, an object-oriented modular technology for the creation of integrated navigation systems was taken as a basis. The use of such a technology has permitted us to realize the new functional possibilities of the DSINSs, and also to take into account the following features of the construction and functioning of DSINSs as components of MCCs: need for mutual information exchange among DSINS modules via an MCC airborne top-level computing system; synchronization of measuring-and-computing procedures that are realized in the DSINS. In addition, due to restrictions on overall dimensions and weight, SINSs of surveillance systems are

Galileo spacecraft inertial sensors in-flight calibration design

Science.gov (United States)

Jahanshahi, M. H.; Lai, J. Y.

1983-01-01

The successful navigation of Galileo depends on accurate trajectory correction maneuvers (TCM's) performed during the mission. A set of Inertial Sensor (INS) units, comprised of gyros and accelerometers, mounted on the spacecraft, are utilized to control and monitor the performance of the TCM's. To provide the optimum performance, in-flight calibrations of INS are planned. These calibrations will take place on a regular basis. In this paper, a mathematical description is given of the data reduction technique used in analyzing a typical set of calibration data. The design of the calibration and the inertial sensor error models, necessary for the above analysis, are delineated in detail.

Error and Performance Analysis of MEMS-based Inertial Sensors with a Low-cost GPS Receiver

Directory of Open Access Journals (Sweden)

Yang Gao

2008-03-01

Full Text Available Global Navigation Satellite Systems (GNSS, such as the Global Positioning System (GPS, have been widely utilized and their applications are becoming popular, not only in military or commercial applications, but also for everyday life. Although GPS measurements are the essential information for currently developed land vehicle navigation systems (LVNS, GPS signals are often unavailable or unreliable due to signal blockages under certain environments such as urban canyons. This situation must be compensated in order to provide continuous navigation solutions. To overcome the problems of unavailability and unreliability using GPS and to be cost and size effective as well, Micro Electro Mechanical Systems (MEMS based inertial sensor technology has been pushing for the development of low-cost integrated navigation systems for land vehicle navigation and guidance applications. This paper will analyze the characterization of MEMS based inertial sensors and the performance of an integrated system prototype of MEMS based inertial sensors, a low-cost GPS receiver and a digital compass. The influence of the stochastic variation of sensors will be assessed and modeled by two different methods, namely Gauss-Markov (GM and AutoRegressive (AR models, with GPS signal blockage of different lengths. Numerical results from kinematic testing have been used to assess the performance of different modeling schemes.

Enhanced Subsea Acoustically Aided Inertial Navigation

DEFF Research Database (Denmark)

Jørgensen, Martin Juhl

time is expensive so lots of effort is put into cutting down on time spent on all tasks. Accuracy demanding tasks such as subsea construction and surveying are subject to strict quality control requirements taking up a lot of time. Offshore equipment is rugged and sturdy as the environmental conditions...... are harsh, likewise should the use of it be simple and robust to ensure that it actually works. The contributions of this thesis are all focused on enhancing accuracy and time efficiency while bearing operational reliability and complexity strongly in mind. The basis of inertial navigation, the inertial...... at desired survey points; the other uses a mapping sensor such as subsea lidar to simply map the area in question. Both approaches are shown to work in practice. Generating high resolution maps, as the latter approach, is how the author anticipates all subsea surveys will be conducted in the near future....

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

Science.gov (United States)

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.

Inertial Pocket Navigation System: Unaided 3D Positioning

Directory of Open Access Journals (Sweden)

Estefania Munoz Diaz

2015-04-01

Full Text Available 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.

Inertial Pocket Navigation System: Unaided 3D Positioning

Science.gov (United States)

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

DEVELOPMENT OF A PEDESTRIAN INDOOR NAVIGATION SYSTEM BASED ON MULTI-SENSOR FUSION AND FUZZY LOGIC ESTIMATION ALGORITHMS

Directory of Open Access Journals (Sweden)

Y. C. Lai

2015-05-01

Full Text Available This paper presents a pedestrian indoor navigation system based on the multi-sensor fusion and fuzzy logic estimation algorithms. The proposed navigation system is a self-contained dead reckoning navigation that means no other outside signal is demanded. In order to achieve the self-contained capability, a portable and wearable inertial measure unit (IMU has been developed. Its adopted sensors are the low-cost inertial sensors, accelerometer and gyroscope, based on the micro electro-mechanical system (MEMS. There are two types of the IMU modules, handheld and waist-mounted. The low-cost MEMS sensors suffer from various errors due to the results of manufacturing imperfections and other effects. Therefore, a sensor calibration procedure based on the scalar calibration and the least squares methods has been induced in this study to improve the accuracy of the inertial sensors. With the calibrated data acquired from the inertial sensors, the step length and strength of the pedestrian are estimated by multi-sensor fusion and fuzzy logic estimation algorithms. The developed multi-sensor fusion algorithm provides the amount of the walking steps and the strength of each steps in real-time. Consequently, the estimated walking amount and strength per step are taken into the proposed fuzzy logic estimation algorithm to estimates the step lengths of the user. Since the walking length and direction are both the required information of the dead reckoning navigation, the walking direction is calculated by integrating the angular rate acquired by the gyroscope of the developed IMU module. Both the walking length and direction are calculated on the IMU module and transmit to a smartphone with Bluetooth to perform the dead reckoning navigation which is run on a self-developed APP. Due to the error accumulating of dead reckoning navigation, a particle filter and a pre-loaded map of indoor environment have been applied to the APP of the proposed navigation system

Development of a Pedestrian Indoor Navigation System Based on Multi-Sensor Fusion and Fuzzy Logic Estimation Algorithms

Science.gov (United States)

Lai, Y. C.; Chang, C. C.; Tsai, C. M.; Lin, S. Y.; Huang, S. C.

2015-05-01

This paper presents a pedestrian indoor navigation system based on the multi-sensor fusion and fuzzy logic estimation algorithms. The proposed navigation system is a self-contained dead reckoning navigation that means no other outside signal is demanded. In order to achieve the self-contained capability, a portable and wearable inertial measure unit (IMU) has been developed. Its adopted sensors are the low-cost inertial sensors, accelerometer and gyroscope, based on the micro electro-mechanical system (MEMS). There are two types of the IMU modules, handheld and waist-mounted. The low-cost MEMS sensors suffer from various errors due to the results of manufacturing imperfections and other effects. Therefore, a sensor calibration procedure based on the scalar calibration and the least squares methods has been induced in this study to improve the accuracy of the inertial sensors. With the calibrated data acquired from the inertial sensors, the step length and strength of the pedestrian are estimated by multi-sensor fusion and fuzzy logic estimation algorithms. The developed multi-sensor fusion algorithm provides the amount of the walking steps and the strength of each steps in real-time. Consequently, the estimated walking amount and strength per step are taken into the proposed fuzzy logic estimation algorithm to estimates the step lengths of the user. Since the walking length and direction are both the required information of the dead reckoning navigation, the walking direction is calculated by integrating the angular rate acquired by the gyroscope of the developed IMU module. Both the walking length and direction are calculated on the IMU module and transmit to a smartphone with Bluetooth to perform the dead reckoning navigation which is run on a self-developed APP. Due to the error accumulating of dead reckoning navigation, a particle filter and a pre-loaded map of indoor environment have been applied to the APP of the proposed navigation system to extend its

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

Science.gov (United States)

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.

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

Science.gov (United States)

2010-03-01

Magnetometer (Ref [23]) Until miniature atomic magnetometers transition from laboratory demonstration units to a mass produced product, fluxgate ...and/or magnetoresistive designs are a better suited magnetometer technology for a miniature navigation system. Figure 8 below shows the basic fluxgate ...is required to resolve magnetic field orientation. Fig 8. Fluxgate Magnetometer Schematic The PNI Sensor Corporation (Santa Rosa, CA

Data Integration from GPS and Inertial Navigation Systems for Pedestrians in Urban Area

Directory of Open Access Journals (Sweden)

Krzysztof Bikonis

2013-09-01

Full Text Available The GPS system is widely used in navigation and the GPS receiver can offer long-term stable absolute positioning information. The overall system performance depends largely on the signal environments. The position obtained from GPS is often degraded due to obstruction and multipath effect caused by buildings, city infrastructure and vegetation, whereas, the current performance achieved by inertial navigation systems (INS is still relatively poor due to the large inertial sensor errors. The complementary features of GPS and INS are the main reasons why integrated GPS/INS systems are becoming increasingly popular. GPS/INS systems offer a high data rate, high accuracy position and orientation that can work in all environments, particularly those where satellite availability is restricted. In the paper integration algorithm of GPS and INS systems data for pedestrians in urban area is presented. For data integration an Extended Kalman Filter (EKF algorithm is proposed. Complementary characteristics of GPS and INS with EKF can overcome the problem of huge INS drifts, GPS outages, dense multipath effect and other individual problems associated with these sensors.

A Rigorous Temperature-Dependent Stochastic Modelling and Testing for MEMS-Based Inertial Sensor Errors

Directory of Open Access Journals (Sweden)

Spiros Pagiatakis

2009-10-01

Full Text Available In this paper, we examine the effect of changing the temperature points on MEMS-based inertial sensor random error. We collect static data under different temperature points using a MEMS-based inertial sensor mounted inside a thermal chamber. Rigorous stochastic models, namely Autoregressive-based Gauss-Markov (AR-based GM models are developed to describe the random error behaviour. The proposed AR-based GM model is initially applied to short stationary inertial data to develop the stochastic model parameters (correlation times. It is shown that the stochastic model parameters of a MEMS-based inertial unit, namely the ADIS16364, are temperature dependent. In addition, field kinematic test data collected at about 17 °C are used to test the performance of the stochastic models at different temperature points in the filtering stage using Unscented Kalman Filter (UKF. It is shown that the stochastic model developed at 20 °C provides a more accurate inertial navigation solution than the ones obtained from the stochastic models developed at −40 °C, −20 °C, 0 °C, +40 °C, and +60 °C. The temperature dependence of the stochastic model is significant and should be considered at all times to obtain optimal navigation solution for MEMS-based INS/GPS integration.

A Rigorous Temperature-Dependent Stochastic Modelling and Testing for MEMS-Based Inertial Sensor Errors.

Science.gov (United States)

El-Diasty, Mohammed; Pagiatakis, Spiros

2009-01-01

In this paper, we examine the effect of changing the temperature points on MEMS-based inertial sensor random error. We collect static data under different temperature points using a MEMS-based inertial sensor mounted inside a thermal chamber. Rigorous stochastic models, namely Autoregressive-based Gauss-Markov (AR-based GM) models are developed to describe the random error behaviour. The proposed AR-based GM model is initially applied to short stationary inertial data to develop the stochastic model parameters (correlation times). It is shown that the stochastic model parameters of a MEMS-based inertial unit, namely the ADIS16364, are temperature dependent. In addition, field kinematic test data collected at about 17 °C are used to test the performance of the stochastic models at different temperature points in the filtering stage using Unscented Kalman Filter (UKF). It is shown that the stochastic model developed at 20 °C provides a more accurate inertial navigation solution than the ones obtained from the stochastic models developed at -40 °C, -20 °C, 0 °C, +40 °C, and +60 °C. The temperature dependence of the stochastic model is significant and should be considered at all times to obtain optimal navigation solution for MEMS-based INS/GPS integration.

Hybrid extended particle filter (HEPF) for integrated inertial navigation and global positioning systems

International Nuclear Information System (INIS)

Aggarwal, Priyanka; Syed, Zainab; El-Sheimy, Naser

2009-01-01

Navigation includes the integration of methodologies and systems for estimating time-varying position, velocity and attitude of moving objects. Navigation incorporating the integrated inertial navigation system (INS) and global positioning system (GPS) generally requires extensive evaluations of nonlinear equations involving double integration. Currently, integrated navigation systems are commonly implemented using the extended Kalman filter (EKF). The EKF assumes a linearized process, measurement models and Gaussian noise distributions. These assumptions are unrealistic for highly nonlinear systems like land vehicle navigation and may cause filter divergence. A particle filter (PF) is developed to enhance integrated INS/GPS system performance as it can easily deal with nonlinearity and non-Gaussian noises. In this paper, a hybrid extended particle filter (HEPF) is developed as an alternative to the well-known EKF to achieve better navigation data accuracy for low-cost microelectromechanical system sensors. The results show that the HEPF performs better than the EKF during GPS outages, especially when simulated outages are located in periods with high vehicle dynamics

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

Science.gov (United States)

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

Vision/INS Integrated Navigation System for Poor Vision Navigation Environments

Directory of Open Access Journals (Sweden)

Youngsun Kim

2016-10-01

Full Text Available In order to improve the performance of an inertial navigation system, many aiding sensors can be used. Among these aiding sensors, a vision sensor is of particular note due to its benefits in terms of weight, cost, and power consumption. This paper proposes an inertial and vision integrated navigation method for poor vision navigation environments. The proposed method uses focal plane measurements of landmarks in order to provide position, velocity and attitude outputs even when the number of landmarks on the focal plane is not enough for navigation. In order to verify the proposed method, computer simulations and van tests are carried out. The results show that the proposed method gives accurate and reliable position, velocity and attitude outputs when the number of landmarks is insufficient.

Micro-system inertial sensing technology overview.

Energy Technology Data Exchange (ETDEWEB)

Allen, James Joe

2009-02-01

The purpose of this report is to provide an overview of Micro-System technology as it applies to inertial sensing. Transduction methods are reviewed with capacitance and piezoresistive being the most often used in COTS Micro-electro-mechanical system (MEMS) inertial sensors. Optical transduction is the most recent transduction method having significant impact on improving sensor resolution. A few other methods are motioned which are in a R&D status to hopefully allow MEMS inertial sensors to become viable as a navigation grade sensor. The accelerometer, gyroscope and gravity gradiometer are the type of inertial sensors which are reviewed in this report. Their method of operation and a sampling of COTS sensors and grade are reviewed as well.

An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database.

Science.gov (United States)

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.

Inertial Sensor-Based Gait Recognition: A Review

Science.gov (United States)

Sprager, Sebastijan; Juric, Matjaz B.

2015-01-01

With the recent development of microelectromechanical systems (MEMS), inertial sensors have become widely used in the research of wearable gait analysis due to several factors, such as being easy-to-use and low-cost. Considering the fact that each individual has a unique way of walking, inertial sensors can be applied to the problem of gait recognition where assessed gait can be interpreted as a biometric trait. Thus, inertial sensor-based gait recognition has a great potential to play an important role in many security-related applications. Since inertial sensors are included in smart devices that are nowadays present at every step, inertial sensor-based gait recognition has become very attractive and emerging field of research that has provided many interesting discoveries recently. This paper provides a thorough and systematic review of current state-of-the-art in this field of research. Review procedure has revealed that the latest advanced inertial sensor-based gait recognition approaches are able to sufficiently recognise the users when relying on inertial data obtained during gait by single commercially available smart device in controlled circumstances, including fixed placement and small variations in gait. Furthermore, these approaches have also revealed considerable breakthrough by realistic use in uncontrolled circumstances, showing great potential for their further development and wide applicability. PMID:26340634

The Additional Error of Inertial Sensors Induced by Hypersonic Flight Conditions.

Science.gov (United States)

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

2016-02-26

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.

DVL Velocity Aiding in the HUGIN 1000 Integrated Inertial Navigation System

Directory of Open Access Journals (Sweden)

Bjørn Jalving

2004-10-01

Full Text Available The RDI WHN-600 Doppler Velocity Log (DVL is a key navigation sensor for the HUG1N 1000 Autonomous Underwater Vehicle (AUV. HUGIN 1000 is designed for autonomous submerged operation for long periods of time. This is facilitated by a low drift velocity aided Inertial Navigation System (INS. Major factors determining the position error growth are the IMU and DVL error characteristics and the mission plan pattern_ For instance, low frequency DVL errors cause an approximately linear drift in a straight-line trajectory, while these errors tend to be cancelled out by a lawn mower pattern_ The paper focuses on the accuracy offered by the DVL. HUGIN 1000 is a permanent organic mine countermeasure (MCM capacity on the Royal Norwegian Navy MCM vessel KNM Karmoy. HUGIN 1000 will be part of the NATO force MCMFORNORTH in fall 2004.

THERMAL PROTECTION AND THERMAL STABILIZATION OF FIBER-OPTICAL GYROSCOPE INCLUDED IN STRAPDOWN INERTIAL NAVIGATION SYSTEM

Directory of Open Access Journals (Sweden)

D. S. Gromov

2014-03-01

Full Text Available It is known, that temperature perturbations and thermal modes have significant influence on the accuracy of a fiber-optical gyroscope. Nowadays, thermal perturbations are among the main problems in the field of navigation accuracy. Review of existing methods for decrease of temperature influences on the accuracy of a strapdown inertial navigation system with fiberoptical gyros showed, that the usage of constructive and compensation methods only is insufficient and, therefore, thermostabilization is required. Reversible thermostabilization system is offered, its main executive elements are thermoelectric modules (Peltier’s modules, heat transfer from which is provided by heatsinks at work surfaces of modules. This variant of thermostabilization maintenance is considered; Peltier’s modules and temperature sensors for the system are chosen. Parameters of heatsinks for heat transfer intensification are calculated. Fans for necessary air circulation in the device are chosen and thickness of thermal isolation is calculated. Calculations of thermal modes of navigation system with thermostabilization are made in modern software Autodesk Simulation CFD. Comparison of results for present and previous researches and calculations shows essential decrease in gradients of temperature on gyro surfaces and better uniformity of temperature field in the whole device. Conclusions about efficiency of the given method usage in view of accuracy improvement of navigation system are made. Thermostabilization provision of a strapdown inertial navigation system with fiberoptical gyros is proved. Thermostabilization application in combination with compensational methods can reach a necessary accuracy of navigation system.

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

Science.gov (United States)

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.

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

National Research Council Canada - National Science Library

Nielsen, Michael B

2008-01-01

.... This algorithm provides an alternative to the Global Positioning System (GPS) as a precision navigation source, enabling navigation in GPS denied environments, using low-cost sensors and equipment...

A new systematic calibration method of ring laser gyroscope inertial navigation system

Science.gov (United States)

Wei, Guo; Gao, Chunfeng; Wang, Qi; Wang, Qun; Xiong, Zhenyu; Long, Xingwu

2016-10-01

Inertial navigation system has been the core component of both military and civil navigation systems. Before the INS is put into application, it is supposed to be calibrated in the laboratory in order to compensate repeatability error caused by manufacturing. Discrete calibration method cannot fulfill requirements of high-accurate calibration of the mechanically dithered ring laser gyroscope navigation system with shock absorbers. This paper has analyzed theories of error inspiration and separation in detail and presented a new systematic calibration method for ring laser gyroscope inertial navigation system. Error models and equations of calibrated Inertial Measurement Unit are given. Then proper rotation arrangement orders are depicted in order to establish the linear relationships between the change of velocity errors and calibrated parameter errors. Experiments have been set up to compare the systematic errors calculated by filtering calibration result with those obtained by discrete calibration result. The largest position error and velocity error of filtering calibration result are only 0.18 miles and 0.26m/s compared with 2 miles and 1.46m/s of discrete calibration result. These results have validated the new systematic calibration method and proved its importance for optimal design and accuracy improvement of calibration of mechanically dithered ring laser gyroscope inertial navigation system.

Multi-Sensor SLAM Approach for Robot Navigation

Directory of Open Access Journals (Sweden)

Sid Ahmed BERRABAH

2010-12-01

Full Text Available o be able to operate and act successfully, the robot needs to know at any time where it is. This means the robot has to find out its location relative to the environment. This contribution introduces the increase of accuracy of mobile robot positioning in large outdoor environments based on data fusion from different sensors: camera, GPS, inertial navigation system (INS, and wheel encoders. The fusion is done in a Simultaneous Localization and Mapping (SLAM approach. The paper gives an overview on the proposed algorithm and discusses the obtained results.

A Short Tutorial on Inertial Navigation System and Global Positioning System Integration

Science.gov (United States)

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.

Sensors integration for smartphone navigation: performances and future challenges

Science.gov (United States)

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.

Flight evaluations of approach/landing navigation sensor systems. MLS to kohokei hiko jikken. ; 1990 nendo no jikken gaiyo

Energy Technology Data Exchange (ETDEWEB)

1992-07-01

Flight test results of such navigation sensor systems as MLS (microwave landing system), GPS(global positioning system) and INS (inertial navigation system) on the Dornier-228 research aircraft in 1990 were reported, which tests have being promoted by National Aerospace Laboratory (NAL), Japan to develop unmanned approach/landing (A/L) navigation sensor systems for the future spaceplane HOPE. The measured data corresponding to a WGS84 (world geodetic system 1984) navigation coordinate system were evaluated, and the reference orbit was also prepared by laser tracker analysis. The navigation sensor systems such as MLS were evaluated on the basis of CMN (control motion noise) or PFE (path following error), and preliminary calculation was also conducted for a GPS-INS hybrid system. As experimental results, several data were gathered for each sensor system resulting in possible data comparison between the sensor systems, and the feasibility of the GPS-INS hybrid system was also confirmed. 35 refs., 49 figs., 22 tabs.

Fusion of Inertial Navigation and Imagery Data, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The innovations of the Fusion of Inertial Navigation and Imagery Data are the application of the concept to the dynamic entry-interface through near-landing phases,...

Cloud Absorption Radiometer Autonomous Navigation System - CANS

Science.gov (United States)

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

Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors

Directory of Open Access Journals (Sweden)

Dachuan Li

2015-04-01

Full Text Available This paper presents a non-linear state observer-based integrated navigation scheme for estimating the attitude, position and velocity of micro aerial vehicles (MAV operating in GPS-denied indoor environments, using the measurements from low-cost MEMS (micro electro-mechanical systems inertial sensors and an RGB-D camera. A robust RGB-D visual odometry (VO approach was developed to estimate the MAV’s relative motion by extracting and matching features captured by the RGB-D camera from the environment. The state observer of the RGB-D visual-aided inertial navigation was then designed based on the invariant observer theory for systems possessing symmetries. The motion estimates from the RGB-D VO were fused with inertial and magnetic measurements from the onboard MEMS sensors via the state observer, providing the MAV with accurate estimates of its full six degree-of-freedom states. Implementations on a quadrotor MAV and indoor flight test results demonstrate that the resulting state observer is effective in estimating the MAV’s states without relying on external navigation aids such as GPS. The properties of computational efficiency and simplicity in gain tuning make the proposed invariant observer-based navigation scheme appealing for actual MAV applications in indoor environments.

Kalman Filter for Estimation of Sensor Acceleration Using Six - axis Inertial Sensor

International Nuclear Information System (INIS)

Lee, Jung Keun

2015-01-01

Although an accelerometer is a sensor that measures acceleration, it cannot be used by itself to measure the acceleration when the orientation of the sensor changes. This paper introduces a Kalman filter for the estimation of a sensor acceleration based on a six-axis inertial sensor (i.e., a three-axis accelerometer and three-axis gyroscope). The novelty of the proposed Kalman filter lies in the fact that its state vector includes not only the tilt angle variable but also the sensor acceleration. Thus, the filter can explicitly estimate the latter with a high accuracy. The accuracy of acceleration estimates were validated experimentally under three different dynamic conditions, using an optical motion capture system. It could be concluded that the performance of the proposed Kalman filter was comparable to that of the state-of-the-art estimation algorithm employed by the Xsens MTw. The proposed algorithm may be more suitable than inertial/magnetic sensor-based algorithms for various applications adopting six-axis inertial sensors

On-body inertial sensor location recognition

NARCIS (Netherlands)

Weenk, D.; van Beijnum, Bernhard J.F.; Goaied, Salma; Baten, Christian T.M.; Hermens, Hermanus J.; Veltink, Petrus H.

2015-01-01

Introduction and past research: In previous work we presented an algorithm for automatically identifying the body segment to which an inertial sensor is attached during walking [1]. Using this method, the set-up of inertial motion capture systems becomes easier and attachment errors are avoided. The

Magnetic, Acceleration Fields and Gyroscope Quaternion (MAGYQ-Based Attitude Estimation with Smartphone Sensors for Indoor Pedestrian Navigation

Directory of Open Access Journals (Sweden)

Valérie Renaudin

2014-12-01

Full Text Available The dependence of proposed pedestrian navigation solutions on a dedicated infrastructure is a limiting factor to the deployment of location based services. Consequently self-contained Pedestrian Dead-Reckoning (PDR approaches are gaining interest for autonomous navigation. Even if the quality of low cost inertial sensors and magnetometers has strongly improved, processing noisy sensor signals combined with high hand dynamics remains a challenge. Estimating accurate attitude angles for achieving long term positioning accuracy is targeted in this work. A new Magnetic, Acceleration fields and GYroscope Quaternion (MAGYQ-based attitude angles estimation filter is proposed and demonstrated with handheld sensors. It benefits from a gyroscope signal modelling in the quaternion set and two new opportunistic updates: magnetic angular rate update (MARU and acceleration gradient update (AGU. MAGYQ filter performances are assessed indoors, outdoors, with dynamic and static motion conditions. The heading error, using only the inertial solution, is found to be less than 10° after 1.5 km walking. The performance is also evaluated in the positioning domain with trajectories computed following a PDR strategy.

Extended investigation into continuous laser scanning of underground mine workings by means of Landis inertial navigation system

Science.gov (United States)

Belyaev, E. N.

2017-10-01

The paper investigates the method of applying mobile scanning systems (MSSs) with inertial navigators in the underground conditions for carrying out the surveying tasks. The available mobile laser scanning systems cannot be used in the underground environment since Global Positioning System (GPS) signals cannot be received in mines. This signal not only is necessary for space positioning, but also operates as the main corrective signal for the primary navigation system - the inertial navigation system. The idea of the method described in this paper consists in using MSSs with a different correction of the inertial system than GPS is.

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

Directory of Open Access Journals (Sweden)

Francisco Bonin-Font

2015-01-01

Full Text Available 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.

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

Science.gov (United States)

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.

Time and Relative Distance Inertial Sensor, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Precise location information is critical for crewmembers for safe EVA Moon and Mars exploration. Current inertial navigation systems are too bulky, fragile, and...

A self-calibration method in single-axis rotational inertial navigation system with rotating mechanism

Science.gov (United States)

Chen, Yuanpei; Wang, Lingcao; Li, Kui

2017-10-01

Rotary inertial navigation modulation mechanism can greatly improve the inertial navigation system (INS) accuracy through the rotation. Based on the single-axis rotational inertial navigation system (RINS), a self-calibration method is put forward. The whole system is applied with the rotation modulation technique so that whole inertial measurement unit (IMU) of system can rotate around the motor shaft without any external input. In the process of modulation, some important errors can be decoupled. Coupled with the initial position information and attitude information of the system as the reference, the velocity errors and attitude errors in the rotation are used as measurement to perform Kalman filtering to estimate part of important errors of the system after which the errors can be compensated into the system. The simulation results show that the method can complete the self-calibration of the single-axis RINS in 15 minutes and estimate gyro drifts of three-axis, the installation error angle of the IMU and the scale factor error of the gyro on z-axis. The calibration accuracy of optic gyro drifts could be about 0.003°/h (1σ) as well as the scale factor error could be about 1 parts per million (1σ). The errors estimate reaches the system requirements which can effectively improve the longtime navigation accuracy of the vehicle or the boat.

Integrated INS/GPS Navigation from a Popular Perspective

Science.gov (United States)

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.

A novel redundant INS based on triple rotary inertial measurement units

Science.gov (United States)

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.

Validation of an Inertial Sensor System for Swing Analysis in Golf

Directory of Open Access Journals (Sweden)

Paul Lückemann

2018-02-01

Full Text Available Wearable inertial sensor systems are an upcoming tool for self-evaluation in sports, and can be used for swing analysis in golf. The aim of this work was to determine the validity and repeatability of an inertial sensor system attached to a player’s glove using a radar system as a reference. 20 subjects performed five full swings with each of three different clubs (wood, 7-iron, wedge. Clubhead speed was measured simultaneously by both sensor systems. Limits of Agreement were used to determine the accuracy and precision of the inertial sensor system. Results show that the inertial sensor system is quite accurate but with a lack of precision. Random error was quantified to approximately 17 km/h. The measurement error was dependent on the club type and was weakly negatively correlated to the magnitude of clubhead speed.

Inertial Navigation System/Doppler Velocity Log (INS/DVL Fusion with Partial DVL Measurements

Directory of Open Access Journals (Sweden)

Asaf Tal

2017-02-01

Full Text Available The Technion autonomous underwater vehicle (TAUV is an ongoing project aiming to develop and produce a small AUV to carry on research missions, including payload dropping, and to demonstrate acoustic communication. Its navigation system is based on an inertial navigation system (INS aided by a Doppler velocity log (DVL, magnetometer, and pressure sensor (PS. In many INSs, such as the one used in TAUV, only the velocity vector (provided by the DVL can be used for aiding the INS, i.e., enabling only a loosely coupled integration approach. In cases of partial DVL measurements, such as failure to maintain bottom lock, the DVL cannot estimate the vehicle velocity. Thus, in partial DVL situations no velocity data can be integrated into the TAUV INS, and as a result its navigation solution will drift in time. To circumvent that problem, we propose a DVL-based vehicle velocity solution using the measured partial raw data of the DVL and additional information, thereby deriving an extended loosely coupled (ELC approach. The implementation of the ELC approach requires only software modification. In addition, we present the TAUV six degrees of freedom (6DOF simulation that includes all functional subsystems. Using this simulation, the proposed approach is evaluated and the benefit of using it is shown.

A novel redundant INS based on triple rotary inertial measurement units

International Nuclear Information System (INIS)

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

2016-01-01

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. (paper)

A dead reckoning localization system for mobile robots using inertial sensors and wheel revolution encoding

Energy Technology Data Exchange (ETDEWEB)

Cho, Bong Su; Moon, Woo Sung; Seo, Woo Jin; Baek, Kwang Ryul [Pusan National University, Busan (Korea, Republic of)

2011-11-15

Inertial navigation systems (INS) are composed of inertial sensors, such as accelerometers and gyroscopes. An INS updates its orientation and position automatically; it has an acceptable stability over the short term, however this stability deteriorates over time. Odometry, used to estimate the position of a mobile robot, employs encoders attached to the robot's wheels. However, errors occur caused by the integrative nature of the rotating speed and the slippage between the wheel and the ground. In this paper, we discuss mobile robot position estimation without using external signals in indoor environments. In order to achieve optimal solutions, a Kalman filter that estimates the orientation and velocity of mobile robots has been designed. The proposed system combines INS and odometry and delivers more accurate position information than standalone odometry.

[Potential of using inertial sensors in high level sports].

Science.gov (United States)

Ruzova, T K; Andreev, D A; Shchukin, A I

2013-01-01

The article thoroughly covers development of wireless inertial sensors technology in medicine. The authors describe main criteria of diagnostic value of inertial sensors, advantages and prospects of using these systems in sports medicine, in comparison with other conventional methods of biomechanical examination in sports medicine. The results obtained necessitate further development of this approach, specifically creation of algorithms and methods of biomechanic examination of highly qualified athletes in high achievements sports.

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

NARCIS (Netherlands)

Weenk, D.; van Beijnum, Bernhard J.F.; Baten, Christian T.M.; Hermens, Hermanus J.; Veltink, Petrus H.

2013-01-01

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

Ultrasound-Aided Pedestrian Dead Reckoning for Indoor Navigation

NARCIS (Netherlands)

Fischer, C.; Kavitha Muthukrishnan, K.; Hazas, M.; Gellersen, H.

2008-01-01

Ad hoc solutions for tracking and providing navigation support to emergency response teams is an important and safety-critical challenge. We propose a navigation system based on a combination of foot-mounted inertial sensors and ultrasound beacons. We evaluate experimentally the performance of our

PERFORMANCE CHARACTERISTIC MEMS-BASED IMUs FOR UAVs NAVIGATION

Directory of Open Access Journals (Sweden)

H. A. Mohamed

2015-08-01

Full Text Available 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.

Performance Characteristic Mems-Based IMUs for UAVs Navigation

Science.gov (United States)

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.

A Pedestrian Dead Reckoning System Integrating Low-Cost MEMS Inertial Sensors and GPS Receiver

Directory of Open Access Journals (Sweden)

Jin-feng Li

2014-04-01

Full Text Available The body-mounted inertial systems for pedestrian navigation do not require any preinstalled facilities and can run autonomously. The advantages over other technologies make it especially attractive for the applications such as first responders, military and consumer markets. The hardware platform integrating the low-cost, low-power and small-size MEMS (micro-electro-mechanical systems inertial sensors and GPS (global positioning system receiver is proposed. When the satellite signals are available, the location of the pedestrian is directly obtained from the GPS receiver. The inertial sensors are the complement of the GPS receiver in places where the GPS signals are not available, such as indoors, urban canyons and places under dense foliages. The height tracking is achieved by the barometer. The proposed PDR (pedestrian dead reckoning algorithm is real-timely implemented in the platform. The simple but effective step detection and step length estimation method are realized to reduce the computation and memory requirements on the microprocessor. A complementary filter is proposed to fuse the data from the accelerometer, gyroscope and digital compass for decreasing the heading error, which is the main error source in positioning. The reliability and accuracy of the proposed system is verified by field pedestrian walking tests in outdoors and indoors. The positioning error is less than 4% of the total traveled distance. The results indicate that the pedestrian dead reckoning system is able to provide satisfactory tracking performance.

LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments

OpenAIRE

Tang, Jian; Chen, Yuwei; Niu, Xiaoji; Wang, Li; Chen, Liang; Liu, Jingbin; Shi, Chuang; Hyyppä, Juha

2015-01-01

A new scan that matches an aided Inertial Navigation System (INS) with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR) and Simultaneous Localization and Mapping (SLAM) technologies are normally used to estimate positions as separate tools. However, there are critical implementation problems with each standalone system. Th...

Suitability of Smartphone Inertial Sensors for Real-Time Biofeedback Applications

Science.gov (United States)

Kos, Anton; Tomažič, Sašo; Umek, Anton

2016-01-01

This article studies the suitability of smartphones with built-in inertial sensors for biofeedback applications. Biofeedback systems use various sensors to measure body functions and parameters. These sensor data are analyzed, and the results are communicated back to the user, who then tries to act on the feedback signals. Smartphone inertial sensors can be used to capture body movements in biomechanical biofeedback systems. These sensors exhibit various inaccuracies that induce significant angular and positional errors. We studied deterministic and random errors of smartphone accelerometers and gyroscopes, primarily focusing on their biases. Based on extensive measurements, we determined accelerometer and gyroscope noise models and bias variation ranges. Then, we compiled a table of predicted positional and angular errors under various biofeedback system operation conditions. We suggest several bias compensation options that are suitable for various examples of use in real-time biofeedback applications. Measurements within the developed experimental biofeedback application show that under certain conditions, even uncompensated sensors can be used for real-time biofeedback. For general use, especially for more demanding biofeedback applications, sensor biases should be compensated. We are convinced that real-time biofeedback systems based on smartphone inertial sensors are applicable to many similar examples in sports, healthcare, and other areas. PMID:26927125

Suitability of Smartphone Inertial Sensors for Real-Time Biofeedback Applications.

Science.gov (United States)

Kos, Anton; Tomažič, Sašo; Umek, Anton

2016-02-27

This article studies the suitability of smartphones with built-in inertial sensors for biofeedback applications. Biofeedback systems use various sensors to measure body functions and parameters. These sensor data are analyzed, and the results are communicated back to the user, who then tries to act on the feedback signals. Smartphone inertial sensors can be used to capture body movements in biomechanical biofeedback systems. These sensors exhibit various inaccuracies that induce significant angular and positional errors. We studied deterministic and random errors of smartphone accelerometers and gyroscopes, primarily focusing on their biases. Based on extensive measurements, we determined accelerometer and gyroscope noise models and bias variation ranges. Then, we compiled a table of predicted positional and angular errors under various biofeedback system operation conditions. We suggest several bias compensation options that are suitable for various examples of use in real-time biofeedback applications. Measurements within the developed experimental biofeedback application show that under certain conditions, even uncompensated sensors can be used for real-time biofeedback. For general use, especially for more demanding biofeedback applications, sensor biases should be compensated. We are convinced that real-time biofeedback systems based on smartphone inertial sensors are applicable to many similar examples in sports, healthcare, and other areas.

Inertial sensor-based methods in walking speed estimation: a systematic review.

Science.gov (United States)

Yang, Shuozhi; Li, Qingguo

2012-01-01

Self-selected walking speed is an important measure of ambulation ability used in various clinical gait experiments. Inertial sensors, i.e., accelerometers and gyroscopes, have been gradually introduced to estimate walking speed. This research area has attracted a lot of attention for the past two decades, and the trend is continuing due to the improvement of performance and decrease in cost of the miniature inertial sensors. With the intention of understanding the state of the art of current development in this area, a systematic review on the exiting methods was done in the following electronic engines/databases: PubMed, ISI Web of Knowledge, SportDiscus and IEEE Xplore. Sixteen journal articles and papers in proceedings focusing on inertial sensor based walking speed estimation were fully reviewed. The existing methods were categorized by sensor specification, sensor attachment location, experimental design, and walking speed estimation algorithm.

Inertial Sensor-Based Methods in Walking Speed Estimation: A Systematic Review

Directory of Open Access Journals (Sweden)

Qingguo Li

2012-05-01

Full Text Available Self-selected walking speed is an important measure of ambulation ability used in various clinical gait experiments. Inertial sensors, i.e., accelerometers and gyroscopes, have been gradually introduced to estimate walking speed. This research area has attracted a lot of attention for the past two decades, and the trend is continuing due to the improvement of performance and decrease in cost of the miniature inertial sensors. With the intention of understanding the state of the art of current development in this area, a systematic review on the exiting methods was done in the following electronic engines/databases: PubMed, ISI Web of Knowledge, SportDiscus and IEEE Xplore. Sixteen journal articles and papers in proceedings focusing on inertial sensor based walking speed estimation were fully reviewed. The existing methods were categorized by sensor specification, sensor attachment location, experimental design, and walking speed estimation algorithm.

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

Directory of Open Access Journals (Sweden)

Amedeo Rodi Vetrella

2016-12-01

Full Text Available 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.

Zero velocity interval detection based on a continuous hidden Markov model in micro inertial pedestrian navigation

Science.gov (United States)

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.

A polar-region-adaptable systematic bias collaborative measurement method for shipboard redundant rotational inertial navigation systems

Science.gov (United States)

Wang, Lin; Wu, Wenqi; Wei, Guo; Lian, Junxiang; Yu, Ruihang

2018-05-01

The shipboard redundant rotational inertial navigation system (RINS) configuration, including a dual-axis RINS and a single-axis RINS, can satisfy the demand of marine INSs of especially high reliability as well as achieving trade-off between position accuracy and cost. Generally, the dual-axis RINS is the master INS, and the single-axis RINS is the hot backup INS for high reliability purposes. An integrity monitoring system performs a fault detection function to ensure sailing safety. However, improving the accuracy of the backup INS in case of master INS failure has not been given enough attention. Without the aid of any external information, a systematic bias collaborative measurement method based on an augmented Kalman filter is proposed for the redundant RINSs. Estimates of inertial sensor biases can be used by the built-in integrity monitoring system to monitor the RINS running condition. On the other hand, a position error prediction model is designed for the single-axis RINS to estimate the systematic error caused by its azimuth gyro bias. After position error compensation, the position information provided by the single-axis RINS still remains highly accurate, even if the integrity monitoring system detects a dual-axis RINS fault. Moreover, use of a grid frame as a navigation frame makes the proposed method applicable in any area, including the polar regions. Semi-physical simulation and experiments including sea trials verify the validity of the method.

Application of inertial sensors for motion analysis

Directory of Open Access Journals (Sweden)

Ferenc Soha

2012-06-01

Full Text Available This paper presents our results on the application of various inertial sensors for motion analysis. After the introduction of different sensor types (accelerometer, gyroscope, magnetic field sensor, we discuss the possible data collection and transfer techniques using embedded signal processing and wireless data communication methods [1,2]. Special consideration is given to the interpretation of accelerometer readings, which contains both the static and dynamic components, and is affected by the orientation and rotation of the sensor. We will demonstrate the possibility to decompose these components for quasiperiodic motions. Finally we will demonstrate the application of commercially available devices (Wii sensor, Kinect sensor, mobile phone for motion analysis applications.

Doppler lidar sensor for precision navigation in GPS-deprived environment

Science.gov (United States)

Amzajerdian, F.; Pierrottet, D. F.; Hines, G. D.; Petway, L. B.; Barnes, B. W.

2013-05-01

Landing mission concepts that are being developed for exploration of solar system bodies are increasingly ambitious in their implementations and objectives. Most of these missions require accurate position and velocity data during their descent phase in order to ensure safe, soft landing at the pre-designated sites. Data from the vehicle's Inertial Measurement Unit will not be sufficient due to significant drift error after extended travel time in space. Therefore, an onboard sensor is required to provide the necessary data for landing in the GPS-deprived environment of space. For this reason, NASA Langley Research Center has been developing an advanced Doppler lidar sensor capable of providing accurate and reliable data suitable for operation in the highly constrained environment of space. The Doppler lidar transmits three laser beams in different directions toward the ground. The signal from each beam provides the platform velocity and range to the ground along the laser line-of-sight (LOS). The six LOS measurements are then combined in order to determine the three components of the vehicle velocity vector, and to accurately measure altitude and attitude angles relative to the local ground. These measurements are used by an autonomous Guidance, Navigation, and Control system to accurately navigate the vehicle from a few kilometers above the ground to the designated location and to execute a gentle touchdown. A prototype version of our lidar sensor has been completed for a closed-loop demonstration onboard a rocket-powered terrestrial free-flyer vehicle.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

3D-Calibration for IMU of the Strapdown Inertial Navigation Systems

Directory of Open Access Journals (Sweden)

Avrutov V.V.

2017-01-01

Full Text Available A new calibration method for Inertial Measurement Unit (IMU of Strapdown Iner-tial Navigation Systems was presented. IMU has been composed of accelerometers, gyroscopes and a circuit of signal processing. Normally, a rate transfer test and multi-position tests are us-ing for IMU calibration. The new calibration method is based on whole angle rotation or finite rotation. In fact it’s suggested to turn over IMU around three axes simultaneously. In order to solve the equation of calibration, it is necessary to provide an equality of a rank of basic matrix into degree of basic matrix. The results of simulated IMU data presented to demonstrate the performance of the new calibration method.

Navigation and Control of a Vehicle to the Parking Place Using Ins

Directory of Open Access Journals (Sweden)

Rastislav PIRNÍK

2015-11-01

Full Text Available This article discusses possibility of usage of the inertial navigation system for an autonomous navigation of a vehicle to the parking place inside intelligent parking house. Our research has shown that inertial navigation is suitable only for heading and attitude estimation. In order to achieve reliable and precise position estimation the additional odometer sensor is required. Article also describes control algorithm which can be used for steering control of the car according to pre-set waypoints. Waypoints have to be placed with respect to the dimensions and overall maneuverability of the vehicle.

Review of fall risk assessment in geriatric populations using inertial sensors

OpenAIRE

Howcroft, Jennifer; Kofman, Jonathan; Lemaire, Edward D

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 f...

Fundamentals of Inertial Navigation, Satellite-based Positioning and their Integration

CERN Document Server

Noureldin, Aboelmagd; Georgy, Jacques

2013-01-01

Fundamentals of Inertial Navigation, Satellite-based Positioning and their Integration is an introduction to the field of Integrated Navigation Systems. It serves as an excellent reference for working engineers as well as textbook for beginners and students new to the area. The book is easy to read and understand with minimum background knowledge. The authors explain the derivations in great detail. The intermediate steps are thoroughly explained so that a beginner can easily follow the material. The book shows a step-by-step implementation of navigation algorithms and provides all the necessary details. It provides detailed illustrations for an easy comprehension. The book also demonstrates real field experiments and in-vehicle road test results with professional discussions and analysis. This work is unique in discussing the different INS/GPS integration schemes in an easy to understand and straightforward way. Those schemes include loosely vs tightly coupled, open loop vs closed loop, and many more.

Comparison of robust H∞ filter and Kalman filter for initial alignment of inertial navigation system

Institute of Scientific and Technical Information of China (English)

HAO Yan-ling; CHEN Ming-hui; LI Liang-jun; XU Bo

2008-01-01

There are many filtering methods that can be used for the initial alignment of an integrated inertial navigation system.This paper discussed the use of GPS,but focused on two kinds of filters for the initial alignment of an integrated strapdown inertial navigation system (SINS).One method is based on the Kalman filter (KF),and the other is based on the robust filter.Simulation results showed that the filter provides a quick transient response and a little more accurate estimate than KF,given substantial process noise or unknown noise statistics.So the robust filter is an effective and useful method for initial alignment of SINS.This research should make the use of SINS more popular,and is also a step for further research.

Review of fall risk assessment in geriatric populations using inertial sensors

Science.gov (United States)

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

Gravity Matching Aided Inertial Navigation Technique Based on Marginal Robust Unscented Kalman Filter

Directory of Open Access Journals (Sweden)

Ming Liu

2015-01-01

Full Text Available This paper is concerned with the topic of gravity matching aided inertial navigation technology using Kalman filter. The dynamic state space model for Kalman filter is constructed as follows: the error equation of the inertial navigation system is employed as the process equation while the local gravity model based on 9-point surface interpolation is employed as the observation equation. The unscented Kalman filter is employed to address the nonlinearity of the observation equation. The filter is refined in two ways as follows. The marginalization technique is employed to explore the conditionally linear substructure to reduce the computational load; specifically, the number of the needed sigma points is reduced from 15 to 5 after this technique is used. A robust technique based on Chi-square test is employed to make the filter insensitive to the uncertainties in the above constructed observation model. Numerical simulation is carried out, and the efficacy of the proposed method is validated by the simulation results.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Lightweight, Miniature Inertial Measurement System

Science.gov (United States)

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.

INS integrated motion analysis for autonomous vehicle navigation

Science.gov (United States)

Roberts, Barry; Bazakos, Mike

1991-01-01

The use of inertial navigation system (INS) measurements to enhance the quality and robustness of motion analysis techniques used for obstacle detection is discussed with particular reference to autonomous vehicle navigation. The approach to obstacle detection used here employs motion analysis of imagery generated by a passive sensor. Motion analysis of imagery obtained during vehicle travel is used to generate range measurements to points within the field of view of the sensor, which can then be used to provide obstacle detection. Results obtained with an INS integrated motion analysis approach are reviewed.

Flight results of attitude matching between Space Shuttle and Inertial Upper Stage (IUS) navigation systems

Science.gov (United States)

Treder, Alfred J.; Meldahl, Keith L.

The recorded histories of Shuttle/Orbiter attitude and Inertial Upper Stage (IUS) attitude have been analyzed for all joint flights of the IUS in the Orbiter. This database was studied to determine the behavior of relative alignment between the IUS and Shuttle navigation systems. It is found that the overall accuracy of physical alignment has a Shuttle Orbiter bias component less than 5 arcmin/axis and a short-term stability upper bound of 0.5 arcmin/axis, both at 1 sigma. Summaries of the experienced physical and inertial alginment offsets are shown in this paper, together with alignment variation data, illustrated with some flight histories. Also included is a table of candidate values for some error source groups in an Orbiter/IUS attitude errror model. Experience indicates that the Shuttle is much more accurate and stable as an orbiting launch platform than has so far been advertised. This information will be valuable for future Shuttle payloads, especially those (such as the Aeroassisted Flight Experiment) which carry their own inertial navigation systems, and which could update or initialize their attitude determination systems using the Shuttle as the reference.

Fusion Based on Visible Light Positioning and Inertial Navigation Using Extended Kalman Filters.

Science.gov (United States)

Li, Zhitian; Feng, Lihui; Yang, Aiying

2017-05-11

With the rapid development of smart technology, the need for location-based services (LBS) increases every day. Since classical positioning technology such as GPS cannot satisfy the needs of indoor positioning, new indoor positioning technologies, such as Bluetooth, Wi-Fi, and Visible light communication (VLC), have already cut a figure. VLC positioning has been proposed because it has higher accuracy, costs less, and is easier to accomplish in comparison to the other indoor positioning technologies. However, the practicality of VLC positioning is limited since it is easily affected by multipath effects and the layout of LEDs. Thus, we propose a fusion positioning system based on extended Kalman filters, which can fuse the VLC position and the inertial navigation data. The accuracy of the fusion positioning system is in centimeters, which is better compared to the VLC-based positioning or inertial navigation alone. Furthermore, the fusion positioning system has high accuracy, saves energy, costs little, and is easy to install, making it a promising candidate for future indoor positioning applications.

Inertial Sensor Error Reduction through Calibration and Sensor Fusion

Directory of Open Access Journals (Sweden)

Stefan Lambrecht

2016-02-01

Full Text Available 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.

Architectural elements of hybrid navigation systems for future space transportation

Science.gov (United States)

Trigo, Guilherme F.; Theil, Stephan

2017-12-01

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.

Architectural elements of hybrid navigation systems for future space transportation

Science.gov (United States)

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.

Wellbore inertial navigation system (WINS) software development and test results

Energy Technology Data Exchange (ETDEWEB)

Wardlaw, R. Jr.

1982-09-01

The structure and operation of the real-time software developed for the Wellbore Inertial Navigation System (WINS) application are described. The procedure and results of a field test held in a 7000-ft well in the Nevada Test Site are discussed. Calibration and instrumentation error compensation are outlined, as are design improvement areas requiring further test and development. Notes on Kalman filtering and complete program listings of the real-time software are included in the Appendices. Reference is made to a companion document which describes the downhole instrumentation package.

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

Science.gov (United States)

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

LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments.

Science.gov (United States)

Tang, Jian; Chen, Yuwei; Niu, Xiaoji; Wang, Li; Chen, Liang; Liu, Jingbin; Shi, Chuang; Hyyppä, Juha

2015-07-10

A new scan that matches an aided Inertial Navigation System (INS) with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR) and Simultaneous Localization and Mapping (SLAM) technologies are normally used to estimate positions as separate tools. However, there are critical implementation problems with each standalone system. The drift errors of velocity, position, and heading angles in an INS will accumulate over time, and on-line calibration is a must for sustaining positioning accuracy. SLAM performance is poor in featureless environments where the matching errors can significantly increase. Each standalone positioning method cannot offer a sustainable navigation solution with acceptable accuracy. This paper integrates two complementary technologies-INS and LiDAR SLAM-into one navigation frame with a loosely coupled Extended Kalman Filter (EKF) to use the advantages and overcome the drawbacks of each system to establish a stable long-term navigation process. Static and dynamic field tests were carried out with a self-developed Unmanned Ground Vehicle (UGV) platform-NAVIS. The results prove that the proposed approach can provide positioning accuracy at the centimetre level for long-term operations, even in a featureless indoor environment.

Wide-Bandwidth, Ultra-Accurate, Composite Inertial Reference Sensor, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Applied Technology Associates (ATA) proposes to develop a new inertial sensor by combining two sensing phenomena in a single device. ATA has patented an advanced...

Laboratory measurements of grain-bedrock interactions using inertial sensors.

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Directory of Open Access Journals (Sweden)

Jacques Georgy

2011-04-01

Full Text Available 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

Estimating the orientation of a rigid body moving in space using inertial sensors

Energy Technology Data Exchange (ETDEWEB)

He, Peng, E-mail: peng.he.1@ulaval.ca; Cardou, Philippe, E-mail: pcardou@gmc.ulaval.ca [Université Laval, Robotics Laboratory, Department of Mechanical Engineering (Canada); Desbiens, André, E-mail: andre.desbiens@gel.ulaval.ca [Université Laval, Department of Electrical and Computer Engineering (Canada); Gagnon, Eric, E-mail: Eric.Gagnon@drdc-rddc.gc.ca [RDDC Valcartier (Canada)

2015-09-15

This paper presents a novel method of estimating the orientation of a rigid body moving in space from inertial sensors, by discerning the gravitational and inertial components of the accelerations. In this method, both a rigid-body kinematics model and a stochastic model of the human-hand motion are formulated and combined in a nonlinear state-space system. The state equation represents the rigid body kinematics and stochastic model, and the output equation represents the inertial sensor measurements. It is necessary to mention that, since the output equation is a nonlinear function of the state, the extended Kalman filter (EKF) is applied. The absolute value of the error from the proposed method is shown to be less than 5 deg in simulation and in experiments. It is apparently stable, unlike the time-integration of gyroscope measurements, which is subjected to drift, and remains accurate under large accelerations, unlike the tilt-sensor method.

Estimating the orientation of a rigid body moving in space using inertial sensors

International Nuclear Information System (INIS)

He, Peng; Cardou, Philippe; Desbiens, André; Gagnon, Eric

2015-01-01

This paper presents a novel method of estimating the orientation of a rigid body moving in space from inertial sensors, by discerning the gravitational and inertial components of the accelerations. In this method, both a rigid-body kinematics model and a stochastic model of the human-hand motion are formulated and combined in a nonlinear state-space system. The state equation represents the rigid body kinematics and stochastic model, and the output equation represents the inertial sensor measurements. It is necessary to mention that, since the output equation is a nonlinear function of the state, the extended Kalman filter (EKF) is applied. The absolute value of the error from the proposed method is shown to be less than 5 deg in simulation and in experiments. It is apparently stable, unlike the time-integration of gyroscope measurements, which is subjected to drift, and remains accurate under large accelerations, unlike the tilt-sensor method

Analysis of Indoor Rowing Motion using Wearable Inertial Sensors

NARCIS (Netherlands)

Bosch, S.; Shoaib, M.; Geerlings, Stephen; Buit, Lennart; Meratnia, Nirvana; Havinga, Paul J.M.

2015-01-01

In this exploratory work the motion of rowers is analyzed while rowing on a rowing machine. This is performed using inertial sensors that measure the orientation at several positions on the body. Using these measurements, this work provides a preliminary analysis of the differences between

Sampling and Control Circuit Board for an Inertial Measurement Unit

Science.gov (United States)

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

Camera-marker and inertial sensor fusion for improved motion tracking

NARCIS (Netherlands)

Roetenberg, D.; Veltink, P.H.

2005-01-01

A method for combining a camera-marker based motion analysis system with miniature inertial sensors is proposed. It is used to fill gaps of optical data and can increase the data rate of the optical system.

LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments

Directory of Open Access Journals (Sweden)

Jian Tang

2015-07-01

Full Text Available A new scan that matches an aided Inertial Navigation System (INS with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR and Simultaneous Localization and Mapping (SLAM technologies are normally used to estimate positions as separate tools. However, there are critical implementation problems with each standalone system. The drift errors of velocity, position, and heading angles in an INS will accumulate over time, and on-line calibration is a must for sustaining positioning accuracy. SLAM performance is poor in featureless environments where the matching errors can significantly increase. Each standalone positioning method cannot offer a sustainable navigation solution with acceptable accuracy. This paper integrates two complementary technologies—INS and LiDAR SLAM—into one navigation frame with a loosely coupled Extended Kalman Filter (EKF to use the advantages and overcome the drawbacks of each system to establish a stable long-term navigation process. Static and dynamic field tests were carried out with a self-developed Unmanned Ground Vehicle (UGV platform—NAVIS. The results prove that the proposed approach can provide positioning accuracy at the centimetre level for long-term operations, even in a featureless indoor environment.

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

Science.gov (United States)

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 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.

Modeling and Experimental Study on Characterization of Micromachined Thermal Gas Inertial Sensors

Directory of Open Access Journals (Sweden)

Yan Su

2010-09-01

Full Text Available 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.

Systematic Calibration for Ultra-High Accuracy Inertial Measurement Units

Directory of Open Access Journals (Sweden)

Qingzhong Cai

2016-06-01

Full Text Available 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.

FPGA-based real-time embedded system for RISS/GPS integrated navigation.

Science.gov (United States)

Abdelfatah, Walid Farid; Georgy, Jacques; Iqbal, Umar; Noureldin, Aboelmagd

2012-01-01

Navigation algorithms integrating measurements from multi-sensor systems overcome the problems that arise from using GPS navigation systems in standalone mode. Algorithms which integrate the data from 2D low-cost reduced inertial sensor system (RISS), consisting of a gyroscope and an odometer or wheel encoders, along with a GPS receiver via a Kalman filter has proved to be worthy in providing a consistent and more reliable navigation solution compared to standalone GPS receivers. It has been also shown to be beneficial, especially in GPS-denied environments such as urban canyons and tunnels. The main objective of this paper is to narrow the idea-to-implementation gap that follows the algorithm development by realizing a low-cost real-time embedded navigation system capable of computing the data-fused positioning solution. The role of the developed system is to synchronize the measurements from the three sensors, relative to the pulse per second signal generated from the GPS, after which the navigation algorithm is applied to the synchronized measurements to compute the navigation solution in real-time. Employing a customizable soft-core processor on an FPGA in the kernel of the navigation system, provided the flexibility for communicating with the various sensors and the computation capability required by the Kalman filter integration algorithm.

Ultrasensitive Inertial and Force Sensors with Diamagnetically Levitated Magnets

Science.gov (United States)

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.

Fusing inertial sensor data in an extended Kalman filter for 3D camera tracking.

Science.gov (United States)

Erdem, Arif Tanju; Ercan, Ali Özer

2015-02-01

In a setup where camera measurements are used to estimate 3D egomotion in an extended Kalman filter (EKF) framework, it is well-known that inertial sensors (i.e., accelerometers and gyroscopes) are especially useful when the camera undergoes fast motion. Inertial sensor data can be fused at the EKF with the camera measurements in either the correction stage (as measurement inputs) or the prediction stage (as control inputs). In general, only one type of inertial sensor is employed in the EKF in the literature, or when both are employed they are both fused in the same stage. In this paper, we provide an extensive performance comparison of every possible combination of fusing accelerometer and gyroscope data as control or measurement inputs using the same data set collected at different motion speeds. In particular, we compare the performances of different approaches based on 3D pose errors, in addition to camera reprojection errors commonly found in the literature, which provides further insight into the strengths and weaknesses of different approaches. We show using both simulated and real data that it is always better to fuse both sensors in the measurement stage and that in particular, accelerometer helps more with the 3D position tracking accuracy, whereas gyroscope helps more with the 3D orientation tracking accuracy. We also propose a simulated data generation method, which is beneficial for the design and validation of tracking algorithms involving both camera and inertial measurement unit measurements in general.

Fault-tolerant Sensor Fusion for Marine Navigation

DEFF Research Database (Denmark)

Blanke, Mogens

2006-01-01

Reliability of navigation data are critical for steering and manoeuvring control, and in particular so at high speed or in critical phases of a mission. Should faults occur, faulty instruments need be autonomously isolated and faulty information discarded. This paper designs a navigation solution...... where essential navigation information is provided even with multiple faults in instrumentation. The paper proposes a provable correct implementation through auto-generated state-event logics in a supervisory part of the algorithms. Test results from naval vessels document the performance and shows...... events where the fault-tolerant sensor fusion provided uninterrupted navigation data despite temporal instrument defects...

Tactile object exploration using cursor navigation sensors

DEFF Research Database (Denmark)

Kraft, Dirk; Bierbaum, Alexander; Kjaergaard, Morten

2009-01-01

In robotic applications tactile sensor systems serve the purpose of localizing a contact point and measuring contact forces. We have investigated the applicability of a sensorial device commonly used in cursor navigation technology for tactile sensing in robotics. We show the potential of this se......In robotic applications tactile sensor systems serve the purpose of localizing a contact point and measuring contact forces. We have investigated the applicability of a sensorial device commonly used in cursor navigation technology for tactile sensing in robotics. We show the potential...... of this sensor for active haptic exploration. More specifically, we present experiments and results which demonstrate the extraction of relevant object properties such as local shape, weight and elasticity using this technology. Besides its low price due to mass production and its modularity, an interesting...... aspect of this sensor is that beside a localization of contact points and measurement of the contact normal force also shear forces can be measured. This is relevant for many applications such as surface normal estimation and weight measurements. Scalable tactile sensor arrays have been developed...

A novel visual-inertial monocular SLAM

Science.gov (United States)

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.

Gravity Compensation Using EGM2008 for High-Precision Long-Term Inertial Navigation Systems

Directory of Open Access Journals (Sweden)

Ruonan Wu

2016-12-01

Full Text Available The gravity disturbance vector is one of the major error sources in high-precision and long-term inertial navigation applications. Specific to the inertial navigation systems (INSs with high-order horizontal damping networks, analyses of the error propagation show that the gravity-induced errors exist almost exclusively in the horizontal channels and are mostly caused by deflections of the vertical (DOV. Low-frequency components of the DOV propagate into the latitude and longitude errors at a ratio of 1:1 and time-varying fluctuations in the DOV excite Schuler oscillation. This paper presents two gravity compensation methods using the Earth Gravitational Model 2008 (EGM2008, namely, interpolation from the off-line database and computing gravity vectors directly using the spherical harmonic model. Particular attention is given to the error contribution of the gravity update interval and computing time delay. It is recommended for the marine navigation that a gravity vector should be calculated within 1 s and updated every 100 s at most. To meet this demand, the time duration of calculating the current gravity vector using EGM2008 has been reduced to less than 1 s by optimizing the calculation procedure. A few off-line experiments were conducted using the data of a shipborne INS collected during an actual sea test. With the aid of EGM2008, most of the low-frequency components of the position errors caused by the gravity disturbance vector have been removed and the Schuler oscillation has been attenuated effectively. In the rugged terrain, the horizontal position error could be reduced at best 48.85% of its regional maximum. The experimental results match with the theoretical analysis and indicate that EGM2008 is suitable for gravity compensation of the high-precision and long-term INSs.

Gravity Compensation Using EGM2008 for High-Precision Long-Term Inertial Navigation Systems.

Science.gov (United States)

Wu, Ruonan; Wu, Qiuping; Han, Fengtian; Liu, Tianyi; Hu, Peida; Li, Haixia

2016-12-18

The gravity disturbance vector is one of the major error sources in high-precision and long-term inertial navigation applications. Specific to the inertial navigation systems (INSs) with high-order horizontal damping networks, analyses of the error propagation show that the gravity-induced errors exist almost exclusively in the horizontal channels and are mostly caused by deflections of the vertical (DOV). Low-frequency components of the DOV propagate into the latitude and longitude errors at a ratio of 1:1 and time-varying fluctuations in the DOV excite Schuler oscillation. This paper presents two gravity compensation methods using the Earth Gravitational Model 2008 (EGM2008), namely, interpolation from the off-line database and computing gravity vectors directly using the spherical harmonic model. Particular attention is given to the error contribution of the gravity update interval and computing time delay. It is recommended for the marine navigation that a gravity vector should be calculated within 1 s and updated every 100 s at most. To meet this demand, the time duration of calculating the current gravity vector using EGM2008 has been reduced to less than 1 s by optimizing the calculation procedure. A few off-line experiments were conducted using the data of a shipborne INS collected during an actual sea test. With the aid of EGM2008, most of the low-frequency components of the position errors caused by the gravity disturbance vector have been removed and the Schuler oscillation has been attenuated effectively. In the rugged terrain, the horizontal position error could be reduced at best 48.85% of its regional maximum. The experimental results match with the theoretical analysis and indicate that EGM2008 is suitable for gravity compensation of the high-precision and long-term INSs.

Performance Evaluation and Requirements Assessment for Gravity Gradient Referenced Navigation

Directory of Open Access Journals (Sweden)

Jisun Lee

2015-07-01

Full Text Available In this study, simulation tests for gravity gradient referenced navigation (GGRN are conducted to verify the effects of various factors such as database (DB and sensor errors, flight altitude, DB resolution, initial errors, and measurement update rates on the navigation performance. Based on the simulation results, requirements for GGRN are established for position determination with certain target accuracies. It is found that DB and sensor errors and flight altitude have strong effects on the navigation performance. In particular, a DB and sensor with accuracies of 0.1 E and 0.01 E, respectively, are required to determine the position more accurately than or at a level similar to the navigation performance of terrain referenced navigation (TRN. In most cases, the horizontal position error of GGRN is less than 100 m. However, the navigation performance of GGRN is similar to or worse than that of a pure inertial navigation system when the DB and sensor errors are 3 E or 5 E each and the flight altitude is 3000 m. Considering that the accuracy of currently available gradiometers is about 3 E or 5 E, GGRN does not show much advantage over TRN at present. However, GGRN is expected to exhibit much better performance in the near future when accurate DBs and gravity gradiometer are available.

Unmanned Ground Vehicle Navigation and Coverage Hole Patching in Wireless Sensor Networks

Science.gov (United States)

Zhang, Guyu

2013-01-01

This dissertation presents a study of an Unmanned Ground Vehicle (UGV) navigation and coverage hole patching in coordinate-free and localization-free Wireless Sensor Networks (WSNs). Navigation and coverage maintenance are related problems since coverage hole patching requires effective navigation in the sensor network environment. A…

Feature and Pose Constrained Visual Aided Inertial Navigation for Computationally Constrained Aerial Vehicles

Science.gov (United States)

Williams, Brian; Hudson, Nicolas; Tweddle, Brent; Brockers, Roland; Matthies, Larry

2011-01-01

A Feature and Pose Constrained Extended Kalman Filter (FPC-EKF) is developed for highly dynamic computationally constrained micro aerial vehicles. Vehicle localization is achieved using only a low performance inertial measurement unit and a single camera. The FPC-EKF framework augments the vehicle's state with both previous vehicle poses and critical environmental features, including vertical edges. This filter framework efficiently incorporates measurements from hundreds of opportunistic visual features to constrain the motion estimate, while allowing navigating and sustained tracking with respect to a few persistent features. In addition, vertical features in the environment are opportunistically used to provide global attitude references. Accurate pose estimation is demonstrated on a sequence including fast traversing, where visual features enter and exit the field-of-view quickly, as well as hover and ingress maneuvers where drift free navigation is achieved with respect to the environment.

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

Science.gov (United States)

Song, Jin Woo; Park, Chan Gook

2018-04-21

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.

Indoor Smartphone Navigation Using a Combination of Wi-Fi and Inertial Navigation with Intelligent Checkpoints

Science.gov (United States)

Hofer, H.; Retscher, G.

2017-09-01

For Wi-Fi positioning location fingerprinting is one of the most commonly employed localization technique. To achieve an acceptable level of positioning accuracy on the few meter level, i.e., to provide at least room resolution in buildings, such an approach is very labour consuming as it requires a high density of reference points. Thus, the novel approach developed aims at a significant reduction of workload for the training phase. The basic idea is to intelligently choose waypoints along possible users' trajectories in the indoor environment. These waypoints are termed intelligent checkpoints (iCPs) and serve as reference points for the fingerprinting localization approach. They are selected along the trajectories in such a way that they define a logical sequence with their ascending order. Thereby, the iCPs are located, for instance, at doors at entrances to buildings, rooms, along corridors, etc., or in low density along the trajectory to provide a suitable absolute user localization. Continuous positioning between these iCPs is obtained with the help of the smartphones' inertial sensors. While walking along a selected trajectory to the destination a dynamic recognition of the iCPs is performed and the drift of the inertial sensors is reduced as the iCP recognition serves as absolute position update. Conducted experiments in a multi-storey office building have shown that positioning accuracy of around 2.0 m are achievable which goes along with a reduction of workload by three quarter using this novel approach. The iCP concept and performance are presented and demonstrated in this paper.

A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults

OpenAIRE

Rui Sun; Qi Cheng; Guanyu Wang; Washington Yotto Ochieng

2017-01-01

The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs’ flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in ...

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

Science.gov (United States)

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

Indoor integrated navigation and synchronous data acquisition method for Android smartphone

Science.gov (United States)

Hu, Chunsheng; Wei, Wenjian; Qin, Shiqiao; Wang, Xingshu; Habib, Ayman; Wang, Ruisheng

2015-08-01

Smartphones are widely used at present. Most smartphones have cameras and kinds of sensors, such as gyroscope, accelerometer and magnet meter. Indoor navigation based on smartphone is very important and valuable. According to the features of the smartphone and indoor navigation, a new indoor integrated navigation method is proposed, which uses MEMS (Micro-Electro-Mechanical Systems) IMU (Inertial Measurement Unit), camera and magnet meter of smartphone. The proposed navigation method mainly involves data acquisition, camera calibration, image measurement, IMU calibration, initial alignment, strapdown integral, zero velocity update and integrated navigation. Synchronous data acquisition of the sensors (gyroscope, accelerometer and magnet meter) and the camera is the base of the indoor navigation on the smartphone. A camera data acquisition method is introduced, which uses the camera class of Android to record images and time of smartphone camera. Two kinds of sensor data acquisition methods are introduced and compared. The first method records sensor data and time with the SensorManager of Android. The second method realizes open, close, data receiving and saving functions in C language, and calls the sensor functions in Java language with JNI interface. A data acquisition software is developed with JDK (Java Development Kit), Android ADT (Android Development Tools) and NDK (Native Development Kit). The software can record camera data, sensor data and time at the same time. Data acquisition experiments have been done with the developed software and Sumsang Note 2 smartphone. The experimental results show that the first method of sensor data acquisition is convenient but lost the sensor data sometimes, the second method is much better in real-time performance and much less in data losing. A checkerboard image is recorded, and the corner points of the checkerboard are detected with the Harris method. The sensor data of gyroscope, accelerometer and magnet meter have

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

Science.gov (United States)

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.

Assessment of the pivot shift using inertial sensors

OpenAIRE

Zaffagnini, Stefano; Signorelli, Cecilia; Grassi, Alberto; Yue, Han; Raggi, Federico; Urrizola, Francisco; Bonanzinga, Tommaso; Marcacci, Maurilio

2016-01-01

The pivot shift test is an important clinical tool used to assess the stability of the knee following an injury to the anterior cruciate ligament (ACL). Previous studies have shown that significant variability exists in the performance and interpretation of this manoeuvre. Accordingly, a variety of techniques aimed at standardizing and quantifying the pivot shift test have been developed. In recent years, inertial sensors have been used to measure the kinematics of the pivot shift. The goal o...

Ambulatory gait analysis in stroke patients using ultrasound and inertial sensors

NARCIS (Netherlands)

Weenk, D.; van Meulen, Fokke; van Beijnum, Bernhard J.F.; Veltink, Petrus H.

2014-01-01

Objective ambulatory assessment of movements of patients is important for an optimal recovery. In this study an ambulatory system is used for assessing gait parameters in stroke patients. Ultrasound range estimates are fused with inertial sensors using an extended Kalman filter to estimate 3D

Magnetic distortion in motion labs, implications for validating inertial magnetic sensors

NARCIS (Netherlands)

de Vries, W.H.; Veeger, H.E.J.; Baten, C.T.M.; Helm, F.C.

2009-01-01

Background: Ambulatory 3D orientation estimation with Inertial Magnetic Sensor Units (IMU's) use the earth magnetic field. The magnitude of distortion in orientation in a standard equipped motion lab and its effect on the accuracy of the orientation estimation with IMU's is addressed. Methods:

Magnetic distortion in motion labs, implications for validating inertial magnetic sensors.

NARCIS (Netherlands)

Vries, W.H. de; Veeger, H.E.; Baten, C.T.; Helm, F.C.T. van der

2009-01-01

BACKGROUND: Ambulatory 3D orientation estimation with Inertial Magnetic Sensor Units (IMU's) use the earth magnetic field. The magnitude of distortion in orientation in a standard equipped motion lab and its effect on the accuracy of the orientation estimation with IMU's is addressed. METHODS:

Design and testing of a multi-sensor pedestrian location and navigation platform.

Science.gov (United States)

Morrison, Aiden; Renaudin, Valérie; Bancroft, Jared B; Lachapelle, Gérard

2012-01-01

Navigation and location technologies are continually advancing, allowing ever higher accuracies and operation under ever more challenging conditions. The development of such technologies requires the rapid evaluation of a large number of sensors and related utilization strategies. The integration of Global Navigation Satellite Systems (GNSSs) such as the Global Positioning System (GPS) with accelerometers, gyros, barometers, magnetometers and other sensors is allowing for novel applications, but is hindered by the difficulties to test and compare integrated solutions using multiple sensor sets. In order to achieve compatibility and flexibility in terms of multiple sensors, an advanced adaptable platform is required. This paper describes the design and testing of the NavCube, a multi-sensor navigation, location and timing platform. The system provides a research tool for pedestrian navigation, location and body motion analysis in an unobtrusive form factor that enables in situ data collections with minimal gait and posture impact. Testing and examples of applications of the NavCube are provided.

Observability-Based Guidance and Sensor Placement

Science.gov (United States)

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.

A new method for determining which stars are near a star sensor field-of-view

Science.gov (United States)

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.

77 FR 42419 - Airworthiness Directives; Honeywell International, Inc. Global Navigation Satellite Sensor Units

Science.gov (United States)

2012-07-19

... Airworthiness Directives; Honeywell International, Inc. Global Navigation Satellite Sensor Units AGENCY: Federal.... Model KGS200 Mercury\\2\\ wide area augmentation system (WAAS) global navigation satellite sensor units... similar Honeywell global positioning system (GPS) sensor and the same software as the Model KGS200 Mercury...

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Jin-Chun Piao

2017-11-01

Full Text Available 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.

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

Science.gov (United States)

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

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

Directory of Open Access Journals (Sweden)

Gaddi Blumrosen

2013-08-01

Full Text Available 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.

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

Science.gov (United States)

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

In-motion initial alignment and positioning with INS/CNS/ODO integrated navigation system for lunar rovers

Science.gov (United States)

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

2017-06-01

Many countries have been paying great attention to space exploration, especially about the Moon and the Mars. Autonomous and high-accuracy navigation systems are needed for probers and rovers to accomplish missions. Inertial navigation system (INS)/celestial navigation system (CNS) based navigation system has been used widely on the lunar rovers. Initialization is a particularly important step for navigation. This paper presents an in-motion alignment and positioning method for lunar rovers by INS/CNS/odometer integrated navigation. The method can estimate not only the position and attitude errors, but also the biases of the accelerometers and gyros using the standard Kalman filter. The differences between the platform star azimuth, elevation angles and the computed star azimuth, elevation angles, and the difference between the velocity measured by odometer and the velocity measured by inertial sensors are taken as measurements. The semi-physical experiments are implemented to demonstrate that the position error can reduce to 10 m and attitude error is within 2″ during 5 min. The experiment results prove that it is an effective and attractive initialization approach for lunar rovers.

A Bionic Polarization Navigation Sensor and Its Calibration Method.

Science.gov (United States)

Zhao, Huijie; Xu, Wujian

2016-08-03

The polarization patterns of skylight which arise due to the scattering of sunlight in the atmosphere can be used by many insects for deriving compass information. Inspired by insects' polarized light compass, scientists have developed a new kind of navigation method. One of the key techniques in this method is the polarimetric sensor which is used to acquire direction information from skylight. In this paper, a polarization navigation sensor is proposed which imitates the working principles of the polarization vision systems of insects. We introduce the optical design and mathematical model of the sensor. In addition, a calibration method based on variable substitution and non-linear curve fitting is proposed. The results obtained from the outdoor experiments provide support for the feasibility and precision of the sensor. The sensor's signal processing can be well described using our mathematical model. A relatively high degree of accuracy in polarization measurement can be obtained without any error compensation.

Inertial sensor-based smoother for gait analysis.

Science.gov (United States)

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).

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

Science.gov (United States)

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.

Absolute Navigation Performance of the Orion Exploration Fight Test 1

Science.gov (United States)

Zanetti, Renato; Holt, Greg; Gay, Robert; D'Souza, Christopher; Sud, Jastesh

2016-01-01

Launched in December 2014 atop a Delta IV Heavy from the Kennedy Space Center, the Orion vehicle's Exploration Flight Test-1 (EFT-1) successfully completed the objective to stress the system by placing the un-crewed vehicle on a high-energy parabolic trajectory replicating conditions similar to those that would be experienced when returning from an asteroid or a lunar mission. Unique challenges associated with designing the navigation system for EFT-1 are presented with an emphasis on how redundancy and robustness influenced the architecture. Two Inertial Measurement Units (IMUs), one GPS receiver and three barometric altimeters (BALTs) comprise the navigation sensor suite. The sensor data is multiplexed using conventional integration techniques and the state estimate is refined by the GPS pseudorange and deltarange measurements in an Extended Kalman Filter (EKF) that employs UDU factorization. The performance of the navigation system during flight is presented to substantiate the design.

Assessment of modern smartphone sensors performance on vehicle localization in urban environments

Science.gov (United States)

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.

Inertial Navigation System for India's Reusable Launch Vehicle-Technology Demonstrator (RLV-TD HEX) Mission

Science.gov (United States)

Umadevi, P.; Navas, A.; Karuturi, Kesavabrahmaji; Shukkoor, A. Abdul; Kumar, J. Krishna; Sreekumar, Sreejith; Basim, A. Mohammed

2017-12-01

This work presents the configuration of Inertial Navigation System (INS) used in India's Reusable Launch Vehicle-Technology Demonstrator (RLV-TD) Program. In view of the specific features and requirements of the RLV-TD, specific improvements and modifications were required in the INS. A new system was designed, realised and qualified meeting the mission requirements of RLV-TD, at the same time taking advantage of the flight heritage attained in INS through various Launch vehicle Missions of the country. The new system has additional redundancy in acceleration channel, in-built inclinometer based bias update scheme for acceleration channels and sign conventions as employed in an aircraft. Data acquisition in micro cycle periodicity (10 ms) was incorporated which was required to provide rate and attitude information at higher sampling rate for ascent phase control. Provision was incorporated for acquisition of rate and acceleration data with high resolution for aerodynamic characterisation and parameter estimation. GPS aided navigation scheme was incorporated to meet the stringent accuracy requirements of the mission. Navigation system configuration for RLV-TD, specific features incorporated to meet the mission requirements, various tests carried out and performance during RLV-TD flight are highlighted.

Low Cost Multisensor Kinematic Positioning and Navigation System with Linux/RTAI

Directory of Open Access Journals (Sweden)

Baoxin Hu

2012-09-01

Full Text Available Despite its popularity, the development of an embedded real-time multisensor kinematic positioning and navigation system discourages many researchers and developers due to its complicated hardware environment setup and time consuming device driver development. To address these issues, this paper proposed a multisensor kinematic positioning and navigation system built on Linux with Real Time Application Interface (RTAI, which can be constructed in a fast and economical manner upon popular hardware platforms. The authors designed, developed, evaluated and validated the application of Linux/RTAI in the proposed system for the integration of the low cost MEMS IMU and OEM GPS sensors. The developed system with Linux/RTAI as the core of a direct geo-referencing system provides not only an excellent hard real-time performance but also the conveniences for sensor hardware integration and real-time software development. A software framework is proposed in this paper for a universal kinematic positioning and navigation system with loosely-coupled integration architecture. In addition, general strategies of sensor time synchronization in a multisensor system are also discussed. The success of the loosely-coupled GPS-aided inertial navigation Kalman filter is represented via post-processed solutions from road tests.

Information Potential Fields Navigation in Wireless Ad-Hoc Sensor Networks

Directory of Open Access Journals (Sweden)

Yong Qi

2011-05-01

Full Text Available As wireless sensor networks (WSNs are increasingly being deployed in some important applications, it becomes imperative that we consider application requirements in in-network processes. We intend to use a WSN to aid information querying and navigation within a dynamic and real-time environment. We propose a novel method that relies on the heat diffusion equation to finish the navigation process conveniently and easily. From the perspective of theoretical analysis, our proposed work holds the lower constraint condition. We use multiple scales to reach the goal of accurate navigation. We present a multi-scale gradient descent method to satisfy users’ requirements in WSNs. Formula derivations and simulations show that the method is accurately and efficiently able to solve typical sensor network configuration information navigation problems. Simultaneously, the structure of heat diffusion equation allows more flexibility and adaptability in searching algorithm designs.

Recognition of Walking Activities Using Wireless Inertial and Orientation Sensors: A Performance Evaluation

NARCIS (Netherlands)

Yalçin, Ç.; Marin Perianu, Mihai; Marin Perianu, Raluca; Havinga, Paul J.M.; Augusto, J.C.

In this paper, we evaluate experimentally several methods for recognizing walking activities using on-body wireless nodes equipped with inertial and orientation sensors. The walking activities (walking on flat surfaces, uphill and downhill, upstairs and downstairs) are selected by healthcare experts

Biologically inspired autonomous agent navigation using an integrated polarization analyzing CMOS image sensor

NARCIS (Netherlands)

Sarkaer, M.; San Segundo Bello, D.; Van Hoof, C.; Theuwissen, A.

2010-01-01

The navigational strategies of insects using skylight polarization are interesting for applications in autonomous agent navigation because they rely on very little information for navigation. A polarization navigation sensor using the Stokes parameters to determine the orientation is presented. The

Using Posture Estimation to Enhance Personal Inertial Tracking

Science.gov (United States)

2016-06-01

augment tracking during periods without GPS coverage. The goal of this research is to improve the current personal inertial navigation system by...solution is to use inertial navigation systems to augment tracking during periods without GPS coverage. The goal of this research is to improve the...For large items such as vehicles or aircraft, a Global Positioning System ( GPS ) is used to track the locations of friendly units and display these

On-the-fly Locata/inertial navigation system integration for precise maritime application

Science.gov (United States)

Jiang, Wei; Li, Yong; Rizos, Chris

2013-10-01

The application of Global Navigation Satellite System (GNSS) technology has meant that marine navigators have greater access to a more consistent and accurate positioning capability than ever before. However, GNSS may not be able to meet all emerging navigation performance requirements for maritime applications with respect to service robustness, accuracy, integrity and availability. In particular, applications in port areas (for example automated docking) and in constricted waterways, have very stringent performance requirements. Even when an integrated inertial navigation system (INS)/GNSS device is used there may still be performance gaps. GNSS signals are easily blocked or interfered with, and sometimes the satellite geometry may not be good enough for high accuracy and high reliability applications. Furthermore, the INS accuracy degrades rapidly during GNSS outages. This paper investigates the use of a portable ground-based positioning system, known as ‘Locata’, which was integrated with an INS, to provide accurate navigation in a marine environment without reliance on GNSS signals. An ‘on-the-fly’ Locata resolution algorithm that takes advantage of geometry change via an extended Kalman filter is proposed in this paper. Single-differenced Locata carrier phase measurements are utilized to achieve accurate and reliable solutions. A ‘loosely coupled’ decentralized Locata/INS integration architecture based on the Kalman filter is used for data processing. In order to evaluate the system performance, a field trial was conducted on Sydney Harbour. A Locata network consisting of eight Locata transmitters was set up near the Sydney Harbour Bridge. The experiment demonstrated that the Locata on-the-fly (OTF) algorithm is effective and can improve the system accuracy in comparison with the conventional ‘known point initialization’ (KPI) method. After the OTF and KPI comparison, the OTF Locata/INS integration is then assessed further and its performance

On-the-fly Locata/inertial navigation system integration for precise maritime application

International Nuclear Information System (INIS)

Jiang, Wei; Li, Yong; Rizos, Chris

2013-01-01

The application of Global Navigation Satellite System (GNSS) technology has meant that marine navigators have greater access to a more consistent and accurate positioning capability than ever before. However, GNSS may not be able to meet all emerging navigation performance requirements for maritime applications with respect to service robustness, accuracy, integrity and availability. In particular, applications in port areas (for example automated docking) and in constricted waterways, have very stringent performance requirements. Even when an integrated inertial navigation system (INS)/GNSS device is used there may still be performance gaps. GNSS signals are easily blocked or interfered with, and sometimes the satellite geometry may not be good enough for high accuracy and high reliability applications. Furthermore, the INS accuracy degrades rapidly during GNSS outages. This paper investigates the use of a portable ground-based positioning system, known as ‘Locata’, which was integrated with an INS, to provide accurate navigation in a marine environment without reliance on GNSS signals. An ‘on-the-fly’ Locata resolution algorithm that takes advantage of geometry change via an extended Kalman filter is proposed in this paper. Single-differenced Locata carrier phase measurements are utilized to achieve accurate and reliable solutions. A ‘loosely coupled’ decentralized Locata/INS integration architecture based on the Kalman filter is used for data processing. In order to evaluate the system performance, a field trial was conducted on Sydney Harbour. A Locata network consisting of eight Locata transmitters was set up near the Sydney Harbour Bridge. The experiment demonstrated that the Locata on-the-fly (OTF) algorithm is effective and can improve the system accuracy in comparison with the conventional ‘known point initialization’ (KPI) method. After the OTF and KPI comparison, the OTF Locata/INS integration is then assessed further and its performance

Spoofing Detection Using GNSS/INS/Odometer Coupling for Vehicular Navigation.

Science.gov (United States)

Broumandan, Ali; Lachapelle, Gérard

2018-04-24

Location information is one of the most vital information required to achieve intelligent and context-aware capability for various applications such as driverless cars. However, related security and privacy threats are a major holdback. With increasing focus on using Global Navigation Satellite Systems (GNSS) for autonomous navigation and related applications, it is important to provide robust navigation solutions, yet signal spoofing for illegal or covert transportation and misleading receiver timing is increasing and now frequent. Hence, detection and mitigation of spoofing attacks has become an important topic. Several contributions on spoofing detection have been made, focusing on different layers of a GNSS receiver. This paper focuses on spoofing detection utilizing self-contained sensors, namely inertial measurement units (IMUs) and vehicle odometer outputs. A spoofing detection approach based on a consistency check between GNSS and IMU/odometer mechanization is proposed. To detect a spoofing attack, the method analyses GNSS and IMU/odometer measurements independently during a pre-selected observation window and cross checks the solutions provided by GNSS and inertial navigation solution (INS)/odometer mechanization. The performance of the proposed method is verified in real vehicular environments. Mean spoofing detection time and detection performance in terms of receiver operation characteristics (ROC) in sub-urban and dense urban environments are evaluated.

Spoofing Detection Using GNSS/INS/Odometer Coupling for Vehicular Navigation

Directory of Open Access Journals (Sweden)

Ali Broumandan

2018-04-01

Full Text Available Location information is one of the most vital information required to achieve intelligent and context-aware capability for various applications such as driverless cars. However, related security and privacy threats are a major holdback. With increasing focus on using Global Navigation Satellite Systems (GNSS for autonomous navigation and related applications, it is important to provide robust navigation solutions, yet signal spoofing for illegal or covert transportation and misleading receiver timing is increasing and now frequent. Hence, detection and mitigation of spoofing attacks has become an important topic. Several contributions on spoofing detection have been made, focusing on different layers of a GNSS receiver. This paper focuses on spoofing detection utilizing self-contained sensors, namely inertial measurement units (IMUs and vehicle odometer outputs. A spoofing detection approach based on a consistency check between GNSS and IMU/odometer mechanization is proposed. To detect a spoofing attack, the method analyses GNSS and IMU/odometer measurements independently during a pre-selected observation window and cross checks the solutions provided by GNSS and inertial navigation solution (INS/odometer mechanization. The performance of the proposed method is verified in real vehicular environments. Mean spoofing detection time and detection performance in terms of receiver operation characteristics (ROC in sub-urban and dense urban environments are evaluated.

Development of Fast Error Compensation Algorithm for Integrated Inertial-Satellite Navigation System of Small-size Unmanned Aerial Vehicles in Complex Environment

Directory of Open Access Journals (Sweden)

A. V. Fomichev

2015-01-01

Full Text Available In accordance with the structural features of small-size unmanned aerial vehicle (UAV, and considering the feasibility of this project, the article studies an integrated inertial-satellite navigation system (INS. The INS algorithm development is based on the method of indirect filtration and principle of loosely coupled combination of output data on UAV positions and velocity. Data on position and velocity are provided from the strapdown inertial navigation system (SINS and satellite navigation system (GPS. A difference between the output flows of measuring data on position and velocity provided from the SINS and GPS is used to evaluate SINS errors by means of the basic algorithm of Kalman filtering. Then the outputs of SINS are revised. The INS possesses the following advantages: a simpler mathematical model of Kalman filtering, high reliability, two independently operating navigation systems, and high redundancy of available navigation information.But in case of loosely coupled scheme, INS can meet the challenge of high precision and reliability of navigation only when the SINS and GPS operating conditions are normal all the time. The proposed INS is used with UAV moving in complex environment due to obstacles available, severe natural climatic conditions, etc. This case expects that it is impossible for UAV to receive successful GPS-signals frequently. In order to solve this problem, was developed an algorithm for rapid compensation for errors of INS information, which could effectively solve the problem of failure of the navigation system in case there are no GPS-signals .Since it is almost impossible to obtain the data of the real trajectory in practice, in the course of simulation in accordance with the kinematic model of the UAV and the complex environment of the terrain, the flight path generator is used to produce the flight path. The errors of positions and velocities are considered as an indicator of the INS effectiveness. The results

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

Science.gov (United States)

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.

Autonomous Integrated Navigation for Indoor Robots Utilizing On-Line Iterated Extended Rauch-Tung-Striebel Smoothing

Directory of Open Access Journals (Sweden)

Yuan Xu

2013-11-01

Full Text Available In order to reduce the estimated errors of the inertial navigation system (INS/Wireless sensor network (WSN-integrated navigation for mobile robots indoors, this work proposes an on-line iterated extended Rauch-Tung-Striebel smoothing (IERTSS utilizing inertial measuring units (IMUs and an ultrasonic positioning system. In this mode, an iterated Extended Kalman filter (IEKF is used in forward data processing of the Extended Rauch-Tung-Striebel smoothing (ERTSS to improve the accuracy of the filtering output for the smoother. Furthermore, in order to achieve the on-line smoothing, IERTSS is embedded into the average filter. For verification, a real indoor test has been done to assess the performance of the proposed method. The results show that the proposed method is effective in reducing the errors compared with the conventional schemes.

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

Science.gov (United States)

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

Science.gov (United States)

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

A Damping Grid Strapdown Inertial Navigation System Based on a Kalman Filter for Ships in Polar Regions.

Science.gov (United States)

Huang, Weiquan; Fang, Tao; Luo, Li; Zhao, Lin; Che, Fengzhu

2017-07-03

The grid strapdown inertial navigation system (SINS) used in polar navigation also includes three kinds of periodic oscillation errors as common SINS are based on a geographic coordinate system. Aiming ships which have the external information to conduct a system reset regularly, suppressing the Schuler periodic oscillation is an effective way to enhance navigation accuracy. The Kalman filter based on the grid SINS error model which applies to the ship is established in this paper. The errors of grid-level attitude angles can be accurately estimated when the external velocity contains constant error, and then correcting the errors of the grid-level attitude angles through feedback correction can effectively dampen the Schuler periodic oscillation. The simulation results show that with the aid of external reference velocity, the proposed external level damping algorithm based on the Kalman filter can suppress the Schuler periodic oscillation effectively. Compared with the traditional external level damping algorithm based on the damping network, the algorithm proposed in this paper can reduce the overshoot errors when the state of grid SINS is switched from the non-damping state to the damping state, and this effectively improves the navigation accuracy of the system.

Benefits of Combined GPS/GLONASS with Low-Cost MEMS IMUs for Vehicular Urban Navigation

Directory of Open Access Journals (Sweden)

Giovanni Pugliano

2012-04-01

Full Text Available The integration of Global Navigation Satellite Systems (GNSS with Inertial Navigation Systems (INS has been very actively researched for many years due to the complementary nature of the two systems. In particular, during the last few years the integration with micro-electromechanical system (MEMS inertial measurement units (IMUs has been investigated. In fact, recent advances in MEMS technology have made possible the development of a new generation of low cost inertial sensors characterized by small size and light weight, which represents an attractive option for mass-market applications such as vehicular and pedestrian navigation. However, whereas there has been much interest in the integration of GPS with a MEMS-based INS, few research studies have been conducted on expanding this application to the revitalized GLONASS system. This paper looks at the benefits of adding GLONASS to existing GPS/INS(MEMS systems using loose and tight integration strategies. The relative benefits of various constraints are also assessed. Results show that when satellite visibility is poor (approximately 50% solution availability the benefits of GLONASS are only seen with tight integration algorithms. For more benign environments, a loosely coupled GPS/GLONASS/INS system offers performance comparable to that of a tightly coupled GPS/INS system, but with reduced complexity and development time.

Benefits of combined GPS/GLONASS with low-cost MEMS IMUs for vehicular urban navigation.

Science.gov (United States)

Angrisano, Antonio; Petovello, Mark; Pugliano, Giovanni

2012-01-01

The integration of Global Navigation Satellite Systems (GNSS) with Inertial Navigation Systems (INS) has been very actively researched for many years due to the complementary nature of the two systems. In particular, during the last few years the integration with micro-electromechanical system (MEMS) inertial measurement units (IMUs) has been investigated. In fact, recent advances in MEMS technology have made possible the development of a new generation of low cost inertial sensors characterized by small size and light weight, which represents an attractive option for mass-market applications such as vehicular and pedestrian navigation. However, whereas there has been much interest in the integration of GPS with a MEMS-based INS, few research studies have been conducted on expanding this application to the revitalized GLONASS system. This paper looks at the benefits of adding GLONASS to existing GPS/INS(MEMS) systems using loose and tight integration strategies. The relative benefits of various constraints are also assessed. Results show that when satellite visibility is poor (approximately 50% solution availability) the benefits of GLONASS are only seen with tight integration algorithms. For more benign environments, a loosely coupled GPS/GLONASS/INS system offers performance comparable to that of a tightly coupled GPS/INS system, but with reduced complexity and development time.

Observability of satellite launcher navigation with INS, GPS, attitude sensors and reference trajectory

Science.gov (United States)

Beaudoin, Yanick; Desbiens, André; Gagnon, Eric; Landry, René

2018-01-01

The navigation system of a satellite launcher is of paramount importance. In order to correct the trajectory of the launcher, the position, velocity and attitude must be known with the best possible precision. In this paper, the observability of four navigation solutions is investigated. The first one is the INS/GPS couple. Then, attitude reference sensors, such as magnetometers, are added to the INS/GPS solution. The authors have already demonstrated that the reference trajectory could be used to improve the navigation performance. This approach is added to the two previously mentioned navigation systems. For each navigation solution, the observability is analyzed with different sensor error models. First, sensor biases are neglected. Then, sensor biases are modelled as random walks and as first order Markov processes. The observability is tested with the rank and condition number of the observability matrix, the time evolution of the covariance matrix and sensitivity to measurement outlier tests. The covariance matrix is exploited to evaluate the correlation between states in order to detect structural unobservability problems. Finally, when an unobservable subspace is detected, the result is verified with theoretical analysis of the navigation equations. The results show that evaluating only the observability of a model does not guarantee the ability of the aiding sensors to correct the INS estimates within the mission time. The analysis of the covariance matrix time evolution could be a powerful tool to detect this situation, however in some cases, the problem is only revealed with a sensitivity to measurement outlier test. None of the tested solutions provide GPS position bias observability. For the considered mission, the modelling of the sensor biases as random walks or Markov processes gives equivalent results. Relying on the reference trajectory can improve the precision of the roll estimates. But, in the context of a satellite launcher, the roll

Application of the spherical harmonic gravity model in high precision inertial navigation systems

International Nuclear Information System (INIS)

Wang, Jing; Yang, Gongliu; Zhou, Xiao; Li, Xiangyun

2016-01-01

The spherical harmonic gravity model (SHM) may, in general, be considered as a suitable alternative to the normal gravity model (NGM), because it represents the Earth’s gravitational field more accurately. However, the high-resolution SHM has never been used in current inertial navigation systems (INSs) due to its extremely complex expression. In this paper, the feasibility and accuracy of a truncated SHM are discussed for application in a real-time free-INS with a precision demand better than 0.8 nm h −1 . In particular, the time and space complexity are analyzed mathematically to verify the feasibility of the SHM. Also, a test on a typical navigation computer shows a storable range of cut-off degrees. To further evaluate the appropriate degree and accuracy of the truncated SHM, analyses of covariance and truncation error are proposed. Finally, a SHM of degree 12 is demonstrated to be the appropriate model for routine INSs in the precision range of 0.4–0.75 nm h −1 . Flight simulations and road tests show its outstanding performance over the traditional NGM. (paper)

Sensor fusion for mobile robot navigation

International Nuclear Information System (INIS)

Kam, M.; Zhu, X.; Kalata, P.

1997-01-01

The authors review techniques for sensor fusion in robot navigation, emphasizing algorithms for self-location. These find use when the sensor suite of a mobile robot comprises several different sensors, some complementary and some redundant. Integrating the sensor readings, the robot seeks to accomplish tasks such as constructing a map of its environment, locating itself in that map, and recognizing objects that should be avoided or sought. The review describes integration techniques in two categories: low-level fusion is used for direct integration of sensory data, resulting in parameter and state estimates; high-level fusion is used for indirect integration of sensory data in hierarchical architectures, through command arbitration and integration of control signals suggested by different modules. The review provides an arsenal of tools for addressing this (rather ill-posed) problem in machine intelligence, including Kalman filtering, rule-based techniques, behavior based algorithms and approaches that borrow from information theory, Dempster-Shafer reasoning, fuzzy logic and neural networks. It points to several further-research needs, including: robustness of decision rules; simultaneous consideration of self-location, motion planning, motion control and vehicle dynamics; the effect of sensor placement and attention focusing on sensor fusion; and adaptation of techniques from biological sensor fusion

Target Tracking with Sensor Navigation Using Coupled RSS and AoA Measurements

Directory of Open Access Journals (Sweden)

Slavisa Tomic

2017-11-01

Full Text Available This work addresses the problem of tracking a signal-emitting mobile target in wireless sensor networks (WSNs with navigated mobile sensors. The sensors are properly equipped to acquire received signal strength (RSS and angle of arrival (AoA measurements from the received signal, while the target transmit power is assumed not known. We start by showing how to linearize the highly non-linear measurement model. Then, by employing a Bayesian approach, we combine the linearized observation model with prior knowledge extracted from the state transition model. Based on the maximum a posteriori (MAP principle and the Kalman filtering (KF framework, we propose new MAP and KF algorithms, respectively. We also propose a simple and efficient mobile sensor navigation procedure, which allows us to further enhance the estimation accuracy of our algorithms with a reduced number of sensors. Model flaws, which result in imperfect knowledge about the path loss exponent (PLE and the true mobile sensors’ locations, are taken into consideration. We have carried out an extensive simulation study, and our results confirm the superiority of the proposed algorithms, as well as the effectiveness of the proposed navigation routine.

Surface navigation on Mars with a Navigation Satellite

Science.gov (United States)

Vijayaraghavan, A.; Thurman, Sam W.; Kahn, Robert D.; Hastrup, Rolf C.

Radiometric navigation data from the Deep Space Network (DSN) stations on the earth to transponders and other surface elements such as rovers and landers on Mars, can determine their positions to only within a kilometer in inertial space. The positional error is mostly in the z-component of the surface element parallel to the Martian spin-axis. However, with Doppler and differenced-Doppler data from a Navigation Satellite in orbit around Mars to two or more of such transponders on the planetary surface, their positions can be determined to within 15 meters (or 20 meters for one-way Doppler beacons on Mars) in inertial space. In this case, the transponders (or other vehicles) on Mars need not even be capable of directly communicating to the earth. When the Navigation Satellite data is complemented by radiometric observations from the DSN stations also, directly to the surface elements on Mars, their positions can be determined to within 3 meters in inertial space. The relative positions of such surface elements on Mars (relative to one another) in Mars-fixed coordinates, however, can be determined to within 5 meters from simply range and Doppler data from the DSN stations to the surface elements. These results are obtained from covariance studies assuming X-band data noise levels and data-arcs not exceeding 10 days. They are significant in the planning and deployment of a Mars-based navigation network necessary to support real-time operations during critical phases of manned exploration of Mars.

Modular finger and hand motion capturing system based on inertial and magnetic sensors

Directory of Open Access Journals (Sweden)

Valtin Markus

2017-03-01

Full Text Available The assessment of hand posture and kinematics is increasingly important in various fields. This includes the rehabilitation of stroke survivors with restricted hand function. This paper presents a modular, ambulatory measurement system for the assement of the remaining hand function and for closed-loop controlled therapy. The device is based on inertial sensors and utilizes up to five interchangeable sensor strips to achieve modularity and to simplify the sensor attachment. We introduce the modular hardware design and describe algorithms used to calculate the joint angles. Measurements with two experimental setups demonstrate the feasibility and the potential of such a tracking device.

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

Directory of Open Access Journals (Sweden)

Tongyang Sun

2017-01-01

Full Text Available 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.

Lower limb spasticity assessment using an inertial sensor: a reliability study

International Nuclear Information System (INIS)

Sterpi, I; Colombo, R; Caroli, A; Meazza, E; Maggioni, G; Pistarini, C

2013-01-01

Spasticity is a common motor impairment in patients with neurological disorders that can prevent functional recovery after rehabilitation. In the clinical setting, its assessment is carried out using standardized clinical scales. The aim of this study was to verify the applicability of inertial sensors for an objective measurement of quadriceps spasticity and evaluate its test–retest and inter-rater reliability during the implementation of the Wartenberg pendulum test. Ten healthy subjects and 11 patients in vegetative state with severe brain damage were enrolled in this study. Subjects were evaluated three times on three consecutive days. The test–retest reliability of measurement was assessed in the first two days. The third day was devoted to inter-rater reliability assessment. In addition, the lower limb muscle tone was bilaterally evaluated at the knee joint by the modified Ashworth scale. The factorial ANOVA analysis showed that the implemented method allowed us to discriminate between healthy and pathological conditions. The fairly low SEM and high ICC values obtained for the pendulum parameters indicated a good test–retest and inter-rater reliability of measurement. This study shows that an inertial sensor can be reliably used to characterize leg kinematics during the Wartenberg pendulum test and provide quantitative evaluation of quadriceps spasticity. (paper)

A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults.

Science.gov (United States)

Sun, Rui; Cheng, Qi; Wang, Guanyu; Ochieng, Washington Yotto

2017-09-29

The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs' flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in UAVs. Contrary to the classic UAV sensor fault detection algorithms, based on predefined or modelled faults, the proposed algorithm combines an online data training mechanism with the ANFIS-based decision system. The main advantages of this algorithm are that it allows real-time model-free residual analysis from Kalman Filter (KF) estimates and the ANFIS to build a reliable fault detection system. In addition, it allows fast and accurate detection of faults, which makes it suitable for real-time applications. Experimental results have demonstrated the effectiveness of the proposed fault detection method in terms of accuracy and misdetection rate.

A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults

Directory of Open Access Journals (Sweden)

Rui Sun

2017-09-01

Full Text Available The use of Unmanned Aerial Vehicles (UAVs has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs’ flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS-based approach is presented for the detection of on-board navigation sensor faults in UAVs. Contrary to the classic UAV sensor fault detection algorithms, based on predefined or modelled faults, the proposed algorithm combines an online data training mechanism with the ANFIS-based decision system. The main advantages of this algorithm are that it allows real-time model-free residual analysis from Kalman Filter (KF estimates and the ANFIS to build a reliable fault detection system. In addition, it allows fast and accurate detection of faults, which makes it suitable for real-time applications. Experimental results have demonstrated the effectiveness of the proposed fault detection method in terms of accuracy and misdetection rate.

A Novel 3D Multilateration Sensor Using Distributed Ultrasonic Beacons for Indoor Navigation

Directory of Open Access Journals (Sweden)

Rohan Kapoor

2016-10-01

Full Text Available Navigation and guidance systems are a critical part of any autonomous vehicle. In this paper, a novel sensor grid using 40 KHz ultrasonic transmitters is presented for adoption in indoor 3D positioning applications. In the proposed technique, a vehicle measures the arrival time of incoming ultrasonic signals and calculates the position without broadcasting to the grid. This system allows for conducting silent or covert operations and can also be used for the simultaneous navigation of a large number of vehicles. The transmitters and receivers employed are first described. Transmission lobe patterns and receiver directionality determine the geometry of transmitter clusters. Range and accuracy of measurements dictate the number of sensors required to navigate in a given volume. Laboratory experiments were performed in which a small array of transmitters was set up and the sensor system was tested for position accuracy. The prototype system is shown to have a 1-sigma position error of about 16 cm, with errors between 7 and 11 cm in the local horizontal coordinates. This research work provides foundations for the future development of ultrasonic navigation sensors for a variety of autonomous vehicle applications.

Determine the Foot Strike Pattern Using Inertial Sensors

Directory of Open Access Journals (Sweden)

Tzyy-Yuang Shiang

2016-01-01

Full Text Available From biomechanical point of view, strike pattern plays an important role in preventing potential injury risk in running. Traditionally, strike pattern determination was conducted by using 3D motion analysis system with cameras. However, the procedure is costly and not convenient. With the rapid development of technology, sensors have been applied in sport science field lately. Therefore, this study was designed to determine the algorithm that can identify landing strategies with a wearable sensor. Six healthy male participants were recruited to perform heel and forefoot strike strategies at 7, 10, and 13 km/h speeds. The kinematic data were collected by Vicon 3D motion analysis system and 2 inertial measurement units (IMU attached on the dorsal side of both shoes. The data of each foot strike were gathered for pitch angle and strike index analysis. Comparing the strike index from IMU with the pitch angle from Vicon system, our results showed that both signals exhibited highly correlated changes between different strike patterns in the sagittal plane (r=0.98. Based on the findings, the IMU sensors showed potential capabilities and could be extended beyond the context of sport science to other fields, including clinical applications.

Novel Navigation Algorithm for Wireless Sensor Networks without Information of Locations

NARCIS (Netherlands)

Guo, Peng; Jiang, Tao; Yi, Youwen; Zhang, Qian; Zhang, Kui

2011-01-01

In this paper, we propose a novel algorithm of distributed navigation for people to escape from critical event region in wireless sensor networks (WSNs). Unlike existing works, the scenario discussed in the paper has no goal or exit as guidance, leading to a big challenge for the navigation problem.

Drift Reduction in Pedestrian Navigation System by Exploiting Motion Constraints and Magnetic Field

Directory of Open Access Journals (Sweden)

Muhammad Ilyas

2016-09-01

Full Text Available Pedestrian navigation systems (PNS using foot-mounted MEMS inertial sensors use zero-velocity updates (ZUPTs to reduce drift in navigation solutions and estimate inertial sensor errors. However, it is well known that ZUPTs cannot reduce all errors, especially as heading error is not observable. Hence, the position estimates tend to drift and even cyclic ZUPTs are applied in updated steps of the Extended Kalman Filter (EKF. This urges the use of other motion constraints for pedestrian gait and any other valuable heading reduction information that is available. In this paper, we exploit two more motion constraints scenarios of pedestrian gait: (1 walking along straight paths; (2 standing still for a long time. It is observed that these motion constraints (called “virtual sensor”, though considerably reducing drift in PNS, still need an absolute heading reference. One common absolute heading estimation sensor is the magnetometer, which senses the Earth’s magnetic field and, hence, the true heading angle can be calculated. However, magnetometers are susceptible to magnetic distortions, especially in indoor environments. In this work, an algorithm, called magnetic anomaly detection (MAD and compensation is designed by incorporating only healthy magnetometer data in the EKF updating step, to reduce drift in zero-velocity updated INS. Experiments are conducted in GPS-denied and magnetically distorted environments to validate the proposed algorithms.

Sensor-based control with digital maps association for global navigation: a real application for autonomous vehicles

OpenAIRE

Alves De Lima , Danilo; Corrêa Victorino , Alessandro

2015-01-01

International audience; This paper presents a sensor-based control strategy applied in the global navigation of autonomous vehicles in urban environments. Typically, sensor-based control performs local navigation tasks regarding some features perceived from the environment. However, when there is more than one possibility to go, like in road intersection, the vehicle control fails to accomplish its global navigation. In order to solve this problem, we propose the vehicle global navigation bas...

Data analysis of inertial sensor for train positioning detection system

Energy Technology Data Exchange (ETDEWEB)

Kim, Seong Jin; Park, Sung Soo; Lee, Jae Ho; Kang, Dong Hoon [Korea Railroad Research Institute, Uiwang (Korea, Republic of)

2015-02-15

Train positioning detection information is fundamental for high-speed railroad inspection, making it possible to simultaneously determine the status and evaluate the integrity of railroad equipment. This paper presents the results of measurements and an analysis of an inertial measurement unit (IMU) used as a positioning detection sensors. Acceleration and angular rate measurements from the IMU were analyzed in the amplitude and frequency domains, with a discussion on vibration and train motions. Using these results and GPS information, the positioning detection of a Korean tilting train express was performed from Naju station to Illo station on the Honam-line. The results of a synchronized analysis of sensor measurements and train motion can help in the design of a train location detection system and improve the positioning detection performance.

Analysis of Landing in Ski Jumping by Means of Inertial Sensors and Force Insoles

Directory of Open Access Journals (Sweden)

Veronica Bessone

2018-02-01

Full Text Available Landing and its preparation are important phases for performance and safety of ski jumpers. A correct ski positioning could influence the jump length as also the cushioning effect of the aerodynamic forces that permits the reduction of landing impacts. Consequently, the detection of ski angles during landing preparation could allow for analyzing landing techniques that result in reduced impact forces for the athletes. In this study, two athletes performed with force insoles and inertial sensors positioned on the ski during training conditions on the ski jumping hill. The results confirmed previous studies, showing that impact forces can reach more than four times body weight. In the analyzed cases, the force distribution resulted to be more concentrated on the forefoot and the main movement influencing the impact was the pitch. The combination of inertial sensors, in particular gyroscopes, plus force insoles demonstrated to be an interesting set up for ski jumping movement analysis.

Gait Kinematic Analysis in Water Using Wearable Inertial Magnetic Sensors.

Directory of Open Access Journals (Sweden)

Silvia Fantozzi

Full Text Available Walking is one of the fundamental motor tasks executed during aquatic therapy. Previous kinematics analyses conducted using waterproofed video cameras were limited to the sagittal plane and to only one or two consecutive steps. Furthermore, the set-up and post-processing are time-consuming and thus do not allow a prompt assessment of the correct execution of the movements during the aquatic session therapy. The aim of the present study was to estimate the 3D joint kinematics of the lower limbs and thorax-pelvis joints in sagittal and frontal planes during underwater walking using wearable inertial and magnetic sensors. Eleven healthy adults were measured during walking both in shallow water and in dry-land conditions. Eight wearable inertial and magnetic sensors were inserted in waterproofed boxes and fixed to the body segments by means of elastic modular bands. A validated protocol (Outwalk was used. Gait cycles were automatically segmented and selected if relevant intraclass correlation coefficients values were higher than 0.75. A total of 704 gait cycles for the lower limb joints were normalized in time and averaged to obtain the mean cycle of each joint, among participants. The mean speed in water was 40% lower than that of the dry-land condition. Longer stride duration and shorter stride distance were found in the underwater walking. In the sagittal plane, the knee was more flexed (≈ 23° and the ankle more dorsiflexed (≈ 9° at heel strike, and the hip was more flexed at toe-off (≈ 13° in water than on land. On the frontal plane in the underwater walking, smoother joint angle patterns were observed for thorax-pelvis and hip, and ankle was more inversed at toe-off (≈ 7° and showed a more inversed mean value (≈ 7°. The results were mainly explained by the effect of the speed in the water as supported by the linear mixed models analysis performed. Thus, it seemed that the combination of speed and environment triggered

Gait Kinematic Analysis in Water Using Wearable Inertial Magnetic Sensors.

Science.gov (United States)

Fantozzi, Silvia; Giovanardi, Andrea; Borra, Davide; Gatta, Giorgio

2015-01-01

Walking is one of the fundamental motor tasks executed during aquatic therapy. Previous kinematics analyses conducted using waterproofed video cameras were limited to the sagittal plane and to only one or two consecutive steps. Furthermore, the set-up and post-processing are time-consuming and thus do not allow a prompt assessment of the correct execution of the movements during the aquatic session therapy. The aim of the present study was to estimate the 3D joint kinematics of the lower limbs and thorax-pelvis joints in sagittal and frontal planes during underwater walking using wearable inertial and magnetic sensors. Eleven healthy adults were measured during walking both in shallow water and in dry-land conditions. Eight wearable inertial and magnetic sensors were inserted in waterproofed boxes and fixed to the body segments by means of elastic modular bands. A validated protocol (Outwalk) was used. Gait cycles were automatically segmented and selected if relevant intraclass correlation coefficients values were higher than 0.75. A total of 704 gait cycles for the lower limb joints were normalized in time and averaged to obtain the mean cycle of each joint, among participants. The mean speed in water was 40% lower than that of the dry-land condition. Longer stride duration and shorter stride distance were found in the underwater walking. In the sagittal plane, the knee was more flexed (≈ 23°) and the ankle more dorsiflexed (≈ 9°) at heel strike, and the hip was more flexed at toe-off (≈ 13°) in water than on land. On the frontal plane in the underwater walking, smoother joint angle patterns were observed for thorax-pelvis and hip, and ankle was more inversed at toe-off (≈ 7°) and showed a more inversed mean value (≈ 7°). The results were mainly explained by the effect of the speed in the water as supported by the linear mixed models analysis performed. Thus, it seemed that the combination of speed and environment triggered modifications in the

Context-Aided Sensor Fusion for Enhanced Urban Navigation

Science.gov (United States)

Martí, Enrique David; Martín, David; García, Jesús; de la Escalera, Arturo; Molina, José Manuel; Armingol, José María

2012-01-01

The deployment of Intelligent Vehicles in urban environments requires reliable estimation of positioning for urban navigation. The inherent complexity of this kind of environments fosters the development of novel systems which should provide reliable and precise solutions to the vehicle. This article details an advanced GNSS/IMU fusion system based on a context-aided Unscented Kalman filter for navigation in urban conditions. The constrained non-linear filter is here conditioned by a contextual knowledge module which reasons about sensor quality and driving context in order to adapt it to the situation, while at the same time it carries out a continuous estimation and correction of INS drift errors. An exhaustive analysis has been carried out with available data in order to characterize the behavior of available sensors and take it into account in the developed solution. The performance is then analyzed with an extensive dataset containing representative situations. The proposed solution suits the use of fusion algorithms for deploying Intelligent Transport Systems in urban environments. PMID:23223080

Multi-sensor fusion method for crop row tracking and traversability operations

OpenAIRE

Benet, B.; Lenain, R.

2017-01-01

Precision agriculture vehicles need autonomous navigation in cultures to carry out their tasks, such as planting, maintenance and harvesting in cultures such as vegetable, vineyard, or horticulture. The detection of natural objects like trunks, grass, leaf, or obstacles in front of vehicle in crop row is crucial for safe navigation. Sensors such as LiDAR devices or Time Of Flight cameras (TOF), allow to obtain geometric data in natural environment, using information of an Inertial Measurement...

An improved particle filter and its application to an INS/GPS integrated navigation system in a serious noisy scenario

International Nuclear Information System (INIS)

Wang, Xuemei; Ni, Wenbo

2016-01-01

For loosely coupled INS/GPS integrated navigation systems with low-cost and low-accuracy microelectromechanical device inertial sensors, in order to obtain enough accuracy, a full-state nonlinear dynamic model rather than a linearized error model is much more preferable. Particle filters are particularly for nonlinear and non-Gaussian situations, but typical bootstrap particle filters (BPFs) and some improved particle filters (IPFs) such as auxiliary particle filters (APFs) and Gaussian particle filters (GPFs) cannot solve the mismatch between the importance function and the likelihood function very well. The predicted particles propagated through inertial navigation equations cannot be scattered with certainty within the effective range of current observation when there are large drift errors of the inertial sensors. Therefore, the current observation cannot play the correction role well and these particle filters are invalid to some extent. The proposed IPF firstly estimates the corresponding state bias errors according to the current observation and then corrects the bias errors of the predicted particles before determining the weights and resampling the particles. Simulations and practical experiments both show that the proposed IPF can effectively solve the mismatch between the importance function and the likelihood function of a BPF and compensate the accumulated errors of INSs very well. It has great robustness in a serious noisy scenario. (paper)

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

Science.gov (United States)

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

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

Directory of Open Access Journals (Sweden)

Yoshihisa Sakurai

2016-04-01

Full Text Available 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.

A New PDR Navigation Device for Challenging Urban Environments

Directory of Open Access Journals (Sweden)

Miguel Ortiz

2017-01-01

Full Text Available The motivations, the design, and some applications of the new Pedestrian Dead Reckoning (PDR navigation device, ULISS (Ubiquitous Localization with Inertial Sensors and Satellites, are presented in this paper. It is an original device conceived to follow the European recommendation of privacy by design to protect location data which opens new research toward self-contained pedestrian navigation approaches. Its application is presented with an enhanced PDR algorithm to estimate pedestrian’s footpaths in an autonomous manner irrespective of the handheld device carrying mode: texting or swinging. An analysis of real-time coding issues toward a demonstrator is also conducted. Indoor experiments, conducted with 3 persons, give a 5.8% mean positioning error over the 3 km travelled distances.

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

Science.gov (United States)

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.

Orion Exploration Flight Test-l (EFT -1) Absolute Navigation Design

Science.gov (United States)

Sud, Jastesh; Gay, Robert; Holt, Greg; Zanetti, Renato

2014-01-01

Scheduled to launch in September 2014 atop a Delta IV Heavy from the Kennedy Space Center, the Orion Multi-Purpose-Crew-Vehicle (MPCV's) maiden flight dubbed "Exploration Flight Test -1" (EFT-1) intends to stress the system by placing the uncrewed vehicle on a high-energy parabolic trajectory replicating conditions similar to those that would be experienced when returning from an asteroid or a lunar mission. Unique challenges associated with designing the navigation system for EFT-1 are presented in the narrative with an emphasis on how redundancy and robustness influenced the architecture. Two Inertial Measurement Units (IMUs), one GPS receiver and three barometric altimeters (BALTs) comprise the navigation sensor suite. The sensor data is multiplexed using conventional integration techniques and the state estimate is refined by the GPS pseudorange and deltarange measurements in an Extended Kalman Filter (EKF) that employs the UDUT decomposition approach. The design is substantiated by simulation results to show the expected performance.

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

Directory of Open Access Journals (Sweden)

Yanlei Gu

2015-12-01

Full Text Available 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.

An alternative sensor fusion method for object orientation using low-cost MEMS inertial sensors

Science.gov (United States)

Bouffard, Joshua L.

This thesis develops an alternative sensor fusion approach for object orientation using low-cost MEMS inertial sensors. The alternative approach focuses on the unique challenges of small UAVs. Such challenges include the vibrational induced noise onto the accelerometer and bias offset errors of the rate gyroscope. To overcome these challenges, a sensor fusion algorithm combines the measured data from the accelerometer and rate gyroscope to achieve a single output free from vibrational noise and bias offset errors. One of the most prevalent sensor fusion algorithms used for orientation estimation is the Extended Kalman filter (EKF). The EKF filter performs the fusion process by first creating the process model using the nonlinear equations of motion and then establishing a measurement model. With the process and measurement models established, the filter operates by propagating the mean and covariance of the states through time. The success of EKF relies on the ability to establish a representative process and measurement model of the system. In most applications, the EKF measurement model utilizes the accelerometer and GPS-derived accelerations to determine an estimate of the orientation. However, if the GPS-derived accelerations are not available then the measurement model becomes less reliable when subjected to harsh vibrational environments. This situation led to the alternative approach, which focuses on the correlation between the rate gyroscope and accelerometer-derived angle. The correlation between the two sensors then determines how much the algorithm will use one sensor over the other. The result is a measurement that does not suffer from the vibrational noise or from bias offset errors.

Context-Aided Sensor Fusion for Enhanced Urban Navigation

Directory of Open Access Journals (Sweden)

Enrique David Martí

2012-12-01

Full Text Available  The deployment of Intelligent Vehicles in urban environments requires reliable estimation of positioning for urban navigation. The inherent complexity of this kind of environments fosters the development of novel systems which should provide reliable and precise solutions to the vehicle. This article details an advanced GNSS/IMU fusion system based on a context-aided Unscented Kalman filter for navigation in urban conditions. The constrained non-linear filter is here conditioned by a contextual knowledge module which reasons about sensor quality and driving context in order to adapt it to the situation, while at the same time it carries out a continuous estimation and correction of INS drift errors. An exhaustive analysis has been carried out with available data in order to characterize the behavior of available sensors and take it into account in the developed solution. The performance is then analyzed with an extensive dataset containing representative situations. The proposed solution suits the use of fusion algorithms for deploying Intelligent Transport Systems in urban environments.

Upper Limb Kinematics Using Inertial and Magnetic Sensors: Comparison of Sensor-to-Segment Calibrations

Directory of Open Access Journals (Sweden)

Brice Bouvier

2015-07-01

Full Text Available Magneto-Inertial Measurement Unit sensors (MIMU display high potential for the quantitative evaluation of upper limb kinematics, as they allow monitoring ambulatory measurements. The sensor-to-segment calibration step, consisting of establishing the relation between MIMU sensors and human segments, plays an important role in the global accuracy of joint angles. The aim of this study was to compare sensor-to-segment calibrations for the MIMU-based estimation of wrist, elbow, and shoulder joint angles, by examining trueness (“close to the reference” and precision (reproducibility validity criteria. Ten subjects performed five sessions with three different operators. Three classes of calibrations were studied: segment axes equal to technical MIMU axes (TECH, segment axes generated during a static pose (STATIC, and those generated during functional movements (FUNCT. The calibrations were compared during the maximal uniaxial movements of each joint, plus an extra multi-joint movement. Generally, joint angles presented good trueness and very good precision in the range 5°–10°. Only small discrepancy between calibrations was highlighted, with the exception of a few cases. The very good overall accuracy (trueness and precision of MIMU-based joint angle data seems to be more dependent on the level of rigor of the experimental procedure (operator training than on the choice of calibration itself.

A High-Rate Virtual Instrument of Marine Vehicle Motions for Underwater Navigation and Ocean Remote Sensing

CERN Document Server

Gelin, Chrystel

2013-01-01

Dead-Reckoning aided with Doppler velocity measurement has been the most common method for underwater navigation for small vehicles. Unfortunately DR requires frequent position recalibrations and underwater vehicle navigation systems are limited to periodic position update when they surface. Finally standard Global Positioning System (GPS) receivers are unable to provide the rate or precision required when used on a small vessel. To overcome this, a low cost high rate motion measurement system for an Unmanned Surface Vehicle (USV) with underwater and oceanographic purposes is proposed. The proposed onboard system for the USV consists of an Inertial Measurement Unit (IMU) with accelerometers and rate gyros, a GPS receiver, a flux-gate compass, a roll and tilt sensor and an ADCP. Interfacing all the sensors proved rather challenging because of their different characteristics. The proposed data fusion technique integrates the sensors and develops an embeddable software package, using real time data fusion method...

A novel particle filter approach for indoor positioning by fusing WiFi and inertial sensors

Directory of Open Access Journals (Sweden)

Zhu Nan

2015-12-01

Full Text Available WiFi fingerprinting is the method of recording WiFi signal strength from access points (AP along with the positions at which they were recorded, and later matching those to new measurements for indoor positioning. Inertial positioning utilizes the accelerometer and gyroscopes for pedestrian positioning. However, both methods have their limitations, such as the WiFi fluctuations and the accumulative error of inertial sensors. Usually, the filtering method is used for integrating the two approaches to achieve better location accuracy. In the real environments, especially in the indoor field, the APs could be sparse and short range. To overcome the limitations, a novel particle filter approach based on Rao Blackwellized particle filter (RBPF is presented in this paper. The indoor environment is divided into several local maps, which are assumed to be independent of each other. The local areas are estimated by the local particle filter, whereas the global areas are combined by the global particle filter. The algorithm has been investigated by real field trials using a WiFi tablet on hand with an inertial sensor on foot. It could be concluded that the proposed method reduces the complexity of the positioning algorithm obviously, as well as offers a significant improvement in position accuracy compared to other conventional algorithms, allowing indoor positioning error below 1.2 m.

Bioinspired optical sensors for unmanned aerial systems

Science.gov (United States)

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 Novel AHRS Inertial Sensor-Based Algorithm for Wheelchair Propulsion Performance Analysis

OpenAIRE

Jonathan Bruce Shepherd; Tomohito Wada; David Rowlands; Daniel Arthur James

2016-01-01

With the increasing rise of professionalism in sport, athletes, teams, and coaches are looking to technology to monitor performance in both games and training in order to find a competitive advantage. The use of inertial sensors has been proposed as a cost effective and adaptable measurement device for monitoring wheelchair kinematics; however, the outcomes are dependent on the reliability of the processing algorithms. Though there are a variety of algorithms that have been proposed to monito...

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

Science.gov (United States)

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.

Adaptive Iterated Extended Kalman Filter and Its Application to Autonomous Integrated Navigation for Indoor Robot

Directory of Open Access Journals (Sweden)

Yuan Xu

2014-01-01

Full Text Available As the core of the integrated navigation system, the data fusion algorithm should be designed seriously. In order to improve the accuracy of data fusion, this work proposed an adaptive iterated extended Kalman (AIEKF which used the noise statistics estimator in the iterated extended Kalman (IEKF, and then AIEKF is used to deal with the nonlinear problem in the inertial navigation systems (INS/wireless sensors networks (WSNs-integrated navigation system. Practical test has been done to evaluate the performance of the proposed method. The results show that the proposed method is effective to reduce the mean root-mean-square error (RMSE of position by about 92.53%, 67.93%, 55.97%, and 30.09% compared with the INS only, WSN, EKF, and IEKF.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Yue-Yan Chan

2010-12-01

Full Text Available 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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Laboratory Validation of Inertial Body Sensors to Detect Cigarette Smoking Arm Movements

Directory of Open Access Journals (Sweden)

Bethany R. Raiff

2014-02-01

Full Text Available Cigarette smoking remains the leading cause of preventable death in the United States. Traditional in-clinic cessation interventions may fail to intervene and interrupt the rapid progression to relapse that typically occurs following a quit attempt. The ability to detect actual smoking behavior in real-time is a measurement challenge for health behavior research and intervention. The successful detection of real-time smoking through mobile health (mHealth methodology has substantial implications for developing highly efficacious treatment interventions. The current study was aimed at further developing and testing the ability of inertial sensors to detect cigarette smoking arm movements among smokers. The current study involved four smokers who smoked six cigarettes each in a laboratory-based assessment. Participants were outfitted with four inertial body movement sensors on the arms, which were used to detect smoking events at two levels: the puff level and the cigarette level. Two different algorithms (Support Vector Machines (SVM and Edge-Detection based learning were trained to detect the features of arm movement sequences transmitted by the sensors that corresponded with each level. The results showed that performance of the SVM algorithm at the cigarette level exceeded detection at the individual puff level, with low rates of false positive puff detection. The current study is the second in a line of programmatic research demonstrating the proof-of-concept for sensor-based tracking of smoking, based on movements of the arm and wrist. This study demonstrates efficacy in a real-world clinical inpatient setting and is the first to provide a detection rate against direct observation, enabling calculation of true and false positive rates. The study results indicate that the approach performs very well with some participants, whereas some challenges remain with participants who generate more frequent non-smoking movements near the face. Future

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

Science.gov (United States)

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

2018-03-01

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

Autonomous Quality Control of Joint Orientation Measured with Inertial Sensors

Directory of Open Access Journals (Sweden)

Karina Lebel

2016-07-01

Full Text Available 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.

Extended Kalman filter-based methods for pose estimation using visual, inertial and magnetic sensors: comparative analysis and performance evaluation.

Science.gov (United States)

Ligorio, Gabriele; Sabatini, Angelo Maria

2013-02-04

In this paper measurements from a monocular vision system are fused with inertial/magnetic measurements from an Inertial Measurement Unit (IMU) rigidly connected to the camera. Two Extended Kalman filters (EKFs) were developed to estimate the pose of the IMU/camera sensor moving relative to a rigid scene (ego-motion), based on a set of fiducials. The two filters were identical as for the state equation and the measurement equations of the inertial/magnetic sensors. The DLT-based EKF exploited visual estimates of the ego-motion using a variant of the Direct Linear Transformation (DLT) method; the error-driven EKF exploited pseudo-measurements based on the projection errors from measured two-dimensional point features to the corresponding three-dimensional fiducials. The two filters were off-line analyzed in different experimental conditions and compared to a purely IMU-based EKF used for estimating the orientation of the IMU/camera sensor. The DLT-based EKF was more accurate than the error-driven EKF, less robust against loss of visual features, and equivalent in terms of computational complexity. Orientation root mean square errors (RMSEs) of 1° (1.5°), and position RMSEs of 3.5 mm (10 mm) were achieved in our experiments by the DLT-based EKF (error-driven EKF); by contrast, orientation RMSEs of 1.6° were achieved by the purely IMU-based EKF.

Attitude and gyro bias estimation by the rotation of an inertial measurement unit

International Nuclear Information System (INIS)

Wu, Zheming; Sun, Zhenguo; Zhang, Wenzeng; Chen, Qiang

2015-01-01

In navigation applications, the presence of an unknown bias in the measurement of rate gyros is a key performance-limiting factor. In order to estimate the gyro bias and improve the accuracy of attitude measurement, we proposed a new method which uses the rotation of an inertial measurement unit, which is independent from rigid body motion. By actively changing the orientation of the inertial measurement unit (IMU), the proposed method generates sufficient relations between the gyro bias and tilt angle (roll and pitch) error via ridge body dynamics, and the gyro bias, including the bias that causes the heading error, can be estimated and compensated. The rotation inertial measurement unit method makes the gravity vector measured from the IMU continuously change in a body-fixed frame. By theoretically analyzing the mathematic model, the convergence of the attitude and gyro bias to the true values is proven. The proposed method provides a good attitude estimation using only measurements from an IMU, when other sensors such as magnetometers and GPS are unreliable. The performance of the proposed method is illustrated under realistic robotic motions and the results demonstrate an improvement in the accuracy of the attitude estimation. (paper)

Navigation system for a mobile robot with a visual sensor using a fish-eye lens

Science.gov (United States)

Kurata, Junichi; Grattan, Kenneth T. V.; Uchiyama, Hironobu

1998-02-01

Various position sensing and navigation systems have been proposed for the autonomous control of mobile robots. Some of these systems have been installed with an omnidirectional visual sensor system that proved very useful in obtaining information on the environment around the mobile robot for position reckoning. In this article, this type of navigation system is discussed. The sensor is composed of one TV camera with a fish-eye lens, using a reference target on a ceiling and hybrid image processing circuits. The position of the robot, with respect to the floor, is calculated by integrating the information obtained from a visual sensor and a gyroscope mounted in the mobile robot, and the use of a simple algorithm based on PTP control for guidance is discussed. An experimental trial showed that the proposed system was both valid and useful for the navigation of an indoor vehicle.

Inertial Sensor-Based Robust Gait Analysis in Non-Hospital Settings for Neurological Disorders

Directory of Open Access Journals (Sweden)

Can Tunca

2017-04-01

Full Text Available The gold standards for gait analysis are instrumented walkways and marker-based motion capture systems, which require costly infrastructure and are only available in hospitals and specialized gait clinics. Even though the completeness and the accuracy of these systems are unquestionable, a mobile and pervasive gait analysis alternative suitable for non-hospital settings is a clinical necessity. Using inertial sensors for gait analysis has been well explored in the literature with promising results. However, the majority of the existing work does not consider realistic conditions where data collection and sensor placement imperfections are imminent. Moreover, some of the underlying assumptions of the existing work are not compatible with pathological gait, decreasing the accuracy. To overcome these challenges, we propose a foot-mounted inertial sensor-based gait analysis system that extends the well-established zero-velocity update and Kalman filtering methodology. Our system copes with various cases of data collection difficulties and relaxes some of the assumptions invalid for pathological gait (e.g., the assumption of observing a heel strike during a gait cycle. The system is able to extract a rich set of standard gait metrics, including stride length, cadence, cycle time, stance time, swing time, stance ratio, speed, maximum/minimum clearance and turning rate. We validated the spatio-temporal accuracy of the proposed system by comparing the stride length and swing time output with an IR depth-camera-based reference system on a dataset comprised of 22 subjects. Furthermore, to highlight the clinical applicability of the system, we present a clinical discussion of the extracted metrics on a disjoint dataset of 17 subjects with various neurological conditions.

Simple method for absolute calibration of geophones, seismometers, and other inertial vibration sensors

International Nuclear Information System (INIS)

Kann, Frank van; Winterflood, John

2005-01-01

A simple but powerful method is presented for calibrating geophones, seismometers, and other inertial vibration sensors, including passive accelerometers. The method requires no cumbersome or expensive fixtures such as shaker platforms and can be performed using a standard instrument commonly available in the field. An absolute calibration is obtained using the reciprocity property of the device, based on the standard mathematical model for such inertial sensors. It requires only simple electrical measurement of the impedance of the sensor as a function of frequency to determine the parameters of the model and hence the sensitivity function. The method is particularly convenient if one of these parameters, namely the suspended mass is known. In this case, no additional mechanical apparatus is required and only a single set of impedance measurements yields the desired calibration function. Moreover, this measurement can be made with the device in situ. However, the novel and most powerful aspect of the method is its ability to accurately determine the effective suspended mass. For this, the impedance measurement is made with the device hanging from a simple spring or flexible cord (depending on the orientation of its sensitive axis). To complete the calibration, the device is weighed to determine its total mass. All the required calibration parameters, including the suspended mass, are then determined from a least-squares fit to the impedance as a function of frequency. A demonstration using both a 4.5 Hz geophone and a 1 Hz seismometer shows that the method can yield accurate absolute calibrations with an error of 0.1% or better, assuming no a priori knowledge of any parameters

Flight Test Result for the Ground-Based Radio Navigation System Sensor with an Unmanned Air Vehicle.

Science.gov (United States)

Jang, Jaegyu; Ahn, Woo-Guen; Seo, Seungwoo; Lee, Jang Yong; Park, Jun-Pyo

2015-11-11

The Ground-based Radio Navigation System (GRNS) is an alternative/backup navigation system based on time synchronized pseudolites. It has been studied for some years due to the potential vulnerability issue of satellite navigation systems (e.g., GPS or Galileo). In the framework of our study, a periodic pulsed sequence was used instead of the randomized pulse sequence recommended as the RTCM (radio technical commission for maritime services) SC (special committee)-104 pseudolite signal, as a randomized pulse sequence with a long dwell time is not suitable for applications requiring high dynamics. This paper introduces a mathematical model of the post-correlation output in a navigation sensor, showing that the aliasing caused by the additional frequency term of a periodic pulsed signal leads to a false lock (i.e., Doppler frequency bias) during the signal acquisition process or in the carrier tracking loop of the navigation sensor. We suggest algorithms to resolve the frequency false lock issue in this paper, relying on the use of a multi-correlator. A flight test with an unmanned helicopter was conducted to verify the implemented navigation sensor. The results of this analysis show that there were no false locks during the flight test and that outliers stem from bad dilution of precision (DOP) or fluctuations in the received signal quality.

GPS/MEMS IMU/Microprocessor Board for Navigation

Science.gov (United States)

Gender, Thomas K.; Chow, James; Ott, William E.

2009-01-01

A miniaturized instrumentation package comprising a (1) Global Positioning System (GPS) receiver, (2) an inertial measurement unit (IMU) consisting largely of surface-micromachined sensors of the microelectromechanical systems (MEMS) type, and (3) a microprocessor, all residing on a single circuit board, is part of the navigation system of a compact robotic spacecraft intended to be released from a larger spacecraft [e.g., the International Space Station (ISS)] for exterior visual inspection of the larger spacecraft. Variants of the package may also be useful in terrestrial collision-detection and -avoidance applications. The navigation solution obtained by integrating the IMU outputs is fed back to a correlator in the GPS receiver to aid in tracking GPS signals. The raw GPS and IMU data are blended in a Kalman filter to obtain an optimal navigation solution, which can be supplemented by range and velocity data obtained by use of (l) a stereoscopic pair of electronic cameras aboard the robotic spacecraft and/or (2) a laser dynamic range imager aboard the ISS. The novelty of the package lies mostly in those aspects of the design of the MEMS IMU that pertain to controlling mechanical resonances and stabilizing scale factors and biases.

Sensor guided control and navigation with intelligent machines. Final technical report

Energy Technology Data Exchange (ETDEWEB)

Ghosh, Bijoy K.

2001-03-26

This item constitutes the final report on ''Visionics: An integrated approach to analysis and design of intelligent machines.'' The report discusses dynamical systems approach to problems in robust control of possibly time-varying linear systems, problems in vision and visually guided control, and, finally, applications of these control techniques to intelligent navigation with a mobile platform. Robust design of a controller for a time-varying system essentially deals with the problem of synthesizing a controller that can adapt to sudden changes in the parameters of the plant and can maintain stability. The approach presented is to design a compensator that simultaneously stabilizes each and every possible mode of the plant as the parameters undergo sudden and unexpected changes. Such changes can in fact be detected by a visual sensor and, hence, visually guided control problems are studied as a natural consequence. The problem here is to detect parameters of the plant and maintain st ability in the closed loop using a ccd camera as a sensor. The main result discussed in the report is the role of perspective systems theory that was developed in order to analyze such a detection and control problem. The robust control algorithms and the visually guided control algorithms are applied in the context of a PUMA 560 robot arm control where the goal is to visually locate a moving part on a mobile turntable. Such problems are of paramount importance in manufacturing with a certain lack of structure. Sensor guided control problems are extended to problems in robot navigation using a NOMADIC mobile platform with a ccd and a laser range finder as sensors. The localization and map building problems are studied with the objective of navigation in an unstructured terrain.

Assessing locomotor skills development in childhood using wearable inertial sensor devices: the running paradigm.

Science.gov (United States)

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.

Estimating Orientation Using Magnetic and Inertial Sensors and Different Sensor Fusion Approaches: Accuracy Assessment in Manual and Locomotion Tasks

Directory of Open Access Journals (Sweden)

Elena Bergamini

2014-10-01

Full Text Available 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.

A Novel Vehicle Stationary Detection Utilizing Map Matching and IMU Sensors

Directory of Open Access Journals (Sweden)

Md. Syedul Amin

2014-01-01

Full Text Available Precise navigation is a vital need for many modern vehicular applications. The global positioning system (GPS cannot provide continuous navigation information in urban areas. The widely used inertial navigation system (INS can provide full vehicle state at high rates. However, the accuracy diverges quickly in low cost microelectromechanical systems (MEMS based INS due to bias, drift, noise, and other errors. These errors can be corrected in a stationary state. But detecting stationary state is a challenging task. A novel stationary state detection technique from the variation of acceleration, heading, and pitch and roll of an attitude heading reference system (AHRS built from the inertial measurement unit (IMU sensors is proposed. Besides, the map matching (MM algorithm detects the intersections where the vehicle is likely to stop. Combining these two results, the stationary state is detected with a smaller timing window of 3 s. A longer timing window of 5 s is used when the stationary state is detected only from the AHRS. The experimental results show that the stationary state is correctly identified and the position error is reduced to 90% and outperforms previously reported work. The proposed algorithm would help to reduce INS errors and enhance the performance of the navigation system.

Dual-EKF-Based Real-Time Celestial Navigation for Lunar Rover

Directory of Open Access Journals (Sweden)

Li Xie

2012-01-01

Full Text Available A key requirement of lunar rover autonomous navigation is to acquire state information accurately in real-time during its motion and set up a gradual parameter-based nonlinear kinematics model for the rover. In this paper, we propose a dual-extended-Kalman-filter- (dual-EKF- based real-time celestial navigation (RCN method. The proposed method considers the rover position and velocity on the lunar surface as the system parameters and establishes a constant velocity (CV model. In addition, the attitude quaternion is considered as the system state, and the quaternion differential equation is established as the state equation, which incorporates the output of angular rate gyroscope. Therefore, the measurement equation can be established with sun direction vector from the sun sensor and speed observation from the speedometer. The gyro continuous output ensures the algorithm real-time operation. Finally, we use the dual-EKF method to solve the system equations. Simulation results show that the proposed method can acquire the rover position and heading information in real time and greatly improve the navigation accuracy. Our method overcomes the disadvantage of the cumulative error in inertial navigation.

Meta-image navigation augmenters for unmanned aircraft systems (MINA for UAS)

Science.gov (United States)

Òªelik, Koray; Somani, Arun K.; Schnaufer, Bernard; Hwang, Patrick Y.; McGraw, Gary A.; Nadke, Jeremy

2013-05-01

GPS is a critical sensor for Unmanned Aircraft Systems (UASs) due to its accuracy, global coverage and small hardware footprint, but is subject to denial due to signal blockage or RF interference. When GPS is unavailable, position, velocity and attitude (PVA) performance from other inertial and air data sensors is not sufficient, especially for small UASs. Recently, image-based navigation algorithms have been developed to address GPS outages for UASs, since most of these platforms already include a camera as standard equipage. Performing absolute navigation with real-time aerial images requires georeferenced data, either images or landmarks, as a reference. Georeferenced imagery is readily available today, but requires a large amount of storage, whereas collections of discrete landmarks are compact but must be generated by pre-processing. An alternative, compact source of georeferenced data having large coverage area is open source vector maps from which meta-objects can be extracted for matching against real-time acquired imagery. We have developed a novel, automated approach called MINA (Meta Image Navigation Augmenters), which is a synergy of machine-vision and machine-learning algorithms for map aided navigation. As opposed to existing image map matching algorithms, MINA utilizes publicly available open-source geo-referenced vector map data, such as OpenStreetMap, in conjunction with real-time optical imagery from an on-board, monocular camera to augment the UAS navigation computer when GPS is not available. The MINA approach has been experimentally validated with both actual flight data and flight simulation data and results are presented in the paper.

Satellite Imagery Assisted Road-Based Visual Navigation System

Science.gov (United States)

Volkova, A.; Gibbens, P. W.

2016-06-01

There is a growing demand for unmanned aerial systems as autonomous surveillance, exploration and remote sensing solutions. Among the key concerns for robust operation of these systems is the need to reliably navigate the environment without reliance on global navigation satellite system (GNSS). This is of particular concern in Defence circles, but is also a major safety issue for commercial operations. In these circumstances, the aircraft needs to navigate relying only on information from on-board passive sensors such as digital cameras. An autonomous feature-based visual system presented in this work offers a novel integral approach to the modelling and registration of visual features that responds to the specific needs of the navigation system. It detects visual features from Google Earth* build a feature database. The same algorithm then detects features in an on-board cameras video stream. On one level this serves to localise the vehicle relative to the environment using Simultaneous Localisation and Mapping (SLAM). On a second level it correlates them with the database to localise the vehicle with respect to the inertial frame. The performance of the presented visual navigation system was compared using the satellite imagery from different years. Based on comparison results, an analysis of the effects of seasonal, structural and qualitative changes of the imagery source on the performance of the navigation algorithm is presented. * The algorithm is independent of the source of satellite imagery and another provider can be used

Application of inertial sensors and flux-gate magnetometer to real-time human body motion capture

OpenAIRE

Frey, William.

1996-01-01

Human body tracking for synthetic environment interface has become a significant human- computer interface challenge. There are several different types of motion capture systems currently available. Inherent problems, most resulting from the use of artificially-generated source signals, plague these systems. A proposed motion capture system is being developed at the Naval Postgraduate School which utilizes a combination of inertial sensors to overcome these difficulties. However, the current ...

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

Directory of Open Access Journals (Sweden)

Benedikt Fasel

2017-11-01

Full Text Available 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

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

Science.gov (United States)

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

HyMoTrack: A Mobile AR Navigation System for Complex Indoor Environments.

Science.gov (United States)

Gerstweiler, Georg; Vonach, Emanuel; Kaufmann, Hannes

2015-12-24

Navigating in unknown big indoor environments with static 2D maps is a challenge, especially when time is a critical factor. In order to provide a mobile assistant, capable of supporting people while navigating in indoor locations, an accurate and reliable localization system is required in almost every corner of the building. We present a solution to this problem through a hybrid tracking system specifically designed for complex indoor spaces, which runs on mobile devices like smartphones or tablets. The developed algorithm only uses the available sensors built into standard mobile devices, especially the inertial sensors and the RGB camera. The combination of multiple optical tracking technologies, such as 2D natural features and features of more complex three-dimensional structures guarantees the robustness of the system. All processing is done locally and no network connection is needed. State-of-the-art indoor tracking approaches use mainly radio-frequency signals like Wi-Fi or Bluetooth for localizing a user. In contrast to these approaches, the main advantage of the developed system is the capability of delivering a continuous 3D position and orientation of the mobile device with centimeter accuracy. This makes it usable for localization and 3D augmentation purposes, e.g. navigation tasks or location-based information visualization.

HyMoTrack: A Mobile AR Navigation System for Complex Indoor Environments

Directory of Open Access Journals (Sweden)

Georg Gerstweiler

2015-12-01

Full Text Available Navigating in unknown big indoor environments with static 2D maps is a challenge, especially when time is a critical factor. In order to provide a mobile assistant, capable of supporting people while navigating in indoor locations, an accurate and reliable localization system is required in almost every corner of the building. We present a solution to this problem through a hybrid tracking system specifically designed for complex indoor spaces, which runs on mobile devices like smartphones or tablets. The developed algorithm only uses the available sensors built into standard mobile devices, especially the inertial sensors and the RGB camera. The combination of multiple optical tracking technologies, such as 2D natural features and features of more complex three-dimensional structures guarantees the robustness of the system. All processing is done locally and no network connection is needed. State-of-the-art indoor tracking approaches use mainly radio-frequency signals like Wi-Fi or Bluetooth for localizing a user. In contrast to these approaches, the main advantage of the developed system is the capability of delivering a continuous 3D position and orientation of the mobile device with centimeter accuracy. This makes it usable for localization and 3D augmentation purposes, e.g. navigation tasks or location-based information visualization.

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

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

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

2014-01-01

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. (paper)

WISDOM: wheelchair inertial sensors for displacement and orientation monitoring

Science.gov (United States)

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.

WISDOM: wheelchair inertial sensors for displacement and orientation monitoring

International Nuclear Information System (INIS)

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

2011-01-01

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

Path Planning and Navigation for Mobile Robots in a Hybrid Sensor Network without Prior Location Information

Directory of Open Access Journals (Sweden)

Zheng Zhang

2013-03-01

Full Text Available In a hybrid wireless sensor network with mobile and static nodes, which have no prior geographical knowledge, successful navigation for mobile robots is one of the main challenges. In this paper, we propose two novel navigation algorithms for outdoor environments, which permit robots to travel from one static node to another along a planned path in the sensor field, namely the RAC and the IMAP algorithms. Using this, the robot can navigate without the help of a map, GPS or extra sensor modules, only using the received signal strength indication (RSSI and odometry. Therefore, our algorithms have the advantage of being cost-effective. In addition, a path planning algorithm to schedule mobile robots' travelling paths is presented, which focuses on shorter distances and robust paths for robots by considering the RSSI-Distance characteristics. The simulations and experiments conducted with an autonomous mobile robot show the effectiveness of the proposed algorithms in an outdoor environment.

Radio/FADS/IMU integrated navigation for Mars entry

Science.gov (United States)

Jiang, Xiuqiang; Li, Shuang; Huang, Xiangyu

2018-03-01

Supposing future orbiting and landing collaborative exploration mission as the potential project background, this paper addresses the issue of Mars entry integrated navigation using radio beacon, flush air data sensing system (FADS), and inertial measurement unit (IMU). The range and Doppler information sensed from an orbiting radio beacon, the dynamic pressure and heating data sensed from flush air data sensing system, and acceleration and attitude angular rate outputs from an inertial measurement unit are integrated in an unscented Kalman filter to perform state estimation and suppress the system and measurement noise. Computer simulations show that the proposed integrated navigation scheme can enhance the navigation accuracy, which enables precise entry guidance for the given Mars orbiting and landing collaborative exploration mission.

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

Directory of Open Access Journals (Sweden)

Laura Ruotsalainen

2018-02-01

Full Text Available 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

A Novel AHRS Inertial Sensor-Based Algorithm for Wheelchair Propulsion Performance Analysis

Directory of Open Access Journals (Sweden)

Jonathan Bruce Shepherd

2016-08-01

Full Text Available With the increasing rise of professionalism in sport, athletes, teams, and coaches are looking to technology to monitor performance in both games and training in order to find a competitive advantage. The use of inertial sensors has been proposed as a cost effective and adaptable measurement device for monitoring wheelchair kinematics; however, the outcomes are dependent on the reliability of the processing algorithms. Though there are a variety of algorithms that have been proposed to monitor wheelchair propulsion in court sports, they all have limitations. Through experimental testing, we have shown the Attitude and Heading Reference System (AHRS-based algorithm to be a suitable and reliable candidate algorithm for estimating velocity, distance, and approximating trajectory. The proposed algorithm is computationally inexpensive, agnostic of wheel camber, not sensitive to sensor placement, and can be embedded for real-time implementations. The research is conducted under Griffith University Ethics (GU Ref No: 2016/294.

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

Science.gov (United States)

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.

Sensors and sensor systems for guidance and navigation; Proceedings of the Meeting, Orlando, FL, Apr. 2, 3, 1991

Science.gov (United States)

Wade, Jack; Tuchman, Avi

1991-07-01

The present conference discusses wide field-of-view star-tracker cameras, discrete frequency vs radius reticle trackers, a sensor system for comet approach and landing, a static horizon sensor for a remote-sensing satellite, an improved ring laser gyro navigator, FM reticle trackers in the pupil plane, and the 2D encoding of images via discrete reticles. Also discussed are reduced-cost coil windings for interferometric fiber-optic gyro sensors, the ASTRO 1M space attitude-determination system, passive range-sensor refinement via texture and segmentation, a coherent launch-site atmospheric wind sounder, and a radar-optronic tracking experiment for short and medium range aerial combat. (For individual items see A93-27044 to A93-27046)

A Navigation System for the Visually Impaired: A Fusion of Vision and Depth Sensor

Science.gov (United States)

Kanwal, Nadia; Bostanci, Erkan; Currie, Keith; Clark, Adrian F.

2015-01-01

For a number of years, scientists have been trying to develop aids that can make visually impaired people more independent and aware of their surroundings. Computer-based automatic navigation tools are one example of this, motivated by the increasing miniaturization of electronics and the improvement in processing power and sensing capabilities. This paper presents a complete navigation system based on low cost and physically unobtrusive sensors such as a camera and an infrared sensor. The system is based around corners and depth values from Kinect's infrared sensor. Obstacles are found in images from a camera using corner detection, while input from the depth sensor provides the corresponding distance. The combination is both efficient and robust. The system not only identifies hurdles but also suggests a safe path (if available) to the left or right side and tells the user to stop, move left, or move right. The system has been tested in real time by both blindfolded and blind people at different indoor and outdoor locations, demonstrating that it operates adequately. PMID:27057135

The Use of Calixarene Thin Films in the Sensor Array for VOCs Detection and Olfactory Navigation

Directory of Open Access Journals (Sweden)

Alan F. Holloway

2010-02-01

Full Text Available This work is dedicated to the development of a sensor array for detection of volatile organic chemicals (VOCs in pre-explosive concentrations as well as for olfactory robotic navigation in the frame of two EU projects. A QCM (quartz crystal microbalance sensor array was built utilising quartz crystals spun-coated with thin films of different amphiphilic calixarene molecules to provide a base for pattern recognition of different volatile organic chemicals (VOCs. Commercial Metal-oxide semiconductor (MOS sensors were also used in the same array for the benefit of comparison. The sensor array was tested with a range of organic vapours, such as hydrocarbons, alcohols, ketones, aromatics, etc, in concentrations below LEL and up to UEL (standing for lower and upper explosion limit, respectively; the sensor array proved to be capable of identification and concentration evaluation of a range of VOCs. Comparison of QCM and MOS sensors responses to VOCs in the LEL-UEL range showed the advantage of the former. In addition, the sensor array was tested on the vapours of camphor from cinnamon oil in order to prove the concept of using the "scent marks" for robotic navigation. The results showed that the response signature of QCM coated with calixarenes to camphor is very much different from those of any other VOCs used. Adsorption and de-sorption rates of camphor are also much slower comparing to VOCs due to a high viscosity of the compound. Our experiments demonstrated the suitability of calixarene sensor array for the task and justified the use of camphor as a "scent mark" for olfactory navigation.

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

Science.gov (United States)

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.

Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems.

Science.gov (United States)

Tseng, Chien-Hao; Lin, Sheng-Fuu; Jwo, Dah-Jing

2016-07-26

This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF) and fuzzy logic adaptive system (FLAS) for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system) integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF) is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD) parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF), unscented Kalman filter (UKF), and CKF approaches.

Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems

Directory of Open Access Journals (Sweden)

Chien-Hao Tseng

2016-07-01

Full Text Available This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF and fuzzy logic adaptive system (FLAS for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF, unscented Kalman filter (UKF, and CKF approaches.

Torsion pendulum for the performance test of the inertial sensor for ASTROD-I

International Nuclear Information System (INIS)

Zhou, Z B; Gao, S W; Luo, J

2005-01-01

A torsion pendulum facility for a ground-based performance test of the inertial sensor for ASTROD-1 has been constructed. The twist motion of the test mass is monitored and servo-controlled. The sensitivity of the electrostatic servo-controlled actuator is calibrated based on the elastic torque of the torsion fibre, and the torque resolution of the servo-controlled torsion pendulum comes to 2 x 10 -11 N m Hz -1/2 from 1 mHz to 0.1 Hz, which is likely limited by the seismic noise, electronic noise and the cross coupling between the translation and twist modes

Autonomous Wheeled Robot Platform Testbed for Navigation and Mapping Using Low-Cost Sensors

Science.gov (United States)

Calero, D.; Fernandez, E.; Parés, M. E.

2017-11-01

This paper presents the concept of an architecture for a wheeled robot system that helps researchers in the field of geomatics to speed up their daily research on kinematic geodesy, indoor navigation and indoor positioning fields. The presented ideas corresponds to an extensible and modular hardware and software system aimed at the development of new low-cost mapping algorithms as well as at the evaluation of the performance of sensors. The concept, already implemented in the CTTC's system ARAS (Autonomous Rover for Automatic Surveying) is generic and extensible. This means that it is possible to incorporate new navigation algorithms or sensors at no maintenance cost. Only the effort related to the development tasks required to either create such algorithms needs to be taken into account. As a consequence, change poses a much small problem for research activities in this specific area. This system includes several standalone sensors that may be combined in different ways to accomplish several goals; that is, this system may be used to perform a variety of tasks, as, for instance evaluates positioning algorithms performance or mapping algorithms performance.

Bioinspired polarization navigation sensor for autonomous munitions systems

Science.gov (United States)

Giakos, G. C.; Quang, T.; Farrahi, T.; Deshpande, A.; Narayan, C.; Shrestha, S.; Li, Y.; Agarwal, M.

2013-05-01

Small unmanned aerial vehicles UAVs (SUAVs), micro air vehicles (MAVs), Automated Target Recognition (ATR), and munitions guidance, require extreme operational agility and robustness which can be partially offset by efficient bioinspired imaging sensor designs capable to provide enhanced guidance, navigation and control capabilities (GNC). Bioinspired-based imaging technology can be proved useful either for long-distance surveillance of targets in a cluttered environment, or at close distances limited by space surroundings and obstructions. The purpose of this study is to explore the phenomenology of image formation by different insect eye architectures, which would directly benefit the areas of defense and security, on the following four distinct areas: a) fabrication of the bioinspired sensor b) optical architecture, c) topology, and d) artificial intelligence. The outcome of this study indicates that bioinspired imaging can impact the areas of defense and security significantly by dedicated designs fitting into different combat scenarios and applications.

Extraction and Analysis of Respiratory Motion Using Wearable Inertial Sensor System during Trunk Motion

Directory of Open Access Journals (Sweden)

Apoorva Gaidhani

2017-12-01

Full Text Available 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.

Inertial sensors as measurement tools of elbow range of motion in gerontology

Science.gov (United States)

Sacco, G; Turpin, JM; Marteu, A; Sakarovitch, C; Teboul, B; Boscher, L; Brocker, P; Robert, P; Guerin, O

2015-01-01

Background and purpose Musculoskeletal system deterioration among the aging is a major reason for loss of autonomy and directly affects the quality of life of the elderly. Articular evaluation is part of physiotherapeutic assessment and helps in establishing a precise diagnosis and deciding appropriate therapy. Reference instruments are valid but not easy to use for some joints. The main goal of our study was to determine reliability and intertester reproducibility of the MP-BV, an inertial sensor (the MotionPod® [MP]) combined with specific software (BioVal [BV]), for elbow passive range-of-motion measurements in geriatrics. Methods This open, monocentric, randomized study compared inertial sensor to inclinometer in patients hospitalized in an acute, post-acute, and long-term-care gerontology unit. Results Seventy-seven patients (mean age 83.5±6.4 years, sex ratio 1.08 [male/female]) were analyzed. The MP-BV was reliable for each of the three measurements (flexion, pronation, and supination) for 24.3% (CI 95% 13.9–32.8) of the patients. Separately, the percentages of reliable measures were 59.7% (49.2–70.5) for flexion, 68.8% (58.4–79.5) for pronation, and 62.3% (51.2–73.1) for supination. The intraclass correlation coefficients were 0.15 (0.07–0.73), 0.46 (0.27–0.98), and 0.50 (0.31–40 0.98) for flexion, pronation, and supination, respectively. Conclusion This study shows the convenience of the MP-BV in terms of ease of use and of export of measured data. However, this instrument seems less reliable and valuable compared to the reference instruments used to measure elbow range of motion in gerontology. PMID:25759568

Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation.

Science.gov (United States)

Nitti, Davide O; Bovenga, Fabio; Chiaradia, Maria T; Greco, Mario; Pinelli, Gianpaolo

2015-07-28

This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class, which permits heavy and wide payloads (as required by SAR) and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM). A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimated UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system.

Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation

Directory of Open Access Journals (Sweden)

Davide O. Nitti

2015-07-01

Full Text Available This study explores the potential of Synthetic Aperture Radar (SAR to aid Unmanned Aerial Vehicle (UAV navigation when Inertial Navigation System (INS measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE UAV class, which permits heavy and wide payloads (as required by SAR and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM. A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimated UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system.

IMPLEMENTATION OF INTERTIAL NAVIGATION SYSTEM MODEL DURING AIRCRAFT TESTING

Directory of Open Access Journals (Sweden)

2016-01-01

Full Text Available The flight subset control is required during the aviation equipment test flights. In order to achieve this objective the complex consisting of strap down inertial navigation system (SINS and user equipment of satellite navigation systems (SNS can be used. Such combination needs to be used for error correction in positioning which is accumulated in SINS with time. This article shows the research results of the inertial navigation system (INS model. The results of the position- ing error calculation for various INS classes are given. Each of the examined INS has a different accumulated error for the same time lag. The methods of combining information of INS and SRNS are covered. The results obtained can be applied for upgrading the aircraft flight and navigation complexes. In particular, they can allow to continuously determine speed, coordinates, angular situation and repositioning rate of change of axes of the instrument frame.

Lifting style and participant’s sex do not affect optimal inertial sensor location for ambulatory assessment of trunk inclination

NARCIS (Netherlands)

Faber, G.S.; Chang, C.C.; Kingma, I.; Dennerlein, J.T.

2013-01-01

Trunk inclination (TI) is often used as a measure to quantify back loading in ergonomic workplace evaluation. The goal of the present study was to determine the effects of lifting style and participant's sex on the optimal inertial sensor (IS) location on the back of the trunk for the measurement of

Space Launch Systems Block 1B Preliminary Navigation System Design

Science.gov (United States)

Oliver, T. Emerson; Park, Thomas; Anzalone, Evan; Smith, Austin; Strickland, Dennis; Patrick, Sean

2018-01-01

NASA is currently building the Space Launch Systems (SLS) Block 1 launch vehicle for the Exploration Mission 1 (EM-1) test flight. In parallel, NASA is also designing the Block 1B launch vehicle. The Block 1B vehicle is an evolution of the Block 1 vehicle and extends the capability of the NASA launch vehicle. This evolution replaces the Interim Cryogenic Propulsive Stage (ICPS) with the Exploration Upper Stage (EUS). As the vehicle evolves to provide greater lift capability, increased robustness for manned missions, and the capability to execute more demanding missions so must the SLS Integrated Navigation System evolved to support those missions. This paper describes the preliminary navigation systems design for the SLS Block 1B vehicle. The evolution of the navigation hard-ware and algorithms from an inertial-only navigation system for Block 1 ascent flight to a tightly coupled GPS-aided inertial navigation system for Block 1B is described. The Block 1 GN&C system has been designed to meet a LEO insertion target with a specified accuracy. The Block 1B vehicle navigation system is de-signed to support the Block 1 LEO target accuracy as well as trans-lunar or trans-planetary injection accuracy. Additionally, the Block 1B vehicle is designed to support human exploration and thus is designed to minimize the probability of Loss of Crew (LOC) through high-quality inertial instruments and robust algorithm design, including Fault Detection, Isolation, and Recovery (FDIR) logic.

Sensor Fusion Based Model for Collision Free Mobile Robot Navigation

Science.gov (United States)

Almasri, Marwah; Elleithy, Khaled; Alajlan, Abrar

2015-01-01

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

Sensor Fusion Based Model for Collision Free Mobile Robot Navigation

Directory of Open Access Journals (Sweden)

Marwah Almasri

2015-12-01

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

iBILL: Using iBeacon and Inertial Sensors for Accurate Indoor Localization in Large Open Areas

OpenAIRE

Wu, Xudong; Shen, Ruofei; Fu, Luoyi; Tian, Xiaohua; Liu, Peng; Wang, Xinbing

2017-01-01

As a key technology that is widely adopted in location-based services (LBS), indoor localization has received considerable attention in both research and industrial areas. Despite the huge efforts made for localization using smartphone inertial sensors, its performance is still unsatisfactory in large open areas, such as halls, supermarkets, and museums, due to accumulated errors arising from the uncertainty of users’ mobility and fluctuations of magnetic field. Regarding that, this paper pre...

Inertial sensors to quantify the pivot shift test in the treatment of anterior cruciate ligament injury

OpenAIRE

ZAFFAGNINI, STEFANO; LOPOMO, NICOLA; SIGNORELLI, CECILIA; MUCCIOLI, GIULIO MARIA MARCHEGGIANI; BONANZINGA, TOMMASO; GRASSI, ALBERTO; RAGGI, FEDERICO; VISANI, ANDREA; MARCACCI, MAURILIO

2014-01-01

The main purpose of this article was to describe in detail, from the perspective of the clinical end user, a previously presented non-invasive methodology, applied in the treatment of anterior cruciate ligament injury, in which inertial sensors are used to quantify the pivot shift test. The outcomes obtained and relative considerations were compared with findings emerging from a review of the relevant updated literature. The detailed description here provided covers the system, the parameters...

Wearable Sensor Networks for Motion Capture

Directory of Open Access Journals (Sweden)

Dennis Arsenault

2015-08-01

Full Text Available This work presents the development of a full body sensor-based motion tracking system that functions through wearable inertial sensors. The system is comprised of a total of ten wearable sensors and maps the player's motions to an on-screen character in real-time. A hierarchical skeletal model was implemented that allows players to navigate and interact with the virtual world without the need of a hand-held controller. To demonstrate the capabilities of the system, a simple virtual reality game was created. As a wearable system, the ability for the users to engage in activities while not being tied to a camera system, or being forced indoors presents a significant opportunity for mobile entertainment, augmented reality and interactive systems that use the body as a significant form of input. This paper outlines the key developments necessary to implement such a system.

Urban, Indoor and Subterranean Navigation Sensors and Systems (Capteurs et systemes de navigation urbains, interieurs et souterrains)

Science.gov (United States)

2010-11-01

3-10 Multiple Images of an Image Sequence Figure 3-10 A Digital Magnetic Compass from KVH Industries 3-11 Figure 3-11 Earth’s Magnetic Field 3-11...ARINO SENER – Ingenieria y Sistemas S.A Aerospace Division Parque Tecnologico de Madrid Calle Severo Ocho 4 28760 Tres Cantos Madrid Email...experts from government, academia, industry and the military produced an analysis of future navigation sensors and systems whose performance

An Investigation Into the Feasibility of Using a Modern Gravity Gradient Instrument for Passive Aircraft Navigation and Terrain Avoidance

Science.gov (United States)

2009-03-01

the research objectives for this study are presented. It should be noted that sensor cost was not considered for this study. Additionally, further...development costs ) for gravity compensation require- ments of its trident submarine inertial navigation systems and by the Air Force Geo- physics...52]: T (r, φ, λ) = GM ae Nmax∑ n=2 n∑ m=0 (a r )n+1 (Cnm cosmλ+ Snm sinmλ)P nm(cos φ) (31) 44 where r, φ, λ are the geocentric distance, lattitude and

Motion Sensors and Transducers to Navigate an Intelligent Mechatronic Platform for Outdoor Applications

Directory of Open Access Journals (Sweden)

Michail G. PAPOUTSIDAKIS

2016-03-01

Full Text Available The initial goal of this project is to investigate if different sensor types and their attached transducers can support everyday human needs. Nowadays, there is a constant need to automate many time consuming applications not only in industrial environments but also in smaller scale applications, therefore robotics is a field that continuously tracks research interest. The area of human assistance by machines in everyday needs, continues to grow and to keep users interest very high. "Mechatronics" differ from Robotics in terms of integrated electronics, the advantage of being easily re-programmable and more over the versatility of hosting all kind of sensor types, sensor networks, transducers and actuators. In this research project, such an integrated autonomous device will be presented, focusing around the use of sensors and their feedback signals for proximity, position, motion, distance, placement and finally navigation. The ultimate sensor type choice for the task as well as all transducers signals management will also be highlighted. An up-to-date technology microcontroller will host all the above information and moreover move the mechatronic platform via motor actuators. The control algorithm which will be designed for the application is responsible for receiving all feedback signals, processing them and safely navigate the system in order to undertake its mission. The project scenario, the necessary electronic equipment and the controller design method will be highlighted in the following paragraphs of this document. Conclusions and results of sensor usage, platform's performance and problems solutions, forms the rest of this paper body.

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

Science.gov (United States)

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.

Estimation of Vertical Ground Reaction Forces and Sagittal Knee Kinematics During Running Using Three Inertial Sensors

Directory of Open Access Journals (Sweden)

Frank J. Wouda

2018-03-01

Full Text Available Analysis of running mechanics has traditionally been limited to a gait laboratory using either force plates or an instrumented treadmill in combination with a full-body optical motion capture system. With the introduction of inertial motion capture systems, it becomes possible to measure kinematics in any environment. However, kinetic information could not be provided with such technology. Furthermore, numerous body-worn sensors are required for a full-body motion analysis. The aim of this study is to examine the validity of a method to estimate sagittal knee joint angles and vertical ground reaction forces during running using an ambulatory minimal body-worn sensor setup. Two concatenated artificial neural networks were trained (using data from eight healthy subjects to estimate the kinematics and kinetics of the runners. The first artificial neural network maps the information (orientation and acceleration of three inertial sensors (placed at the lower legs and pelvis to lower-body joint angles. The estimated joint angles in combination with measured vertical accelerations are input to a second artificial neural network that estimates vertical ground reaction forces. To validate our approach, estimated joint angles were compared to both inertial and optical references, while kinetic output was compared to measured vertical ground reaction forces from an instrumented treadmill. Performance was evaluated using two scenarios: training and evaluating on a single subject and training on multiple subjects and evaluating on a different subject. The estimated kinematics and kinetics of most subjects show excellent agreement (ρ>0.99 with the reference, for single subject training. Knee flexion/extension angles are estimated with a mean RMSE <5°. Ground reaction forces are estimated with a mean RMSE < 0.27 BW. Additionaly, peak vertical ground reaction force, loading rate and maximal knee flexion during stance were compared, however, no significant

A computational platform for modeling and simulation of pipeline georeferencing systems

Energy Technology Data Exchange (ETDEWEB)

Guimaraes, A.G.; Pellanda, P.C.; Gois, J.A. [Instituto Militar de Engenharia (IME), Rio de Janeiro, RJ (Brazil); Roquette, P.; Pinto, M.; Durao, R. [Instituto de Pesquisas da Marinha (IPqM), Rio de Janeiro, RJ (Brazil); Silva, M.S.V.; Martins, W.F.; Camillo, L.M.; Sacsa, R.P.; Madeira, B. [Ministerio de Ciencia e Tecnologia (CT-PETRO2006MCT), Brasilia, DF (Brazil). Financiadora de Estudos e Projetos (FINEP). Plano Nacional de Ciencia e Tecnologia do Setor Petroleo e Gas Natural

2009-07-01

This work presents a computational platform for modeling and simulation of pipeline geo referencing systems, which was developed based on typical pipeline characteristics, on the dynamical modeling of Pipeline Inspection Gauge (PIG) and on the analysis and implementation of an inertial navigation algorithm. The software environment of PIG trajectory simulation and navigation allows the user, through a friendly interface, to carry-out evaluation tests of the inertial navigation system under different scenarios. Therefore, it is possible to define the required specifications of the pipeline geo referencing system components, such as: required precision of inertial sensors, characteristics of the navigation auxiliary system (GPS surveyed control points, odometers etc.), pipeline construction information to be considered in order to improve the trajectory estimation precision, and the signal processing techniques more suitable for the treatment of inertial sensors data. The simulation results are analyzed through the evaluation of several performance metrics usually considered in inertial navigation applications, and 2D and 3D plots of trajectory estimation error and of recovered trajectory in the three coordinates are made available to the user. This paper presents the simulation platform and its constituting modules and defines their functional characteristics and interrelationships.(author)

Research on robot navigation vision sensor based on grating projection stereo vision

Science.gov (United States)

Zhang, Xiaoling; Luo, Yinsheng; Lin, Yuchi; Zhu, Lei

2016-10-01

A novel visual navigation method based on grating projection stereo vision for mobile robot in dark environment is proposed. This method is combining with grating projection profilometry of plane structured light and stereo vision technology. It can be employed to realize obstacle detection, SLAM (Simultaneous Localization and Mapping) and vision odometry for mobile robot navigation in dark environment without the image match in stereo vision technology and without phase unwrapping in the grating projection profilometry. First, we research the new vision sensor theoretical, and build geometric and mathematical model of the grating projection stereo vision system. Second, the computational method of 3D coordinates of space obstacle in the robot's visual field is studied, and then the obstacles in the field is located accurately. The result of simulation experiment and analysis shows that this research is useful to break the current autonomous navigation problem of mobile robot in dark environment, and to provide the theoretical basis and exploration direction for further study on navigation of space exploring robot in the dark and without GPS environment.

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

Science.gov (United States)

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.

An Adaptive Technique for a Redundant-Sensor Navigation System. Ph.D. Thesis

Science.gov (United States)

Chien, T. T.

1972-01-01

An on-line adaptive technique is developed to provide a self-contained redundant-sensor navigation system with a capability to utilize its full potentiality in reliability and performance. The gyro navigation system is modeled as a Gauss-Markov process, with degradation modes defined as changes in characteristics specified by parameters associated with the model. The adaptive system is formulated as a multistage stochastic process: (1) a detection system, (2) an identification system and (3) a compensation system. It is shown that the sufficient statistics for the partially observable process in the detection and identification system is the posterior measure of the state of degradation, conditioned on the measurement history.

Optimization of reliability centered predictive maintenance scheme for inertial navigation system

International Nuclear Information System (INIS)

Jiang, Xiuhong; Duan, Fuhai; Tian, Heng; Wei, Xuedong

2015-01-01

The goal of this study is to propose a reliability centered predictive maintenance scheme for a complex structure Inertial Navigation System (INS) with several redundant components. GO Methodology is applied to build the INS reliability analysis model—GO chart. Components Remaining Useful Life (RUL) and system reliability are updated dynamically based on the combination of components lifetime distribution function, stress samples, and the system GO chart. Considering the redundant design in INS, maintenance time is based not only on components RUL, but also (and mainly) on the timing of when system reliability fails to meet the set threshold. The definition of components maintenance priority balances three factors: components importance to system, risk degree, and detection difficulty. Maintenance Priority Number (MPN) is introduced, which may provide quantitative maintenance priority results for all components. A maintenance unit time cost model is built based on components MPN, components RUL predictive model and maintenance intervals for the optimization of maintenance scope. The proposed scheme can be applied to serve as the reference for INS maintenance. Finally, three numerical examples prove the proposed predictive maintenance scheme is feasible and effective. - Highlights: • A dynamic PdM with a rolling horizon is proposed for INS with redundant components. • GO Methodology is applied to build the system reliability analysis model. • A concept of MPN is proposed to quantify the maintenance sequence of components. • An optimization model is built to select the optimal group of maintenance components. • The optimization goal is minimizing the cost of maintaining system reliability

Low Cost Integrated Navigation System for Unmanned Vessel

Directory of Open Access Journals (Sweden)

Yang Changsong

2017-11-01

Full Text Available Large errors of low-cost MEMS inertial measurement unit (MIMU lead to huge navigation errors, even wrong navigation information. An integrated navigation system for unmanned vessel is proposed. It consists of a low-cost MIMU and Doppler velocity sonar (DVS. This paper presents an integrated navigation method, to improve the performance of navigation system. The integrated navigation system is tested using simulation and semi-physical simulation experiments, whose results show that attitude, velocity and position accuracy has improved awfully, giving exactly accurate navigation results. By means of the combination of low-cost MIMU and DVS, the proposed system is able to overcome fast drift problems of the low cost IMU.

FLIGHT DEVELOPMENT OF A DISTRIBUTED INERTIAL SATELLITE MICRONAVIGATTION SYSTEM FOR SYNTHETIC - APERTURE RADAR

Directory of Open Access Journals (Sweden)

Alexander Vladimirovich Chernodarov

2017-01-01

Full Text Available The current state of the onboard systems is characterized by the integration of aviation and radio-electronic equipment systems for solving problems of navigation and control. These problems include micro-navigation of the anten- na phase center (APC of the radar during the review of the Earth's surface from aboard the aircraft. Increasing of the reso- lution of the radar station (RLS by hardware increasing the antenna size is not always possible due to restrictions on the aircraft onboard equipment weight and dimensions. Therefore the implementation of analytic extension of the radiation pattern by "gluing" the images, obtained by RLS on the aircraft motion trajectory is embodied. The estimations are con- verted into amendments to the signals of RLS with synthetic aperture RSA to compensate instabilities. The purpose of the research is building a theoretical basis and a practical implementation of procedures for evaluating the trajectory APS in- stabilities using a distributed system of inertial-satellite micro-navigation (DSMN taking into account the RSA flight oper- ations actual conditions. The technology of evaluation and compensation of RSA trajectory instabilities via DSMN is con- sidered. The implementation of this technology is based on the mutual support of inertial, satellite and radar systems. Syn- chronization procedures of inertial and satellite measurements in the evaluation of DSMN errors are proposed. The given results of DSMN flight testing justify the possibility and expediency to apply the proposed technology in order to improve the resolution of RSA. The compensation of aircraft trajectory instabilities in RSA signals can be provided by inertial- satellite micro-navigation system, taking into account the actual conditions of the RSA flight operations. The researches show that in order to achieve the required resolution of RSA it seems to be appropriate to define the rational balance be- tween accuracy DSMN characteristics

Inertia compensated force and pressure sensors

Energy Technology Data Exchange (ETDEWEB)

Bill, B.; Engeler, P.; Gossweiler, C. [Kistler Instrumente AG, Winterthur (Switzerland)

2001-07-01

Any moving structure is affected by inertial effects. In case of force and pressure sensors, inertial effects cause measurement errors. The paper deals with novel signal conditioning methods and mechanical design features to minimize inertial effects. A novel solution for passive compensation of pressure sensors is presented. (orig.)

Intelligent personal navigator supported by knowledge-based systems for estimating dead reckoning navigation parameters

Science.gov (United States)

Moafipoor, Shahram

Personal navigators (PN) have been studied for about a decade in different fields and applications, such as safety and rescue operations, security and emergency services, and police and military applications. The common goal of all these applications is to provide precise and reliable position, velocity, and heading information of each individual in various environments. In the PN system developed in this dissertation, the underlying assumption is that the system does not require pre-existing infrastructure to enable pedestrian navigation. To facilitate this capability, a multisensor system concept, based on the Global Positioning System (GPS), inertial navigation, barometer, magnetometer, and a human pedometry model has been developed. An important aspect of this design is to use the human body as navigation sensor to facilitate Dead Reckoning (DR) navigation in GPS-challenged environments. The system is designed predominantly for outdoor environments, where occasional loss of GPS lock may happen; however, testing and performance demonstration have been extended to indoor environments. DR navigation is based on a relative-measurement approach, with the key idea of integrating the incremental motion information in the form of step direction (SD) and step length (SL) over time. The foundation of the intelligent navigation system concept proposed here rests in exploiting the human locomotion pattern, as well as change of locomotion in varying environments. In this context, the term intelligent navigation represents the transition from the conventional point-to-point DR to dynamic navigation using the knowledge about the mechanism of the moving person. This approach increasingly relies on integrating knowledge-based systems (KBS) and artificial intelligence (AI) methodologies, including artificial neural networks (ANN) and fuzzy logic (FL). In addition, a general framework of the quality control for the real-time validation of the DR processing is proposed, based on a

Vision Sensor-Based Road Detection for Field Robot Navigation

Directory of Open Access Journals (Sweden)

Keyu Lu

2015-11-01

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

A 16-bit sigma-delta modulator applied in micro-machined inertial sensors

Science.gov (United States)

Honglin, Xu; Qiang, Fu; Hongna, Liu; Liang, Yin; Pengfei, Wang; Xiaowei, Liu

2014-04-01

A fourth-order low-distortion low-pass sigma-delta (ΣΔ) modulator is presented for micro-machined inertial sensors. The proposed single-loop single-bit feedback modulator is optimized with a feed-forward path to decrease the nonlinearities and power consumption. The IC is implemented in a standard 0.6 μm CMOS technology and operates at a sampling frequency of 3.846 MHz. The chip area is 2.12 mm2 with 23 pads. The experimental results indicate a signal-to-noise ratio (SNR) of 100 dB and dynamic range (DR) of 103 dB at an oversampling rate (OSR) of 128 with the input signal amplitude of -3.88 dBFS at 9.8 kHz; the power consumption is 15 mW at a 5 V supply.

A 16-bit sigma–delta modulator applied in micro-machined inertial sensors

International Nuclear Information System (INIS)

Xu Honglin; Fu Qiang; Liu Hongna; Yin Liang; Wang Pengfei; Liu Xiaowei

2014-01-01

A fourth-order low-distortion low-pass sigma–delta (ΣΔ) modulator is presented for micro-machined inertial sensors. The proposed single-loop single-bit feedback modulator is optimized with a feed-forward path to decrease the nonlinearities and power consumption. The IC is implemented in a standard 0.6 μm CMOS technology and operates at a sampling frequency of 3.846 MHz. The chip area is 2.12 mm 2 with 23 pads. The experimental results indicate a signal-to-noise ratio (SNR) of 100 dB and dynamic range (DR) of 103 dB at an oversampling rate (OSR) of 128 with the input signal amplitude of −3.88 dBFS at 9.8 kHz; the power consumption is 15 mW at a 5 V supply. (semiconductor integrated circuits)

GPS/INS Sensor Fusion Using GPS Wind up Model

Science.gov (United States)

Williamson, Walton R. (Inventor)

2013-01-01

A method of stabilizing an inertial navigation system (INS), includes the steps of: receiving data from an inertial navigation system; and receiving a finite number of carrier phase observables using at least one GPS receiver from a plurality of GPS satellites; calculating a phase wind up correction; correcting at least one of the finite number of carrier phase observables using the phase wind up correction; and calculating a corrected IMU attitude or velocity or position using the corrected at least one of the finite number of carrier phase observables; and performing a step selected from the steps consisting of recording, reporting, or providing the corrected IMU attitude or velocity or position to another process that uses the corrected IMU attitude or velocity or position. A GPS stabilized inertial navigation system apparatus is also described.

SGA-WZ: A New Strapdown Airborne Gravimeter

Directory of Open Access Journals (Sweden)

Kaidong Zhang

2012-07-01

Full Text Available 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.

Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1

Science.gov (United States)

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.

Fault-tolerant and Diagnostic Methods for Navigation

DEFF Research Database (Denmark)

Blanke, Mogens

2003-01-01

to diagnose faults and autonomously provide valid navigation data, disregarding any faulty sensor data and use sensor fusion to obtain a best estimate for users. This paper discusses how diagnostic and fault-tolerant methods are applicable in marine systems. An example chosen is sensor fusion for navigation......Precise and reliable navigation is crucial, and for reasons of safety, essential navigation instruments are often duplicated. Hardware redundancy is mostly used to manually switch between instruments should faults occur. In contrast, diagnostic methods are available that can use analytic redundancy...

Sensors and sensor systems for guidance and navigation II; Proceedings of the Meeting, Orlando, FL, Apr. 22, 23, 1992

Science.gov (United States)

Welch, Sharon S.

Topics discussed in this volume include aircraft guidance and navigation, optics for visual guidance of aircraft, spacecraft and missile guidance and navigation, lidar and ladar systems, microdevices, gyroscopes, cockpit displays, and automotive displays. Papers are presented on optical processing for range and attitude determination, aircraft collision avoidance using a statistical decision theory, a scanning laser aircraft surveillance system for carrier flight operations, star sensor simulation for astroinertial guidance and navigation, autonomous millimeter-wave radar guidance systems, and a 1.32-micron long-range solid state imaging ladar. Attention is also given to a microfabricated magnetometer using Young's modulus changes in magnetoelastic materials, an integrated microgyroscope, a pulsed diode ring laser gyroscope, self-scanned polysilicon active-matrix liquid-crystal displays, the history and development of coated contrast enhancement filters for cockpit displays, and the effect of the display configuration on the attentional sampling performance. (For individual items see A93-28152 to A93-28176, A93-28178 to A93-28180)

A State-of-the-Art Survey of Indoor Positioning and Navigation Systems and Technologies

Directory of Open Access Journals (Sweden)

Wilson Sakpere

2017-12-01

Full Text Available The research and use of positioning and navigation technologies outdoors has seen a steady and exponential growth. Based on this success, there have been attempts to implement these technologies indoors, leading to numerous studies. Most of the algorithms, techniques and technologies used have been implemented outdoors. However, how they fare indoors is different altogether. Thus, several technologies have been proposed and implemented to improve positioning and navigation indoors. Among them are Infrared (IR, Ultrasound, Audible Sound, Magnetic, Optical and Vision, Radio Frequency (RF, Visible Light, Pedestrian Dead Reckoning (PDR/Inertial Navigation System (INS and Hybrid. The RF technologies include Bluetooth, Ultra-wideband (UWB, Wireless Sensor Network (WSN, Wireless Local Area Network (WLAN, Radio-Frequency Identification (RFID and Near Field Communication (NFC. In addition, positioning techniques applied in indoor positioning systems include the signal properties and positioning algorithms. The prevalent signal properties are Angle of Arrival (AOA, Time of Arrival (TOA, Time Difference of Arrival (TDOA and Received Signal Strength Indication (RSSI, while the positioning algorithms are Triangulation, Trilateration, Proximity and Scene Analysis/ Fingerprinting. This paper presents a state-of-the-art survey of indoor positioning and navigation systems and technologies, and their use in various scenarios. It analyses distinct positioning technology metrics such as accuracy, complexity, cost, privacy, scalability and usability. This paper has profound implications for future studies of positioning and navigation.

Vertical Jump Height Estimation Algorithm Based on Takeoff and Landing Identification Via Foot-Worn Inertial Sensing.

Science.gov (United States)

Wang, Jianren; Xu, Junkai; Shull, Peter B

2018-03-01

Vertical jump height is widely used for assessing motor development, functional ability, and motor capacity. Traditional methods for estimating vertical jump height rely on force plates or optical marker-based motion capture systems limiting assessment to people with access to specialized laboratories. Current wearable designs need to be attached to the skin or strapped to an appendage which can potentially be uncomfortable and inconvenient to use. This paper presents a novel algorithm for estimating vertical jump height based on foot-worn inertial sensors. Twenty healthy subjects performed countermovement jumping trials and maximum jump height was determined via inertial sensors located above the toe and under the heel and was compared with the gold standard maximum jump height estimation via optical marker-based motion capture. Average vertical jump height estimation errors from inertial sensing at the toe and heel were -2.2±2.1 cm and -0.4±3.8 cm, respectively. Vertical jump height estimation with the presented algorithm via inertial sensing showed excellent reliability at the toe (ICC(2,1)=0.98) and heel (ICC(2,1)=0.97). There was no significant bias in the inertial sensing at the toe, but proportional bias (b=1.22) and fixed bias (a=-10.23cm) were detected in inertial sensing at the heel. These results indicate that the presented algorithm could be applied to foot-worn inertial sensors to estimate maximum jump height enabling assessment outside of traditional laboratory settings, and to avoid bias errors, the toe may be a more suitable location for inertial sensor placement than the heel.

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

Directory of Open Access Journals (Sweden)

Paula Jimena Ramos Giraldo

2017-04-01

Full Text Available 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.

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

Science.gov (United States)

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.

Investigation of Anticipatory Postural Adjustments during One-Leg Stance Using Inertial Sensors: Evidence from Subjects with Parkinsonism.

Science.gov (United States)

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   0.74), 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.

Investigation of Matlab® as platform in navigation and control of an Automatic Guided Vehicle utilising an omnivision sensor.

Science.gov (United States)

Kotze, Ben; Jordaan, Gerrit

2014-08-25

Automatic Guided Vehicles (AGVs) are navigated utilising multiple types of sensors for detecting the environment. In this investigation such sensors are replaced and/or minimized by the use of a single omnidirectional camera picture stream. An area of interest is extracted, and by using image processing the vehicle is navigated on a set path. Reconfigurability is added to the route layout by signs incorporated in the navigation process. The result is the possible manipulation of a number of AGVs, each on its own designated colour-signed path. This route is reconfigurable by the operator with no programming alteration or intervention. A low resolution camera and a Matlab® software development platform are utilised. The use of Matlab® lends itself to speedy evaluation and implementation of image processing options on the AGV, but its functioning in such an environment needs to be assessed.

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

Science.gov (United States)

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.

Revised electrostatic model of the LISA Pathfinder inertial sensor

Energy Technology Data Exchange (ETDEWEB)

Brandt, Nico [Astrium GmbH, 88039 Friedrichshafen (Germany); Fichter, Walter, E-mail: nico.brandt@astrium.eads.ne [iFR, Universitaet Stuttgart, Pfaffenwaldring 7a, 70569 Stuttgart (Germany)

2009-03-01

A comprehensive electrostatic finite-element (FE) analysis of the LISA Pathfinder Inertial Sensor (IS) has been carried out at Astrium GmbH. Starting with a detailed geometrical model of the IS housing and test mass (TM) flight units, FE results were derived from multiple analyses runs applying the Maxwell 3D field simulation software. The electrostatic forces and torques on the TM in 6DoF, as well as all non-negligible capacitances between the TM, the 18 electrodes, and the housing, have been extracted for different TM translations and rotations. The results of the FE analyses were expected to confirm the existing IS electrostatic model predictions used for performance analysis, simulations, and on-board algorithms. Major discrepancies were found, however, between the results and the model used so far. In general, FE results give considerably larger capacitance values than the equivalent infinite non-parallel plate estimates. In contrast, the FE derived forces and torques are in general significantly lower compared to the analytic IS electrostatic model predictions. In this paper, these results are discussed in detail and the reasons for the deviations are elaborated. Based on these results, an adapted analytic IS electrostatic model is proposed that reflects the electrostatic forces, torques, and stiffness values in the LISA Pathfinder IS significantly more accurate.

Revised electrostatic model of the LISA Pathfinder inertial sensor

International Nuclear Information System (INIS)

Brandt, Nico; Fichter, Walter

2009-01-01

A comprehensive electrostatic finite-element (FE) analysis of the LISA Pathfinder Inertial Sensor (IS) has been carried out at Astrium GmbH. Starting with a detailed geometrical model of the IS housing and test mass (TM) flight units, FE results were derived from multiple analyses runs applying the Maxwell 3D field simulation software. The electrostatic forces and torques on the TM in 6DoF, as well as all non-negligible capacitances between the TM, the 18 electrodes, and the housing, have been extracted for different TM translations and rotations. The results of the FE analyses were expected to confirm the existing IS electrostatic model predictions used for performance analysis, simulations, and on-board algorithms. Major discrepancies were found, however, between the results and the model used so far. In general, FE results give considerably larger capacitance values than the equivalent infinite non-parallel plate estimates. In contrast, the FE derived forces and torques are in general significantly lower compared to the analytic IS electrostatic model predictions. In this paper, these results are discussed in detail and the reasons for the deviations are elaborated. Based on these results, an adapted analytic IS electrostatic model is proposed that reflects the electrostatic forces, torques, and stiffness values in the LISA Pathfinder IS significantly more accurate.

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

Science.gov (United States)

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.

Using neuromorphic optical sensors for spacecraft absolute and relative navigation

Science.gov (United States)

Shake, Christopher M.

We develop a novel attitude determination system (ADS) for use on nano spacecraft using neuromorphic optical sensors. The ADS intends to support nano-satellite operations by providing low-cost, low-mass, low-volume, low-power, and redundant attitude determination capabilities with quick and straightforward onboard programmability for real time spacecraft operations. The ADS is experimentally validated with commercial-off-the-shelf optical devices that perform sensing and image processing on the same circuit board and are biologically inspired by insects' vision systems, which measure optical flow while navigating in the environment. The firmware on the devices is modified to both perform the additional biologically inspired task of tracking objects and communicate with a PC/104 form-factor embedded computer running Real Time Application Interface Linux used on a spacecraft simulator. Algorithms are developed for operations using optical flow, point tracking, and hybrid modes with the sensors, and the performance of the system in all three modes is assessed using a spacecraft simulator in the Advanced Autonomous Multiple Spacecraft (ADAMUS) laboratory at Rensselaer. An existing relative state determination method is identified to be combined with the novel ADS to create a self-contained navigation system for nano spacecraft. The performance of the method is assessed in simulation and found not to match the results from its authors using only conditions and equations already published. An improved target inertia tensor method is proposed as an update to the existing relative state method, but found not to perform as expected, but is presented for others to build upon.

Symposium Gyro Technology 1997

Energy Technology Data Exchange (ETDEWEB)

Sorg, H [ed.; Stuttgart Univ. (Germany). Inst. A fuer Mechanik

1997-10-01

This volume includes the twenty papers which were presented at the Symposium Gyro Technology 1997. The subjects that have been treated during the symposium were as follows: Performance and design of silicon micromachined gyro; improved rate gyroscope designs designated for fabrication by modern deep silicon etching; micromechanical vibratory rate gyroscopes fabricated in conventional CMOS; error modelling of silicon angular rate sensor; a capacitive accelerometer as an example for surface micromachined inertial sensors; initial production results of a new family of fiber optic gyroscopes; dual-axis multiplexed open loop fiber optic gyroscope; flattely supported vibratory gyro-sensor using a Trident-type tuning fork resonator; innovative mechanizations to optimize inertial sensors for high or low rate operations; design of a planar vibratory gyroscope using electrostatic actuation and electromanetic detection; fiber optic gyro based land navigation system; FOG AHRS and AHRS/GPS navigation system: the low cost solution; GPS/GLONASS/INS-navigation (GLOGINAV); small-sized integrated system of the sea mobile objects attitude and navigation; concepts for hybrid positioning; preliminary results from a large ring laser gyroscope for fundamental physics and geophysics; a `sense of balance` - AHRS with low-cost vibrating-gyroscopes for medical diagnostics; application of strapdown inertial systems of orientation and navigation in intrapipe moving diagnostic apparatus; investigation of a digital readout system for laser gyro; the use of angular rate multiple integrals as input signals for strapdown attitude algorithms. (AKF)

An activity recognition model using inertial sensor nodes in a wireless sensor network for frozen shoulder rehabilitation exercises.

Science.gov (United States)

Lin, Hsueh-Chun; Chiang, Shu-Yin; Lee, Kai; Kan, Yao-Chiang

2015-01-19

This paper proposes a model for recognizing motions performed during rehabilitation exercises for frozen shoulder conditions. The model consists of wearable wireless sensor network (WSN) inertial sensor nodes, which were developed for this study, and enables the ubiquitous measurement of bodily motions. The model employs the back propagation neural network (BPNN) algorithm to compute motion data that are formed in the WSN packets; herein, six types of rehabilitation exercises were recognized. The packets sent by each node are converted into six components of acceleration and angular velocity according to three axes. Motor features such as basic acceleration, angular velocity, and derivative tilt angle were input into the training procedure of the BPNN algorithm. In measurements of thirteen volunteers, the accelerations and included angles of nodes were adopted from possible features to demonstrate the procedure. Five exercises involving simple swinging and stretching movements were recognized with an accuracy of 85%-95%; however, the accuracy with which exercises entailing spiral rotations were recognized approximately 60%. Thus, a characteristic space and enveloped spectrum improving derivative features were suggested to enable identifying customized parameters. Finally, a real-time monitoring interface was developed for practical implementation. The proposed model can be applied in ubiquitous healthcare self-management to recognize rehabilitation exercises.

An Activity Recognition Model Using Inertial Sensor Nodes in a Wireless Sensor Network for Frozen Shoulder Rehabilitation Exercises

Directory of Open Access Journals (Sweden)

Hsueh-Chun Lin

2015-01-01

Full Text Available This paper proposes a model for recognizing motions performed during rehabilitation exercises for frozen shoulder conditions. The model consists of wearable wireless sensor network (WSN inertial sensor nodes, which were developed for this study, and enables the ubiquitous measurement of bodily motions. The model employs the back propagation neural network (BPNN algorithm to compute motion data that are formed in the WSN packets; herein, six types of rehabilitation exercises were recognized. The packets sent by each node are converted into six components of acceleration and angular velocity according to three axes. Motor features such as basic acceleration, angular velocity, and derivative tilt angle were input into the training procedure of the BPNN algorithm. In measurements of thirteen volunteers, the accelerations and included angles of nodes were adopted from possible features to demonstrate the procedure. Five exercises involving simple swinging and stretching movements were recognized with an accuracy of 85%–95%; however, the accuracy with which exercises entailing spiral rotations were recognized approximately 60%. Thus, a characteristic space and enveloped spectrum improving derivative features were suggested to enable identifying customized parameters. Finally, a real-time monitoring interface was developed for practical implementation. The proposed model can be applied in ubiquitous healthcare self-management to recognize rehabilitation exercises.

Investigation of Matlab® as Platform in Navigation and Control of an Automatic Guided Vehicle Utilising an Omnivision Sensor

Directory of Open Access Journals (Sweden)

Ben Kotze

2014-08-01

Full Text Available Automatic Guided Vehicles (AGVs are navigated utilising multiple types of sensors for detecting the environment. In this investigation such sensors are replaced and/or minimized by the use of a single omnidirectional camera picture stream. An area of interest is extracted, and by using image processing the vehicle is navigated on a set path. Reconfigurability is added to the route layout by signs incorporated in the navigation process. The result is the possible manipulation of a number of AGVs, each on its own designated colour-signed path. This route is reconfigurable by the operator with no programming alteration or intervention. A low resolution camera and a Matlab® software development platform are utilised. The use of Matlab® lends itself to speedy evaluation and implementation of image processing options on the AGV, but its functioning in such an environment needs to be assessed.

Autonomous GPS/INS navigation experiment for Space Transfer Vehicle

Science.gov (United States)

Upadhyay, Triveni N.; Cotterill, Stephen; Deaton, A. W.

1993-01-01

An experiment to validate the concept of developing an autonomous integrated spacecraft navigation system using on board Global Positioning System (GPS) and Inertial Navigation System (INS) measurements is described. The feasibility of integrating GPS measurements with INS measurements to provide a total improvement in spacecraft navigation performance, i.e. improvement in position, velocity and attitude information, was previously demonstrated. An important aspect of this research is the automatic real time reconfiguration capability of the system designed to respond to changes in a spacecraft mission under the control of an expert system.

SLS Block 1-B and Exploration Upper Stage Navigation System Design

Science.gov (United States)

Oliver, T. Emerson; Park, Thomas B.; Smith, Austin; Anzalone, Evan; Bernard, Bill; Strickland, Dennis; Geohagan, Kevin; Green, Melissa; Leggett, Jarred

2018-01-01

The SLS Block 1B vehicle is planned to extend NASA's heavy lift capability beyond the initial SLS Block 1 vehicle. The most noticeable change for this vehicle from SLS Block 1 is the swapping of the upper stage from the Interim Cryogenic Propulsion stage (ICPS), a modified Delta IV upper stage, to the more capable Exploration Upper Stage (EUS). As the vehicle evolves to provide greater lift capability and execute more demanding missions so must the SLS Integrated Navigation System to support those missions. The SLS Block 1 vehicle carries two independent navigation systems. The responsibility of the two systems is delineated between ascent and upper stage flight. The Block 1 navigation system is responsible for the phase of flight between the launch pad and insertion into Low-Earth Orbit (LEO). The upper stage system assumes the mission from LEO to payload separation. For the Block 1B vehicle, the two functions are combined into a single system intended to navigate from ground to payload insertion. Both are responsible for self-disposal once payload delivery is achieved. The evolution of the navigation hardware and algorithms from an inertial-only navigation system for Block 1 ascent flight to a tightly coupled GPS-aided inertial navigation system for Block 1-B is described. The Block 1 GN&C system has been designed to meet a LEO insertion target with a specified accuracy. The Block 1-B vehicle navigation system is designed to support the Block 1 LEO target accuracy as well as trans-lunar or trans-planetary injection accuracy. This is measured in terms of payload impact and stage disposal requirements. Additionally, the Block 1-B vehicle is designed to support human exploration and thus is designed to minimize the probability of Loss of Crew (LOC) through high-quality inertial instruments and Fault Detection, Isolation, and Recovery (FDIR) logic. The preliminary Block 1B integrated navigation system design is presented along with the challenges associated with

Enabling UAV Navigation with Sensor and Environmental Uncertainty in Cluttered and GPS-Denied Environments

Directory of Open Access Journals (Sweden)

Fernando Vanegas

2016-05-01

Full Text Available Unmanned Aerial Vehicles (UAV can navigate with low risk in obstacle-free environments using ground control stations that plan a series of GPS waypoints as a path to follow. This GPS waypoint navigation does however become dangerous in environments where the GPS signal is faulty or is only present in some places and when the airspace is filled with obstacles. UAV navigation then becomes challenging because the UAV uses other sensors, which in turn generate uncertainty about its localisation and motion systems, especially if the UAV is a low cost platform. Additional uncertainty affects the mission when the UAV goal location is only partially known and can only be discovered by exploring and detecting a target. This navigation problem is established in this research as a Partially-Observable Markov Decision Process (POMDP, so as to produce a policy that maps a set of motion commands to belief states and observations. The policy is calculated and updated on-line while flying with a newly-developed system for UAV Uncertainty-Based Navigation (UBNAV, to navigate in cluttered and GPS-denied environments using observations and executing motion commands instead of waypoints. Experimental results in both simulation and real flight tests show that the UAV finds a path on-line to a region where it can explore and detect a target without colliding with obstacles. UBNAV provides a new method and an enabling technology for scientists to implement and test UAV navigation missions with uncertainty where targets must be detected using on-line POMDP in real flight scenarios.

Enabling UAV Navigation with Sensor and Environmental Uncertainty in Cluttered and GPS-Denied Environments.

Science.gov (United States)

Vanegas, Fernando; Gonzalez, Felipe

2016-05-10

Unmanned Aerial Vehicles (UAV) can navigate with low risk in obstacle-free environments using ground control stations that plan a series of GPS waypoints as a path to follow. This GPS waypoint navigation does however become dangerous in environments where the GPS signal is faulty or is only present in some places and when the airspace is filled with obstacles. UAV navigation then becomes challenging because the UAV uses other sensors, which in turn generate uncertainty about its localisation and motion systems, especially if the UAV is a low cost platform. Additional uncertainty affects the mission when the UAV goal location is only partially known and can only be discovered by exploring and detecting a target. This navigation problem is established in this research as a Partially-Observable Markov Decision Process (POMDP), so as to produce a policy that maps a set of motion commands to belief states and observations. The policy is calculated and updated on-line while flying with a newly-developed system for UAV Uncertainty-Based Navigation (UBNAV), to navigate in cluttered and GPS-denied environments using observations and executing motion commands instead of waypoints. Experimental results in both simulation and real flight tests show that the UAV finds a path on-line to a region where it can explore and detect a target without colliding with obstacles. UBNAV provides a new method and an enabling technology for scientists to implement and test UAV navigation missions with uncertainty where targets must be detected using on-line POMDP in real flight scenarios.

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

Science.gov (United States)

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.

Study on polarized optical flow algorithm for imaging bionic polarization navigation micro sensor

Science.gov (United States)

Guan, Le; Liu, Sheng; Li, Shi-qi; Lin, Wei; Zhai, Li-yuan; Chu, Jin-kui

2018-05-01

At present, both the point source and the imaging polarization navigation devices only can output the angle information, which means that the velocity information of the carrier cannot be extracted from the polarization field pattern directly. Optical flow is an image-based method for calculating the velocity of pixel point movement in an image. However, for ordinary optical flow, the difference in pixel value as well as the calculation accuracy can be reduced in weak light. Polarization imaging technology has the ability to improve both the detection accuracy and the recognition probability of the target because it can acquire the extra polarization multi-dimensional information of target radiation or reflection. In this paper, combining the polarization imaging technique with the traditional optical flow algorithm, a polarization optical flow algorithm is proposed, and it is verified that the polarized optical flow algorithm has good adaptation in weak light and can improve the application range of polarization navigation sensors. This research lays the foundation for day and night all-weather polarization navigation applications in future.

A New Calibration Methodology for Thorax and Upper Limbs Motion Capture in Children Using Magneto and Inertial Sensors

Directory of Open Access Journals (Sweden)

Luca Ricci

2014-01-01

Full Text Available 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.

A new calibration method for tri-axial field sensors in strap-down navigation systems

International Nuclear Information System (INIS)

Li, Xiang; Li, Zhi

2012-01-01

This paper presents a novel calibration method for tri-axial field sensors, such as magnetometers and accelerometers, in strap-down navigation systems. Strap-down tri-axial sensors have been widely used as they have the advantages of small size and low cost, but they need to be calibrated in order to ensure their accuracy. The most commonly used calibration method for a tri-axial field sensor is based on ellipsoid fitting, which has no requirement for external references. However, the self-calibration based on ellipsoid fitting is unable to determine and compensate the mutual misalignment between different sensors in a multi-sensor system. Therefore, a novel calibration method that employs the invariance of the dot product of two constant vectors is introduced in this paper. The proposed method, which is named dot product invariance method, brings a complete solution for the error model of tri-axial field sensors, and can solve the problem of alignment in a multi-sensor system. Its effectiveness and superiority over the ellipsoid fitting method are illustrated by numerical simulations, and its application on a digital magnetic compass shows significant enhancement of the heading accuracy. (paper)

Control algorithms for autonomous robot navigation

International Nuclear Information System (INIS)

Jorgensen, C.C.

1985-01-01

This paper examines control algorithm requirements for autonomous robot navigation outside laboratory environments. Three aspects of navigation are considered: navigation control in explored terrain, environment interactions with robot sensors, and navigation control in unanticipated situations. Major navigation methods are presented and relevance of traditional human learning theory is discussed. A new navigation technique linking graph theory and incidental learning is introduced

SINS/CNS Nonlinear Integrated Navigation Algorithm for Hypersonic Vehicle

Directory of Open Access Journals (Sweden)

Yong-jun Yu

2015-01-01

Full Text Available Celestial Navigation System (CNS has characteristics of accurate orientation and strong autonomy and has been widely used in Hypersonic Vehicle. Since the CNS location and orientation mainly depend upon the inertial reference that contains errors caused by gyro drifts and other error factors, traditional Strap-down Inertial Navigation System (SINS/CNS positioning algorithm setting the position error between SINS and CNS as measurement is not effective. The model of altitude azimuth, platform error angles, and horizontal position is designed, and the SINS/CNS tightly integrated algorithm is designed, in which CNS altitude azimuth is set as measurement information. GPF (Gaussian particle filter is introduced to solve the problem of nonlinear filtering. The results of simulation show that the precision of SINS/CNS algorithm which reaches 130 m using three stars is improved effectively.

Deep Kalman Filter: Simultaneous Multi-Sensor Integration and Modelling; A GNSS/IMU Case Study.

Science.gov (United States)

Hosseinyalamdary, Siavash

2018-04-24

Bayes filters, such as the Kalman and particle filters, have been used in sensor fusion to integrate two sources of information and obtain the best estimate of unknowns. The efficient integration of multiple sensors requires deep knowledge of their error sources. Some sensors, such as Inertial Measurement Unit (IMU), have complicated error sources. Therefore, IMU error modelling and the efficient integration of IMU and Global Navigation Satellite System (GNSS) observations has remained a challenge. In this paper, we developed deep Kalman filter to model and remove IMU errors and, consequently, improve the accuracy of IMU positioning. To achieve this, we added a modelling step to the prediction and update steps of the Kalman filter, so that the IMU error model is learned during integration. The results showed our deep Kalman filter outperformed the conventional Kalman filter and reached a higher level of accuracy.

Learning probabilistic features for robotic navigation using laser sensors.

Directory of Open Access Journals (Sweden)

Fidel Aznar

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

Learning probabilistic features for robotic navigation using laser sensors.

Science.gov (United States)

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

2014-01-01

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

Quad Rotorcraft Control Vision-Based Hovering and Navigation

CERN Document Server

García Carrillo, Luis Rodolfo; Lozano, Rogelio; Pégard, Claude

2013-01-01

Quad-Rotor Control develops original control methods for the navigation and hovering flight of an autonomous mini-quad-rotor robotic helicopter. These methods use an imaging system and a combination of inertial and altitude sensors to localize and guide the movement of the unmanned aerial vehicle relative to its immediate environment. The history, classification and applications of UAVs are introduced, followed by a description of modelling techniques for quad-rotors and the experimental platform itself. A control strategy for the improvement of attitude stabilization in quad-rotors is then proposed and tested in real-time experiments. The strategy, based on the use of low-cost components and with experimentally-established robustness, avoids drift in the UAV’s angular position by the addition of an internal control loop to each electronic speed controller ensuring that, during hovering flight, all four motors turn at almost the same speed. The quad-rotor’s Euler angles being very close to the origin, oth...

Autonomous GPS/INS navigation experiment for Space Transfer Vehicle (STV)

Science.gov (United States)

Upadhyay, Triveni N.; Cotterill, Stephen; Deaton, A. Wayne

1991-01-01

An experiment to validate the concept of developing an autonomous integrated spacecraft navigation system using on board Global Positioning System (GPS) and Inertial Navigation System (INS) measurements is described. The feasibility of integrating GPS measurements with INS measurements to provide a total improvement in spacecraft navigation performance, i.e. improvement in position, velocity and attitude information, was previously demonstrated. An important aspect of this research is the automatic real time reconfiguration capability of the system designed to respond to changes in a spacecraft mission under the control of an expert system.

Noise reduction and estimation in multiple micro-electro-mechanical inertial systems

International Nuclear Information System (INIS)

Waegli, Adrian; Skaloud, Jan; Guerrier, Stéphane; Parés, Maria Eulàlia; Colomina, Ismael

2010-01-01

This research studies the reduction and the estimation of the noise level within a redundant configuration of low-cost (MEMS-type) inertial measurement units (IMUs). Firstly, independent observations between units and sensors are assumed and the theoretical decrease in the system noise level is analyzed in an experiment with four MEMS-IMU triads. Then, more complex scenarios are presented in which the noise level can vary in time and for each sensor. A statistical method employed for studying the volatility of financial markets (GARCH) is adapted and tested for the usage with inertial data. This paper demonstrates experimentally and through simulations the benefit of direct noise estimation in redundant IMU setups

Activity Recognition Using Fusion of Low-Cost Sensors on a Smartphone for Mobile Navigation Application

Directory of Open Access Journals (Sweden)

Sara Saeedi

2015-08-01

Full Text Available Low-cost inertial and motion sensors embedded on smartphones have provided a new platform for dynamic activity pattern inference. In this research, a comparison has been conducted on different sensor data, feature spaces and feature selection methods to increase the efficiency and reduce the computation cost of activity recognition on the smartphones. We evaluated a variety of feature spaces and a number of classification algorithms from the area of Machine Learning, including Naive Bayes, Decision Trees, Artificial Neural Networks and Support Vector Machine classifiers. A smartphone app that performs activity recognition is being developed to collect data and send them to a server for activity recognition. Using extensive experiments, the performance of various feature spaces has been evaluated. The results showed that the Bayesian Network classifier yields recognition accuracy of 96.21% using four features while requiring fewer computations.

Absolute Navigation Information Estimation for Micro Planetary Rovers

Directory of Open Access Journals (Sweden)

Muhammad Ilyas

2016-03-01

Full Text Available This paper provides algorithms to estimate absolute navigation information, e.g., absolute attitude and position, by using low power, weight and volume Microelectromechanical Systems-type (MEMS sensors that are suitable for micro planetary rovers. Planetary rovers appear to be easily navigable robots due to their extreme slow speed and rotation but, unfortunately, the sensor suites available for terrestrial robots are not always available for planetary rover navigation. This makes them difficult to navigate in a completely unexplored, harsh and complex environment. Whereas the relative attitude and position can be tracked in a similar way as for ground robots, absolute navigation information, unlike in terrestrial applications, is difficult to obtain for a remote celestial body, such as Mars or the Moon. In this paper, an algorithm called the EASI algorithm (Estimation of Attitude using Sun sensor and Inclinometer is presented to estimate the absolute attitude using a MEMS-type sun sensor and inclinometer, only. Moreover, the output of the EASI algorithm is fused with MEMS gyros to produce more accurate and reliable attitude estimates. An absolute position estimation algorithm has also been presented based on these on-board sensors. Experimental results demonstrate the viability of the proposed algorithms and the sensor suite for low-cost and low-weight micro planetary rovers.

Improving Multisensor Positioning of Land Vehicles with Integrated Visual Odometry for Next-Generation Self-Driving Cars

Directory of Open Access Journals (Sweden)

Muhammed Tahsin Rahman

2018-01-01

Full Text Available For their complete realization, autonomous vehicles (AVs fundamentally rely on the Global Navigation Satellite System (GNSS to provide positioning and navigation information. However, in area such as urban cores, parking lots, and under dense foliage, which are all commonly frequented by AVs, GNSS signals suffer from blockage, interference, and multipath. These effects cause high levels of errors and long durations of service discontinuity that mar the performance of current systems. The prevalence of vision and low-cost inertial sensors provides an attractive opportunity to further increase the positioning and navigation accuracy in such GNSS-challenged environments. This paper presents enhancements to existing multisensor integration systems utilizing the inertial navigation system (INS to aid in Visual Odometry (VO outlier feature rejection. A scheme called Aided Visual Odometry (AVO is developed and integrated with a high performance mechanization architecture utilizing vehicle motion and orientation sensors. The resulting solution exhibits improved state covariance convergence and navigation accuracy, while reducing computational complexity. Experimental verification of the proposed solution is illustrated through three real road trajectories, over two different land vehicles, and using two low-cost inertial measurement units (IMUs.

Inertial Measurement Units-Based Probe Vehicles: Automatic Calibration, Trajectory Estimation, and Context Detection

KAUST Repository

Mousa, Mustafa

2017-12-06

Most probe vehicle data is generated using satellite navigation systems, such as the Global Positioning System (GPS), Globalnaya navigatsionnaya sputnikovaya Sistema (GLONASS), or Galileo systems. However, because of their high cost, relatively high position uncertainty in cities, and low sampling rate, a large quantity of satellite positioning data is required to estimate traffic conditions accurately. To address this issue, we introduce a new type of traffic monitoring system based on inexpensive inertial measurement units (IMUs) as probe sensors. IMUs as traffic probes pose unique challenges in that they need to be precisely calibrated, do not generate absolute position measurements, and their position estimates are subject to accumulating errors. In this paper, we address each of these challenges and demonstrate that the IMUs can reliably be used as traffic probes. After discussing the sensing technique, we present an implementation of this system using a custom-designed hardware platform, and validate the system with experimental data.

Inertial Measurement Units-Based Probe Vehicles: Automatic Calibration, Trajectory Estimation, and Context Detection

KAUST Repository

Mousa, Mustafa; Sharma, Kapil; Claudel, Christian G.

2017-01-01

Most probe vehicle data is generated using satellite navigation systems, such as the Global Positioning System (GPS), Globalnaya navigatsionnaya sputnikovaya Sistema (GLONASS), or Galileo systems. However, because of their high cost, relatively high position uncertainty in cities, and low sampling rate, a large quantity of satellite positioning data is required to estimate traffic conditions accurately. To address this issue, we introduce a new type of traffic monitoring system based on inexpensive inertial measurement units (IMUs) as probe sensors. IMUs as traffic probes pose unique challenges in that they need to be precisely calibrated, do not generate absolute position measurements, and their position estimates are subject to accumulating errors. In this paper, we address each of these challenges and demonstrate that the IMUs can reliably be used as traffic probes. After discussing the sensing technique, we present an implementation of this system using a custom-designed hardware platform, and validate the system with experimental data.

Rigorous Performance Evaluation of Smartphone GNSS/IMU Sensors for ITS Applications

Directory of Open Access Journals (Sweden)

Vassilis Gikas

2016-08-01

Full Text Available With the rapid growth in smartphone technologies and improvement in their navigation sensors, an increasing amount of location information is now available, opening the road to the provision of new Intelligent Transportation System (ITS services. Current smartphone devices embody miniaturized Global Navigation Satellite System (GNSS, Inertial Measurement Unit (IMU and other sensors capable of providing user position, velocity and attitude. However, it is hard to characterize their actual positioning and navigation performance capabilities due to the disparate sensor and software technologies adopted among manufacturers and the high influence of environmental conditions, and therefore, a unified certification process is missing. This paper presents the analysis results obtained from the assessment of two modern smartphones regarding their positioning accuracy (i.e., precision and trueness capabilities (i.e., potential and limitations based on a practical but rigorous methodological approach. Our investigation relies on the results of several vehicle tracking (i.e., cruising and maneuvering tests realized through comparing smartphone obtained trajectories and kinematic parameters to those derived using a high-end GNSS/IMU system and advanced filtering techniques. Performance testing is undertaken for the HTC One S (Android and iPhone 5s (iOS. Our findings indicate that the deviation of the smartphone locations from ground truth (trueness deteriorates by a factor of two in obscured environments compared to those derived in open sky conditions. Moreover, it appears that iPhone 5s produces relatively smaller and less dispersed error values compared to those computed for HTC One S. Also, the navigation solution of the HTC One S appears to adapt faster to changes in environmental conditions, suggesting a somewhat different data filtering approach for the iPhone 5s. Testing the accuracy of the accelerometer and gyroscope sensors for a number of

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

Science.gov (United States)

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.

NA-241_Quarterly Report_SBLibby - 12.31.2017_v2

Energy Technology Data Exchange (ETDEWEB)

Libby, Stephen B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Physics Dept.

2018-01-22

This is an evaluation of candidate navigation solutions for GPS free inspection tools that can be used in tours of large building interiors. In principle, COTS portable inertial motion unit (IMU) sensors with satisfactory accuracy, SWAP (size, weight, power), low error, and bias drift can provide sufficiently accurate dead reckoning navigation in a large building in the absence of GPS. To explore this assumption, the capabilities of representative IMU navigation sensors to meet these requirements will be evaluated, starting with a market survey, and then carrying out a basic analysis of these sensors using LLNL’s navigation codes.

Deep Kalman Filter: Simultaneous Multi-Sensor Integration and Modelling; A GNSS/IMU Case Study

Directory of Open Access Journals (Sweden)

Siavash Hosseinyalamdary

2018-04-01

Full Text Available Bayes filters, such as the Kalman and particle filters, have been used in sensor fusion to integrate two sources of information and obtain the best estimate of unknowns. The efficient integration of multiple sensors requires deep knowledge of their error sources. Some sensors, such as Inertial Measurement Unit (IMU, have complicated error sources. Therefore, IMU error modelling and the efficient integration of IMU and Global Navigation Satellite System (GNSS observations has remained a challenge. In this paper, we developed deep Kalman filter to model and remove IMU errors and, consequently, improve the accuracy of IMU positioning. To achieve this, we added a modelling step to the prediction and update steps of the Kalman filter, so that the IMU error model is learned during integration. The results showed our deep Kalman filter outperformed the conventional Kalman filter and reached a higher level of accuracy.

Indoor wayfinding and navigation

CERN Document Server

2015-01-01

Due to the widespread use of navigation systems for wayfinding and navigation in the outdoors, researchers have devoted their efforts in recent years to designing navigation systems that can be used indoors. This book is a comprehensive guide to designing and building indoor wayfinding and navigation systems. It covers all types of feasible sensors (for example, Wi-Fi, A-GPS), discussing the level of accuracy, the types of map data needed, the data sources, and the techniques for providing routes and directions within structures.

Investigation of Anticipatory Postural Adjustments during One-Leg Stance Using Inertial Sensors: Evidence from Subjects with Parkinsonism

Directory of Open Access Journals (Sweden)

Gianluca Bonora

2017-07-01

Full Text Available 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

SLS Model Based Design: A Navigation Perspective

Science.gov (United States)

Oliver, T. Emerson; Anzalone, Evan; Park, Thomas; Geohagan, Kevin

2018-01-01

The SLS Program has implemented a Model-based Design (MBD) and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team is responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1B design, the additional GPS Receiver hardware model is managed as a DMM at the vehicle design level. This paper describes the models, and discusses the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the navigation components.

Tracking 3D Moving Objects Based on GPS/IMU Navigation Solution, Laser Scanner Point Cloud and GIS Data

Directory of Open Access Journals (Sweden)

Siavash Hosseinyalamdary

2015-07-01

Full Text Available Monitoring vehicular road traffic is a key component of any autonomous driving platform. Detecting moving objects, and tracking them, is crucial to navigating around objects and predicting their locations and trajectories. Laser sensors provide an excellent observation of the area around vehicles, but the point cloud of objects may be noisy, occluded, and prone to different errors. Consequently, object tracking is an open problem, especially for low-quality point clouds. This paper describes a pipeline to integrate various sensor data and prior information, such as a Geospatial Information System (GIS map, to segment and track moving objects in a scene. We show that even a low-quality GIS map, such as OpenStreetMap (OSM, can improve the tracking accuracy, as well as decrease processing time. A bank of Kalman filters is used to track moving objects in a scene. In addition, we apply non-holonomic constraint to provide a better orientation estimation of moving objects. The results show that moving objects can be correctly detected, and accurately tracked, over time, based on modest quality Light Detection And Ranging (LiDAR data, a coarse GIS map, and a fairly accurate Global Positioning System (GPS and Inertial Measurement Unit (IMU navigation solution.

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

Science.gov (United States)

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.

Vision Based Autonomous Robot Navigation Algorithms and Implementations

CERN Document Server

Chatterjee, Amitava; Nirmal Singh, N

2013-01-01

This book is devoted to the theory and development of autonomous navigation of mobile robots using computer vision based sensing mechanism. The conventional robot navigation systems, utilizing traditional sensors like ultrasonic, IR, GPS, laser sensors etc., suffer several drawbacks related to either the physical limitations of the sensor or incur high cost. Vision sensing has emerged as a popular alternative where cameras can be used to reduce the overall cost, maintaining high degree of intelligence, flexibility and robustness. This book includes a detailed description of several new approaches for real life vision based autonomous navigation algorithms and SLAM. It presents the concept of how subgoal based goal-driven navigation can be carried out using vision sensing. The development concept of vision based robots for path/line tracking using fuzzy logic is presented, as well as how a low-cost robot can be indigenously developed in the laboratory with microcontroller based sensor systems. The book descri...

Surgical neuro navigator guided by preoperative magnetic resonance images, based on a magnetic position sensor

International Nuclear Information System (INIS)

Perini, Ana Paula; Siqueira, Rogerio Bulha; Carneiro, Antonio Adilton Oliveira; Oliveira, Lucas Ferrari de; Machado, Helio Rubens

2009-01-01

Image guided neurosurgery enables the neurosurgeon to navigate inside the patient's brain using pre-operative images as a guide and a tracking system, during a surgery. Following a calibration procedure, three-dimensional position and orientation of surgical instruments may be transmitted to computer. The spatial information is used to access a region of interest, in the pre-operative images, displaying them to the neurosurgeon during the surgical procedure. However, when a craniotomy is involved and the lesion is removed, movements of brain tissue can be a significant source of error in these conventional navigation systems. The architecture implemented in this work intends the development of a system to surgical planning and orientation guided by ultrasound image. For surgical orientation, the software developed allows the extraction of slices from the volume of the magnetic resonance images (MRI) with orientation supplied by a magnetic position sensor (Polhemus R ). The slices extracted with this software are important because they show the cerebral area that the neurosurgeon is observing during the surgery, and besides they can be correlated with the intra-operative ultrasound images to detect and to correct the deformation of brain tissue during the surgery. Also, a tool for per-operative navigation was developed, providing three orthogonal planes through the image volume. In the methodology used for the software implementation, the Python tm programming language and the Visualization Toolkit (VTK) graphics library were used. The program to extract slices of the MRI volume allowed the application of transformations in the volume, using coordinates supplied by the position sensor. (author)

In-flight thermal experiments for LISA Pathfinder: Simulating temperature noise at the Inertial Sensors

International Nuclear Information System (INIS)

Armano, M; Audley, H; Born, M; Danzmann, K; Diepholz, I; Auger, G; Binetruy, P; Baird, J; Bortoluzzi, D; Brandt, N; Fitzsimons, E; Bursi, A; Caleno, M; Cavalleri, A; Cesarini, A; Dolesi, R; Ferroni, V; Cruise, M; Dunbar, N; Ferraioli, L

2015-01-01

Thermal Diagnostics experiments to be carried out on board LISA Pathfinder (LPF) will yield a detailed characterisation of how temperature fluctuations affect the LTP (LISA Technology Package) instrument performance, a crucial information for future space based gravitational wave detectors as the proposed eLISA. Amongst them, the study of temperature gradient fluctuations around the test masses of the Inertial Sensors will provide as well information regarding the contribution of the Brownian noise, which is expected to limit the LTP sensitivity at frequencies close to 1 mHz during some LTP experiments. In this paper we report on how these kind of Thermal Diagnostics experiments were simulated in the last LPF Simulation Campaign (November, 2013) involving all the LPF Data Analysis team and using an end-to-end simulator of the whole spacecraft. Such simulation campaign was conducted under the framework of the preparation for LPF operations. (paper)

INCLINATION AND VIBRATION MEASUREMENT BY INERTIAL SENSING FOR STRUCTURAL HEALTH MONITORING

Science.gov (United States)

Sugisaki, Koichi; Abe, Masato; Koshimizu, Satoru

To develop a practical health monitoring system, inertial sensing which can readily be done for wide variety of situations is useful. However inertial sensors are measuring inclination and acceleration in reference to gravity. Therefore inclination are influence by acceleration and vice versa caused measuring errors. Especially, errors are more affected at low-frequency band which is important to estimate displacement. In this study, to establish correcting theory for inertial sensing and to develop method to estimate parameters for some structural system. And conducted a field test targeted at the real railway bridge to verify the effectiveness of the proposed method using response records of the pier under passing train load.

Pedestrian Dead Reckoning Navigation with the Help of A⁎-Based Routing Graphs in Large Unconstrained Spaces

Directory of Open Access Journals (Sweden)

F. Taia Alaoui

2017-01-01

Full Text Available An A⁎-based routing graph is proposed to assist PDR indoor and outdoor navigation with handheld devices. Measurements are provided by inertial and magnetic sensors together with a GNSS receiver. The novelty of this work lies in providing a realistic motion support that mitigates the absence of obstacles and enables the calibration of the PDR model even in large spaces where GNSS signal is unavailable. This motion support is exploited for both predicting positions and updating them using a particle filter. The navigation network is used to correct for the gyro drift, to adjust the step length model and to assess heading misalignment between the pedestrian’s walking direction and the pointing direction of the handheld device. Several datasets have been tested and results show that the proposed model ensures a seamless transition between outdoor and indoor environments and improves the positioning accuracy. The drift is almost cancelled thanks to heading correction in contrast with a drift of 8% for the nonaided PDR approach. The mean error of filtered positions ranges from 3 to 5 m.

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

Directory of Open Access Journals (Sweden)

Bingfei Fan

2017-05-01

Full Text Available 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.

An Enhanced Error Model for EKF-Based Tightly-Coupled Integration of GPS and Land Vehicle's Motion Sensors.

Science.gov (United States)

Karamat, Tashfeen B; Atia, Mohamed M; Noureldin, Aboelmagd

2015-09-22

Reduced inertial sensor systems (RISS) have been introduced by many researchers as a low-cost, low-complexity sensor assembly that can be integrated with GPS to provide a robust integrated navigation system for land vehicles. In earlier works, the developed error models were simplified based on the assumption that the vehicle is mostly moving on a flat horizontal plane. Another limitation is the simplified estimation of the horizontal tilt angles, which is based on simple averaging of the accelerometers' measurements without modelling their errors or tilt angle errors. In this paper, a new error model is developed for RISS that accounts for the effect of tilt angle errors and the accelerometer's errors. Additionally, it also includes important terms in the system dynamic error model, which were ignored during the linearization process in earlier works. An augmented extended Kalman filter (EKF) is designed to incorporate tilt angle errors and transversal accelerometer errors. The new error model and the augmented EKF design are developed in a tightly-coupled RISS/GPS integrated navigation system. The proposed system was tested on real trajectories' data under degraded GPS environments, and the results were compared to earlier works on RISS/GPS systems. The findings demonstrated that the proposed enhanced system introduced significant improvements in navigational performance.

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

Science.gov (United States)

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.

In-Field Validation of an Inertial Sensor-Based System for Movement Analysis and Classification in Ski Mountaineering

Directory of Open Access Journals (Sweden)

Jules Gellaerts

2018-03-01

Full Text Available Ski Mountaineering (SkiMo is a fast growing sport requiring both endurance and technical skills. It involves different types of locomotion with and without the skis. The aim of this study is to develop and validate in the snowfield a novel inertial-based system for analysing cycle parameters and classifying movement in SkiMo in real-time. The study was divided into two parts, one focused on real-time parameters estimation (cadence, distance from strides, stride duration, stride length, number of strides, slope gradient, and power and, second, on transition detection (kickturns, skin on, skin off, ski on and off backpack in order to classify between the different types of locomotion. Experimental protocol involved 16 experienced subjects who performed different SkiMo trials with their own equipment instrumented with a ski-mounted inertial sensor. The results obtained by the algorithm showed precise results with a relative error near 5% on all parameters. The developed system can, therefore, be used by skiers to obtain quantitative training data analysis and real-time feedback in the field. Nevertheless, a deeper validation of this algorithm might be necessary in order to confirm the accuracy on a wider population of subjects with various skill levels.

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

Science.gov (United States)

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.

Application of inertial measuring unit in air navigation for ALS and DAP

African Journals Online (AJOL)

This article describes the inertial measuring device IMU, as well as its use in airborne laser scanning and digital aerial photography. This device is used during the operation of a scanning unit and an aerial photo camera. The structure of an additional connection for a digital video camera is proposed, which will record video ...

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

An Enhanced Error Model for EKF-Based Tightly-Coupled Integration of GPS and Land Vehicle’s Motion Sensors

Science.gov (United States)

Karamat, Tashfeen B.; Atia, Mohamed M.; Noureldin, Aboelmagd

2015-01-01

Reduced inertial sensor systems (RISS) have been introduced by many researchers as a low-cost, low-complexity sensor assembly that can be integrated with GPS to provide a robust integrated navigation system for land vehicles. In earlier works, the developed error models were simplified based on the assumption that the vehicle is mostly moving on a flat horizontal plane. Another limitation is the simplified estimation of the horizontal tilt angles, which is based on simple averaging of the accelerometers’ measurements without modelling their errors or tilt angle errors. In this paper, a new error model is developed for RISS that accounts for the effect of tilt angle errors and the accelerometer’s errors. Additionally, it also includes important terms in the system dynamic error model, which were ignored during the linearization process in earlier works. An augmented extended Kalman filter (EKF) is designed to incorporate tilt angle errors and transversal accelerometer errors. The new error model and the augmented EKF design are developed in a tightly-coupled RISS/GPS integrated navigation system. The proposed system was tested on real trajectories’ data under degraded GPS environments, and the results were compared to earlier works on RISS/GPS systems. The findings demonstrated that the proposed enhanced system introduced significant improvements in navigational performance. PMID:26402680

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

Science.gov (United States)

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

Variable-State-Dimension Kalman-based Filter for orientation determination using inertial and magnetic sensors.

Science.gov (United States)

Sabatini, Angelo Maria

2012-01-01

In this paper a quaternion-based Variable-State-Dimension Extended Kalman Filter (VSD-EKF) is developed for estimating the three-dimensional orientation of a rigid body using the measurements from an Inertial Measurement Unit (IMU) integrated with a triaxial magnetic sensor. Gyro bias and magnetic disturbances are modeled and compensated by including them in the filter state vector. The VSD-EKF switches between a quiescent EKF, where the magnetic disturbance is modeled as a first-order Gauss-Markov stochastic process (GM-1), and a higher-order EKF where extra state components are introduced to model the time-rate of change of the magnetic field as a GM-1 stochastic process, namely the magnetic disturbance is modeled as a second-order Gauss-Markov stochastic process (GM-2). Experimental validation tests show the effectiveness of the VSD-EKF, as compared to either the quiescent EKF or the higher-order EKF when they run separately.

Variable-State-Dimension Kalman-Based Filter for Orientation Determination Using Inertial and Magnetic Sensors

Directory of Open Access Journals (Sweden)

Angelo Maria Sabatini

2012-06-01

Full Text Available In this paper a quaternion-based Variable-State-Dimension Extended Kalman Filter (VSD-EKF is developed for estimating the three-dimensional orientation of a rigid body using the measurements from an Inertial Measurement Unit (IMU integrated with a triaxial magnetic sensor. Gyro bias and magnetic disturbances are modeled and compensated by including them in the filter state vector. The VSD-EKF switches between a quiescent EKF, where the magnetic disturbance is modeled as a first-order Gauss-Markov stochastic process (GM-1, and a higher-order EKF where extra state components are introduced to model the time-rate of change of the magnetic field as a GM-1 stochastic process, namely the magnetic disturbance is modeled as a second-order Gauss-Markov stochastic process (GM-2. Experimental validation tests show the effectiveness of the VSD-EKF, as compared to either the quiescent EKF or the higher-order EKF when they run separately.

Compact autonomous navigation system (CANS)

Science.gov (United States)

Hao, Y. C.; Ying, L.; Xiong, K.; Cheng, H. Y.; Qiao, G. D.

2017-11-01

Autonomous navigation of Satellite and constellation has series of benefits, such as to reduce operation cost and ground station workload, to avoid the event of crises of war and natural disaster, to increase spacecraft autonomy, and so on. Autonomous navigation satellite is independent of ground station support. Many systems are developed for autonomous navigation of satellite in the past 20 years. Along them American MANS (Microcosm Autonomous Navigation System) [1] of Microcosm Inc. and ERADS [2] [3] (Earth Reference Attitude Determination System) of Honeywell Inc. are well known. The systems anticipate a series of good features of autonomous navigation and aim low cost, integrated structure, low power consumption and compact layout. The ERADS is an integrated small 3-axis attitude sensor system with low cost and small volume. It has the Earth center measurement accuracy higher than the common IR sensor because the detected ultraviolet radiation zone of the atmosphere has a brightness gradient larger than that of the IR zone. But the ERADS is still a complex system because it has to eliminate many problems such as making of the sapphire sphere lens, birefringence effect of sapphire, high precision image transfer optical fiber flattener, ultraviolet intensifier noise, and so on. The marginal sphere FOV of the sphere lens of the ERADS is used to star imaging that may be bring some disadvantages., i.e. , the image energy and attitude measurements accuracy may be reduced due to the tilt image acceptance end of the fiber flattener in the FOV. Besides Japan, Germany and Russia developed visible earth sensor for GEO [4] [5]. Do we have a way to develop a cheaper/easier and more accurate autonomous navigation system that can be used to all LEO spacecraft, especially, to LEO small and micro satellites? To return this problem we provide a new type of the system—CANS (Compact Autonomous Navigation System) [6].

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

Science.gov (United States)

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.

MicroASC instrument onboard Juno spacecraft utilizing inertially controlled imaging

DEFF Research Database (Denmark)

Pedersen, David Arge Klevang; Jørgensen, Andreas Härstedt; Benn, Mathias

2016-01-01

This contribution describes the post-processing of the raw image data acquired by the microASC instrument during the Earth-fly-by of the Juno spacecraft. The images show a unique view of the Earth and Moon system as seen from afar. The procedure utilizes attitude measurements and inter......-calibration of the Camera Head Units of the microASC system to trigger the image capturing. The triggering is synchronized with the inertial attitude and rotational phase of the sensor acquiring the images. This is essentially works as inertially controlled imaging facilitating image acquisition from unexplored...

3D gait assessment in young and elderly subjects using foot-worn inertial sensors

NARCIS (Netherlands)

Mariani, B.; Hoskovec, C.; Rochat, S.; Büla, C.; Penders, J.; Aminian, K.

2010-01-01

This study describes the validation of a new wearable system for assessment of 3D spatial parameters of gait. The new method is based on the detection of temporal parameters, coupled to optimized fusion and de-drifted integration of inertial signals. Composed of two wirelesses inertial modules

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

Directory of Open Access Journals (Sweden)

Valentina Camomilla

2018-03-01

Full Text Available 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.

Inertial sensors as measurement tools of elbow range of motion in gerontology

Directory of Open Access Journals (Sweden)

Sacco G

2015-02-01

Full Text Available G Sacco,1–3,* JM Turpin,3,4,* A Marteu,5 C Sakarovitch,6 B Teboul,2 L Boscher,4,5 P Brocker,4 P Robert,1–3 O Guerin2,3,7 1Memory Center, Claude Pompidou Institut, Department of Geriatrics, University Hospital of Nice, Nice, France; 2Centre d’Innovation et d’Usages en Santé (CIU-S, University Hospital of Nice, Cimiez Hospital, Nice, France; 3CoBTeK Cognition Behaviour Technology EA 7276, Research Center Edmond and Lily Safra, Nice Sophia-Antipolis University, Nice, France; 4Rehabilitation Unit, Department of Geriatrics, University Hospital of Nice, Cimiez Hospital, Nice, France; 5Rehabilitation Unit, Department of Neurosciences, University Hospital of Nice, L’Archet Hospital, Nice, France; 6Department of Clinical Research and Innovation, University Hospital of Nice, Cimiez Hospital, Nice, France; 7Acute Geriatrics Unit, Department of Geriatrics, University Hospital of Nice, Cimiez Hospital, Nice, France *These authors contributed equally to this work Background and purpose: Musculoskeletal system deterioration among the aging is a major reason for loss of autonomy and directly affects the quality of life of the elderly. Articular evaluation is part of physiotherapeutic assessment and helps in establishing a precise diagnosis and deciding appropriate therapy. Reference instruments are valid but not easy to use for some joints. The main goal of our study was to determine reliability and intertester reproducibility of the MP-BV, an inertial sensor (the MotionPod® [MP] combined with specific software (BioVal [BV], for elbow passive range-of-motion measurements in geriatrics. Methods: This open, monocentric, randomized study compared inertial sensor to inclinometer in patients hospitalized in an acute, post-acute, and long-term-care gerontology unit. Results: Seventy-seven patients (mean age 83.5±6.4 years, sex ratio 1.08 [male/female] were analyzed. The MP-BV was reliable for each of the three measurements (flexion, pronation, and

Inertial measurement unit–based iterative pose compensation algorithm for low-cost modular manipulator

Directory of Open Access Journals (Sweden)

Yunhan Lin

2016-01-01

Full Text Available It is a necessary mean to realize the accurate motion control of the manipulator which uses end-effector pose correction method and compensation method. In this article, first, we established the kinematic model and error model of the modular manipulator (WUST-ARM, and then we discussed the measurement methods and precision of the inertial measurement unit sensor. The inertial measurement unit sensor is mounted on the end-effector of modular manipulator, to get the real-time pose of the end-effector. At last, a new inertial measurement unit–based iterative pose compensation algorithm is proposed. By applying this algorithm in the pose compensation experiment of modular manipulator which is composed of low-cost rotation joints, the results show that the inertial measurement unit can obtain a higher precision when in static state; it will accurately feedback to the control system with an accurate error compensation angle after a brief delay when the end-effector moves to the target point, and after compensation, the precision errors of roll angle, pitch angle, and yaw angle are reached at 0.05°, 0.01°, and 0.27° respectively. It proves that this low-cost method provides a new solution to improve the end-effector pose of low-cost modular manipulator.

The Performance Analysis of a Real-Time Integrated INS/GPS Vehicle Navigation System with Abnormal GPS Measurement Elimination

Directory of Open Access Journals (Sweden)

Jhen-Kai Liao

2013-08-01

Full Text Available The integration of an Inertial Navigation System (INS and the Global Positioning System (GPS is common in mobile mapping and navigation applications to seamlessly determine the position, velocity, and orientation of the mobile platform. In most INS/GPS integrated architectures, the GPS is considered to be an accurate reference with which to correct for the systematic errors of the inertial sensors, which are composed of biases, scale factors and drift. However, the GPS receiver may produce abnormal pseudo-range errors mainly caused by ionospheric delay, tropospheric delay and the multipath effect. These errors degrade the overall position accuracy of an integrated system that uses conventional INS/GPS integration strategies such as loosely coupled (LC and tightly coupled (TC schemes. Conventional tightly coupled INS/GPS integration schemes apply the Klobuchar model and the Hopfield model to reduce pseudo-range delays caused by ionospheric delay and tropospheric delay, respectively, but do not address the multipath problem. However, the multipath effect (from reflected GPS signals affects the position error far more significantly in a consumer-grade GPS receiver than in an expensive, geodetic-grade GPS receiver. To avoid this problem, a new integrated INS/GPS architecture is proposed. The proposed method is described and applied in a real-time integrated system with two integration strategies, namely, loosely coupled and tightly coupled schemes, respectively. To verify the effectiveness of the proposed method, field tests with various scenarios are conducted and the results are compared with a reliable reference system.

Navigation integrity monitoring and obstacle detection for enhanced-vision systems

Science.gov (United States)

Korn, Bernd; Doehler, Hans-Ullrich; Hecker, Peter

2001-08-01

Typically, Enhanced Vision (EV) systems consist of two main parts, sensor vision and synthetic vision. Synthetic vision usually generates a virtual out-the-window view using databases and accurate navigation data, e. g. provided by differential GPS (DGPS). The reliability of the synthetic vision highly depends on both, the accuracy of the used database and the integrity of the navigation data. But especially in GPS based systems, the integrity of the navigation can't be guaranteed. Furthermore, only objects that are stored in the database can be displayed to the pilot. Consequently, unexpected obstacles are invisible and this might cause severe problems. Therefore, additional information has to be extracted from sensor data to overcome these problems. In particular, the sensor data analysis has to identify obstacles and has to monitor the integrity of databases and navigation. Furthermore, if a lack of integrity arises, navigation data, e.g. the relative position of runway and aircraft, has to be extracted directly from the sensor data. The main contribution of this paper is about the realization of these three sensor data analysis tasks within our EV system, which uses the HiVision 35 GHz MMW radar of EADS, Ulm as the primary EV sensor. For the integrity monitoring, objects extracted from radar images are registered with both database objects and objects (e. g. other aircrafts) transmitted via data link. This results in a classification into known and unknown radar image objects and consequently, in a validation of the integrity of database and navigation. Furthermore, special runway structures are searched for in the radar image where they should appear. The outcome of this runway check contributes to the integrity analysis, too. Concurrent to this investigation a radar image based navigation is performed without using neither precision navigation nor detailed database information to determine the aircraft's position relative to the runway. The performance of our

A new source difference artificial neural network for enhanced positioning accuracy

International Nuclear Information System (INIS)

Bhatt, Deepak; Aggarwal, Priyanka; Devabhaktuni, Vijay; Bhattacharya, Prabir

2012-01-01

Integrated inertial navigation system (INS) and global positioning system (GPS) units provide reliable navigation solution compared to standalone INS or GPS. Traditional Kalman filter-based INS/GPS integration schemes have several inadequacies related to sensor error model and immunity to noise. Alternatively, multi-layer perceptron (MLP) neural networks with three layers have been implemented to improve the position accuracy of the integrated system. However, MLP neural networks show poor accuracy for low-cost INS because of the large inherent sensor errors. For the first time the paper demonstrates the use of knowledge-based source difference artificial neural network (SDANN) to improve navigation performance of low-cost sensor, with or without external aiding sources. Unlike the conventional MLP or artificial neural networks (ANN), the structure of SDANN consists of two MLP neural networks called the coarse model and the difference model. The coarse model learns the input–output data relationship whereas the difference model adds knowledge to the system and fine-tunes the coarse model output by learning the associated training or estimation error. Our proposed SDANN model illustrated a significant improvement in navigation accuracy of up to 81% over conventional MLP. The results demonstrate that the proposed SDANN method is effective for GPS/INS integration schemes using low-cost inertial sensors, with and without GPS

DRIFT-FREE INDOOR NAVIGATION USING SIMULTANEOUS LOCALIZATION AND MAPPING OF THE AMBIENT HETEROGENEOUS MAGNETIC FIELD

Directory of Open Access Journals (Sweden)

J. C. K. Chow

2017-09-01

Full Text Available In the absence of external reference position information (e.g. surveyed targets or Global Navigation Satellite Systems Simultaneous Localization and Mapping (SLAM has proven to be an effective method for indoor navigation. The positioning drift can be reduced with regular loop-closures and global relaxation as the backend, thus achieving a good balance between exploration and exploitation. Although vision-based systems like laser scanners are typically deployed for SLAM, these sensors are heavy, energy inefficient, and expensive, making them unattractive for wearables or smartphone applications. However, the concept of SLAM can be extended to non-optical systems such as magnetometers. Instead of matching features such as walls and furniture using some variation of the Iterative Closest Point algorithm, the local magnetic field can be matched to provide loop-closure and global trajectory updates in a Gaussian Process (GP SLAM framework. With a MEMS-based inertial measurement unit providing a continuous trajectory, and the matching of locally distinct magnetic field maps, experimental results in this paper show that a drift-free navigation solution in an indoor environment with millimetre-level accuracy can be achieved. The GP-SLAM approach presented can be formulated as a maximum a posteriori estimation problem and it can naturally perform loop-detection, feature-to-feature distance minimization, global trajectory optimization, and magnetic field map estimation simultaneously. Spatially continuous features (i.e. smooth magnetic field signatures are used instead of discrete feature correspondences (e.g. point-to-point as in conventional vision-based SLAM. These position updates from the ambient magnetic field also provide enough information for calibrating the accelerometer bias and gyroscope bias in-use. The only restriction for this method is the need for magnetic disturbances (which is typically not an issue for indoor environments; however

Drift-Free Indoor Navigation Using Simultaneous Localization and Mapping of the Ambient Heterogeneous Magnetic Field

Science.gov (United States)

Chow, J. C. K.

2017-09-01

In the absence of external reference position information (e.g. surveyed targets or Global Navigation Satellite Systems) Simultaneous Localization and Mapping (SLAM) has proven to be an effective method for indoor navigation. The positioning drift can be reduced with regular loop-closures and global relaxation as the backend, thus achieving a good balance between exploration and exploitation. Although vision-based systems like laser scanners are typically deployed for SLAM, these sensors are heavy, energy inefficient, and expensive, making them unattractive for wearables or smartphone applications. However, the concept of SLAM can be extended to non-optical systems such as magnetometers. Instead of matching features such as walls and furniture using some variation of the Iterative Closest Point algorithm, the local magnetic field can be matched to provide loop-closure and global trajectory updates in a Gaussian Process (GP) SLAM framework. With a MEMS-based inertial measurement unit providing a continuous trajectory, and the matching of locally distinct magnetic field maps, experimental results in this paper show that a drift-free navigation solution in an indoor environment with millimetre-level accuracy can be achieved. The GP-SLAM approach presented can be formulated as a maximum a posteriori estimation problem and it can naturally perform loop-detection, feature-to-feature distance minimization, global trajectory optimization, and magnetic field map estimation simultaneously. Spatially continuous features (i.e. smooth magnetic field signatures) are used instead of discrete feature correspondences (e.g. point-to-point) as in conventional vision-based SLAM. These position updates from the ambient magnetic field also provide enough information for calibrating the accelerometer bias and gyroscope bias in-use. The only restriction for this method is the need for magnetic disturbances (which is typically not an issue for indoor environments); however, no assumptions

3D Reconfigurable MPSoC for Unmanned Spacecraft Navigation

Science.gov (United States)

Dekoulis, George

2016-07-01

This paper describes the design of a new lightweight spacecraft navigation system for unmanned space missions. The system addresses the demands for more efficient autonomous navigation in the near-Earth environment or deep space. The proposed instrumentation is directly suitable for unmanned systems operation and testing of new airborne prototypes for remote sensing applications. The system features a new sensor technology and significant improvements over existing solutions. Fluxgate type sensors have been traditionally used in unmanned defense systems such as target drones, guided missiles, rockets and satellites, however, the guidance sensors' configurations exhibit lower specifications than the presented solution. The current implementation is based on a recently developed material in a reengineered optimum sensor configuration for unprecedented low-power consumption. The new sensor's performance characteristics qualify it for spacecraft navigation applications. A major advantage of the system is the efficiency in redundancy reduction achieved in terms of both hardware and software requirements.

Evaluation of event-based algorithms for optical flow with ground-truth from inertial measurement sensor

Directory of Open Access Journals (Sweden)

Bodo eRückauer

2016-04-01

Full Text Available 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 240x180 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.

Improved artificial bee colony algorithm based gravity matching navigation method.

Science.gov (United States)

Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang

2014-07-18

Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position.

Doppler Navigation System with a Non-Stabilized Antenna as a Sea-Surface Wind Sensor.

Science.gov (United States)

Nekrasov, Alexey; Khachaturian, Alena; Veremyev, Vladimir; Bogachev, Mikhail

2017-06-09

We propose a concept of the utilization of an aircraft Doppler Navigation System (DNS) as a sea-surface wind sensor complementary to its normal functionality. The DNS with an antenna, which is non-stabilized physically to the local horizontal with x -configured beams, is considered. We consider the wind measurements by the DNS configured in the multi-beam scatterometer mode for a rectilinear flight scenario. The system feasibility and the efficiency of the proposed wind algorithm retrieval are supported by computer simulations. Finally, the associated limitations of the proposed approach are considered.

Field Programmable Gate Array Based Parallel Strapdown Algorithm Design for Strapdown Inertial Navigation Systems

Directory of Open Access Journals (Sweden)

Long-Hua Ma

2011-08-01

Full Text Available A new generalized optimum strapdown algorithm with coning and sculling compensation is presented, in which the position, velocity and attitude updating operations are carried out based on the single-speed structure in which all computations are executed at a single updating rate that is sufficiently high to accurately account for high frequency angular rate and acceleration rectification effects. Different from existing algorithms, the updating rates of the coning and sculling compensations are unrelated with the number of the gyro incremental angle samples and the number of the accelerometer incremental velocity samples. When the output sampling rate of inertial sensors remains constant, this algorithm allows increasing the updating rate of the coning and sculling compensation, yet with more numbers of gyro incremental angle and accelerometer incremental velocity in order to improve the accuracy of system. Then, in order to implement the new strapdown algorithm in a single FPGA chip, the parallelization of the algorithm is designed and its computational complexity is analyzed. The performance of the proposed parallel strapdown algorithm is tested on the Xilinx ISE 12.3 software platform and the FPGA device XC6VLX550T hardware platform on the basis of some fighter data. It is shown that this parallel strapdown algorithm on the FPGA platform can greatly decrease the execution time of algorithm to meet the real-time and high precision requirements of system on the high dynamic environment, relative to the existing implemented on the DSP platform.

Fast-light Enhanced Fiber Gyroscope, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Current state-of-the-art navigation systems incorporate optical gyroscopes and optical accelerometers as inertial sensors. These devices contain no moving parts and...

Mapping, Navigation, and Learning for Off-Road Traversal

DEFF Research Database (Denmark)

Konolige, Kurt; Agrawal, Motilal; Blas, Morten Rufus

2009-01-01

The challenge in the DARPA Learning Applied to Ground Robots (LAGR) project is to autonomously navigate a small robot using stereo vision as the main sensor. During this project, we demonstrated a complete autonomous system for off-road navigation in unstructured environments, using stereo vision......, online terrain traversability learning, visual odometry, map registration, planning, and control. At the end of 3 years, the system we developed outperformed all nine other teams in final blind tests over previously unseen terrain.......The challenge in the DARPA Learning Applied to Ground Robots (LAGR) project is to autonomously navigate a small robot using stereo vision as the main sensor. During this project, we demonstrated a complete autonomous system for off-road navigation in unstructured environments, using stereo vision...

A system to measure the kinematics during the entire ski jump sequence using inertial sensors.

Science.gov (United States)

Chardonnens, Julien; Favre, Julien; Cuendet, Florian; Gremion, Gérald; Aminian, Kamiar

2013-01-04

Three-dimensional analysis of the entire sequence in ski jumping is recommended when studying the kinematics or evaluating performance. Camera-based systems which allow three-dimensional kinematics measurement are complex to set-up and require extensive post-processing, usually limiting ski jumping analyses to small numbers of jumps. In this study, a simple method using a wearable inertial sensors-based system is described to measure the orientation of the lower-body segments (sacrum, thighs, shanks) and skis during the entire jump sequence. This new method combines the fusion of inertial signals and biomechanical constraints of ski jumping. Its performance was evaluated in terms of validity and sensitivity to different performances based on 22 athletes monitored during daily training. The validity of the method was assessed by comparing the inclination of the ski and the slope at landing point and reported an error of -0.2±4.8°. The validity was also assessed by comparison of characteristic angles obtained with the proposed system and reference values in the literature; the differences were smaller than 6° for 75% of the angles and smaller than 15° for 90% of the angles. The sensitivity to different performances was evaluated by comparing the angles between two groups of athletes with different jump lengths and by assessing the association between angles and jump lengths. The differences of technique observed between athletes and the associations with jumps length agreed with the literature. In conclusion, these results suggest that this system is a promising tool for a generalization of three-dimensional kinematics analysis in ski jumping. Copyright © 2012 Elsevier Ltd. All rights reserved.

The KCLBOT: Exploiting RGB-D Sensor Inputs for Navigation Environment Building and Mobile Robot Localization

Directory of Open Access Journals (Sweden)

Evangelos Georgiou

2011-09-01

Full Text Available This paper presents an alternative approach to implementing a stereo camera configuration for SLAM. The approach suggested implements a simplified method using a single RGB-D camera sensor mounted on a maneuverable non-holonomic mobile robot, the KCLBOT, used for extracting image feature depth information while maneuvering. Using a defined quadratic equation, based on the calibration of the camera, a depth computation model is derived base on the HSV color space map. Using this methodology it is possible to build navigation environment maps and carry out autonomous mobile robot path following and obstacle avoidance. This paper presents a calculation model which enables the distance estimation using the RGB-D sensor from Microsoft .NET micro framework device. Experimental results are presented to validate the distance estimation methodology.

A hybrid data fusion method for GNSS/INS integration navigation system

Science.gov (United States)

Yang, Ling; Li, Bofeng; Shen, Yunzhong; Li, Haojun

2017-04-01

Although DGNSS is widely used and PPP-GNSS is nowadays a viable precise positioning technology option, the major disadvantage of GNSS still remains: signal blockage due to obstructions in urban and built up environments, and extreme power attenuation of the signals when operated indoors. The combination of GNSS with other sensors, such as a self-contained inertial navigation system (INS), provides an ideal position and attitude determination solution which can not only mitigate the weakness of GNSS, but also bound the INS error that otherwise would grow with time when the INS operates alone. However, the navigation accuracy provided by GNSS/INS strongly depends on the quality and geometry of the GNSS observations, the quality of the INS technology used, and the integration model applied. There are two main types of coupled schemes for integration systems: loosely coupled integration and tightly coupled integration. In loosely coupled integration, position measurements are taken from both systems and combined optimally, usually in a Kalman filter. Tightly coupled integration directly combines the raw pseudorange or carrier phase measurements of GNSS with inertial measurements in an extended Kalman filter. The latter technique improves the ability to resolve ambiguities, i.e. allows a quicker recovery from outage events such as a loss of signal under vegetation. In recent years, tightly coupled differential carrier phase GNSS/INS integration has become popular, because it has the advantage of providing accurate position information even when GPS measurements are rank-deficient in stand-alone processing and is theoretically optimal in a filtering sense, especially in urban navigation applications. However, the heavier computational burden and sensor communication usually complicate the tightly coupled integration and reduce the system efficiency, compared with the loosely coupled integration. In this paper, it has been proved that the loosely coupled and tightly

Distributed Ship Navigation Control System Based on Dual Network

Science.gov (United States)

Yao, Ying; Lv, Wu

2017-10-01

Navigation system is very important for ship’s normal running. There are a lot of devices and sensors in the navigation system to guarantee ship’s regular work. In the past, these devices and sensors were usually connected via CAN bus for high performance and reliability. However, as the development of related devices and sensors, the navigation system also needs the ability of high information throughput and remote data sharing. To meet these new requirements, we propose the communication method based on dual network which contains CAN bus and industrial Ethernet. Also, we import multiple distributed control terminals with cooperative strategy based on the idea of synchronizing the status by multicasting UDP message contained operation timestamp to make the system more efficient and reliable.

Magnetic navigation and tracking of underwater vehicles

Digital Repository Service at National Institute of Oceanography (India)

Teixeira, F.C.; Pascoal, A.M.

for the navigation of AUVs has been proposed many years ago but the concept still requires practical demonstration. Implementation issues One of the advantages of mag- netic navigation consists in being passive and economical in terms of energy. Magnetic sensors do... like the present one, that require magnetic measurements with very high precision. A typical solution to this problem consists in the placement of magnetic sensors as far away as possible from the sources of noise but this may not be practical...

Inertial Motion Capture Costume Design Study

Directory of Open Access Journals (Sweden)

Agnieszka Szczęsna

2017-03-01

Full Text Available 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.

A New Polar Transfer Alignment Algorithm with the Aid of a Star Sensor and Based on an Adaptive Unscented Kalman Filter

Directory of Open Access Journals (Sweden)

Jianhua Cheng

2017-10-01

Full Text Available Because of the harsh polar environment, the master strapdown inertial navigation system (SINS has low accuracy and the system model information becomes abnormal. In this case, existing polar transfer alignment (TA algorithms which use the measurement information provided by master SINS would lose their effectiveness. In this paper, a new polar TA algorithm with the aid of a star sensor and based on an adaptive unscented Kalman filter (AUKF is proposed to deal with the problems. Since the measurement information provided by master SINS is inaccurate, the accurate information provided by the star sensor is chosen as the measurement. With the compensation of lever-arm effect and the model of star sensor, the nonlinear navigation equations are derived. Combined with the attitude matching method, the filter models for polar TA are designed. An AUKF is introduced to solve the abnormal information of system model. Then, the AUKF is used to estimate the states of TA. Results have demonstrated that the performance of the new polar TA algorithm is better than the state-of-the-art polar TA algorithms. Therefore, the new polar TA algorithm proposed in this paper is effectively to ensure and improve the accuracy of TA in the harsh polar environment.

A New Polar Transfer Alignment Algorithm with the Aid of a Star Sensor and Based on an Adaptive Unscented Kalman Filter.

Science.gov (United States)

Cheng, Jianhua; Wang, Tongda; Wang, Lu; Wang, Zhenmin

2017-10-23

Because of the harsh polar environment, the master strapdown inertial navigation system (SINS) has low accuracy and the system model information becomes abnormal. In this case, existing polar transfer alignment (TA) algorithms which use the measurement information provided by master SINS would lose their effectiveness. In this paper, a new polar TA algorithm with the aid of a star sensor and based on an adaptive unscented Kalman filter (AUKF) is proposed to deal with the problems. Since the measurement information provided by master SINS is inaccurate, the accurate information provided by the star sensor is chosen as the measurement. With the compensation of lever-arm effect and the model of star sensor, the nonlinear navigation equations are derived. Combined with the attitude matching method, the filter models for polar TA are designed. An AUKF is introduced to solve the abnormal information of system model. Then, the AUKF is used to estimate the states of TA. Results have demonstrated that the performance of the new polar TA algorithm is better than the state-of-the-art polar TA algorithms. Therefore, the new polar TA algorithm proposed in this paper is effectively to ensure and improve the accuracy of TA in the harsh polar environment.

Multi-Sensor Localization and Navigation for Remote Manipulation in Smoky Areas

Directory of Open Access Journals (Sweden)

Jose Vicente Marti

2013-04-01

Full Text Available When localizing mobile sensors and actuators in indoor environments laser meters, ultrasonic meters or even image processing techniques are usually used. On the other hand, in smoky conditions, due to a fire or building collapse, once the smoke or dust density grows, optical methods are not efficient anymore. In these scenarios other type of sensors must be used, such as sonar, radar or radiofrequency signals. Indoor localization in low-visibility conditions due to smoke is one of the EU GUARDIANS [1] project goals. The developed method aims to position a robot in front of doors, fire extinguishers and other points of interest with enough accuracy to allow a human operator to manipulate the robot's arm in order to actuate over the element. In coarse-grain localization, a fingerprinting technique based on ZigBee and WiFi signals is used, allowing the robot to navigate inside the building in order to get near the point of interest that requires manipulation. In fine-grained localization a remotely controlled programmable high intensity LED panel is used, which acts as a reference to the system in smoky conditions. Then, smoke detection and visual fine-grained localization are used to position the robot with precisely in the manipulation point (e.g., doors, valves, etc..

INERTIAL TECHNOLOGIES IN SYSTEMS FOR STABILIZATION OF GROUND VEHICLES EQUIPMENT

Directory of Open Access Journals (Sweden)

Olha Sushchenko

2016-12-01

Full Text Available Purpose: The vibratory inertial technology is a recent modern inertial technology. It represents the most perspective approach to design of inertial sensors, which can be used in stabilization and tracking systems operated on vehicles of the wide class. The purpose of the research is to consider advantages of this technology in comparison with laser and fiber-optic ones. Operation of the inertial sensors on the ground vehicles requires some improvement of the Coriolis vibratory gyroscope with the goal to simplify information processing, increase reliability, and compensate bias. Methods: Improvement of the Coriolis vibratory gyroscope includes introducing of the phase detector and additional excitation unit. The possibility to use the improved Coriolis vibratory gyroscope in the stabilization systems operated on the ground vehicles is shown by means of analysis of gyroscope output signal. To prove efficiency of the Coriolis vibratory gyroscope in stabilization system the simulation technique is used. Results: The scheme of the improved Coriolis vibratory gyroscope including the phase detector and additional excitation unit is developed and analyzed. The way to compensate bias is determined. Simulation of the stabilization system with the improved Coriolis vibratory gyroscope is carried out. Expressions for the output signals of the improved Coriolis vibratory gyroscope are derived. The error of the output signal is estimated and the possibility to use the modified Coriolis vibratory gyroscope in stabilization systems is proved. The results of stabilization system simulation are given. Their analysis is carried out. Conclusions: The represented results prove efficiency of the proposed technical decisions. They can be useful for design of stabilization platform with instrumental equipment operated on moving vehicles of the wide class.

Reliability of inertial sensors in the assessment of patients with vestibular disorders: a feasibility study

Directory of Open Access Journals (Sweden)

Sathish K. Sankarpandi

2017-02-01

Full Text Available Abstract Background Vestibular disorders affect an individual’s stability, balance, and gait and predispose them to falls. Traditional laboratory-based semi-objective vestibular assessments are intrusive and cumbersome provide little information about their functional ability. Commercially available wearable inertial sensors allow us to make this real life assessments objective, with a detailed view of their functional abilities. Timed Up and Go (TUG and Postural Sway tests are commonly used tests for gait and balance assessments. Our aim was to assess the feasibility, test-retest reliability and ability to classify fall status in individuals with vestibular disorders using parameters derived from the commercially available wearable system (inertial sensors and the Mobility Lab Software, APDM, Inc.. Methods We recruited 27 individuals diagnosed either with unilateral or bilateral vestibular loss on vestibular function testing. Instrumented Timed Up and Go (iTUG and Postural Sway (iSway were administered three times during the first session and then repeated at a similar time the following week. To evaluate within and between sessions reliability of the parameters the Intra-Class Correlation coefficient (ICC was used. Subsequently, the ability of reliable parameters (ICC ≥ 0.8 to classify fallers from non-fallers was estimated. Results The iTUG test parameters showed good within and between sessions’ reliability with mean ICC (between-sessions values of 0.81 ± 0.17 and 0.69 ± 0.15, respectively. For the iSway test, the relative figures were; 0.76 ± 0.13 and 0.71 ± 0.14, respectively. A retrospective falls classification analysis with past 12 months falls history data yielded an accuracy of 66.70% with an area under the curve of 0.79. Mean Distance from centre of COP (mm of accelerometer’s trajectory (m/s2 from the iSway test was the only significant parameter to classify fallers from non-fallers. Conclusions Using

Acoustic Communications and Navigation for Mobile Under-Ice Sensors

Science.gov (United States)

2017-02-04

contact below the ice. 15. SUBJECT TERMS Arctic Ocean , Undersea Workstations & Vehicles, Signal Processing, Navigation , Underwater Acoustics 16...Partan, Peter Koski, and Sandipa Singh, "Long Range Acoustic Communications and Navigation in the Arctic", Proc. IEEE/MTS Oceans Conf., Washington, DC...Oct. 2015. Freitag, L., P. Koski, A. Morozov, S. Singh, J. Partan, "Acoustic Communications and Navigation Under Arctic Ice", OCEANS , 2012

INS/GPS/LiDAR Integrated Navigation System for Urban and Indoor Environments Using Hybrid Scan Matching Algorithm.

Science.gov (United States)

Gao, Yanbin; Liu, Shifei; Atia, Mohamed M; Noureldin, Aboelmagd

2015-09-15

This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory.

A compact, large-range interferometer for precision measurement and inertial sensing

Science.gov (United States)

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.

Tele-auscultation support system with mixed reality navigation.

Science.gov (United States)

Hori, Kenta; Uchida, Yusuke; Kan, Tsukasa; Minami, Maya; Naito, Chisako; Kuroda, Tomohiro; Takahashi, Hideya; Ando, Masahiko; Kawamura, Takashi; Kume, Naoto; Okamoto, Kazuya; Takemura, Tadamasa; Yoshihara, Hiroyuki

2013-01-01

The aim of this research is to develop an information support system for tele-auscultation. In auscultation, a doctor requires to understand condition of applying a stethoscope, in addition to auscultatory sounds. The proposed system includes intuitive navigation system of stethoscope operation, in addition to conventional audio streaming system of auscultatory sounds and conventional video conferencing system for telecommunication. Mixed reality technology is applied for intuitive navigation of the stethoscope. Information, such as position, contact condition and breath, is overlaid on a view of the patient's chest. The contact condition of the stethoscope is measured by e-textile contact sensors. The breath is measured by a band type breath sensor. In a simulated tele-auscultation experiment, the stethoscope with the contact sensors and the breath sensor were evaluated. The results show that the presentation of the contact condition was not understandable enough for navigating the stethoscope handling. The time series of the breath phases was usable for the remote doctor to understand the breath condition of the patient.

Intelligent Behavioral Action Aiding for Improved Autonomous Image Navigation

Science.gov (United States)

2012-09-13

odometry, SICK laser scanning unit ( Lidar ), Inertial Measurement Unit (IMU) and ultrasonic distance measurement system (Figure 32). The Lidar , IMU...2010, July) GPS world. [Online]. http://www.gpsworld.com/tech-talk- blog/gnss-independent-navigation-solution-using-integrated- lidar -data-11378 [4...Milford, David McKinnon, Michael Warren, Gordon Wyeth, and Ben Upcroft, "Feature-based Visual Odometry and Featureless Place Recognition for SLAM in

Improving inertial Pedestrian Dead-Reckoning by detecting unmodified switched-on lamps in buildings.

Science.gov (United States)

Jiménez, Antonio R; Zampella, Francisco; Seco, Fernando

2014-01-03

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.

Improving Inertial Pedestrian Dead-Reckoning by Detecting Unmodified Switched-on Lamps in Buildings

Directory of Open Access Journals (Sweden)

Antonio R. Jiménez

2014-01-01

Full Text Available 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.

Precision Landing and Hazard Avoidance Doman

Science.gov (United States)

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.

High-accuracy self-calibration method for dual-axis rotation-modulating RLG-INS

Science.gov (United States)

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

2017-05-01

Inertial navigation system has been the core component of both military and civil navigation systems. Dual-axis rotation modulation can completely eliminate the inertial elements constant errors of the three axes to improve the system accuracy. But the error caused by the misalignment angles and the scale factor error cannot be eliminated through dual-axis rotation modulation. And discrete calibration method cannot fulfill requirements of high-accurate calibration of the mechanically dithered ring laser gyroscope navigation system with shock absorbers. This paper has analyzed the effect of calibration error during one modulated period and presented a new systematic self-calibration method for dual-axis rotation-modulating RLG-INS. Procedure for self-calibration of dual-axis rotation-modulating RLG-INS has been designed. The results of self-calibration simulation experiment proved that: this scheme can estimate all the errors in the calibration error model, the calibration precision of the inertial sensors scale factor error is less than 1ppm and the misalignment is less than 5″. These results have validated the systematic self-calibration method and proved its importance for accuracy improvement of dual -axis rotation inertial navigation system with mechanically dithered ring laser gyroscope.

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

Science.gov (United States)

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

Star pattern recognition algorithm aided by inertial information

Science.gov (United States)

Liu, Bao; Wang, Ke-dong; Zhang, Chao

2011-08-01

Star pattern recognition is one of the key problems of the celestial navigation. The traditional star pattern recognition approaches, such as the triangle algorithm and the star angular distance algorithm, are a kind of all-sky matching method whose recognition speed is slow and recognition success rate is not high. Therefore, the real time and reliability of CNS (Celestial Navigation System) is reduced to some extent, especially for the maneuvering spacecraft. However, if the direction of the camera optical axis can be estimated by other navigation systems such as INS (Inertial Navigation System), the star pattern recognition can be fulfilled in the vicinity of the estimated direction of the optical axis. The benefits of the INS-aided star pattern recognition algorithm include at least the improved matching speed and the improved success rate. In this paper, the direction of the camera optical axis, the local matching sky, and the projection of stars on the image plane are estimated by the aiding of INS firstly. Then, the local star catalog for the star pattern recognition is established in real time dynamically. The star images extracted in the camera plane are matched in the local sky. Compared to the traditional all-sky star pattern recognition algorithms, the memory of storing the star catalog is reduced significantly. Finally, the INS-aided star pattern recognition algorithm is validated by simulations. The results of simulations show that the algorithm's computation time is reduced sharply and its matching success rate is improved greatly.

77 FR 9899 - 36(b)(1) Arms Sales Notification

Science.gov (United States)

2012-02-21

... support, and other related elements of program support. (iv) Military Department: Air Force (SAC, Amd 12...) variant that includes a DSU-40 Laser Sensor. The GBU-54 uses global position system aided inertial navigation and/or laser detection to guide to threat targets. The Laser sensor enhances the standard JDAM's...

Periodic leg movement (PLM) monitoring using a distributed body sensor network.

Science.gov (United States)

Madhushri, Priyanka; Ahmed, Beena; Penzel, Thomas; Jovanov, Emil

2015-01-01

Wireless sensors networks represent the architecture of choice for distributed monitoring due to the ease of deployment and configuration. We developed a distributed sleep monitoring system which combines wireless inertial sensors SP-10C by Sensoplex controlled by a custom smartphone application as an extension of the polysomnographic (PSG) monitor SOMNOscreen plus from Somnomedics. While existing activity monitors are wired to the SOMNOscreen, our system allows the use of wireless inertial sensors to improve user's comfort during sleep. The system is intended for monitoring of periodic leg movements (PLM) and user's activity during sleep. Wireless sensors are placed on ankle and toes of the foot in a customized sock. An Android app communicates with wireless sensors over Bluetooth Smart (BTS) link and streams 3D accelerometer values, 4D unit quaternion values and timestamps. In this paper we present a novel method of synchronization of data streams from PSG and inertial sensors, and original method of detection of PLM events. The system was tested using five experiments of simulated PLM, and achieved 96.51% of PLM detection accuracy.

Learning for Autonomous Navigation

Science.gov (United States)

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

2005-01-01

Robotic ground vehicles for outdoor applications have achieved some remarkable successes, notably in autonomous highway following (Dickmanns, 1987), planetary exploration (1), and off-road navigation on Earth (1). Nevertheless, major challenges remain to enable reliable, high-speed, autonomous navigation in a wide variety of complex, off-road terrain. 3-D perception of terrain geometry with imaging range sensors is the mainstay of off-road driving systems. However, the stopping distance at high speed exceeds the effective lookahead distance of existing range sensors. Prospects for extending the range of 3-D sensors is strongly limited by sensor physics, eye safety of lasers, and related issues. Range sensor limitations also allow vehicles to enter large cul-de-sacs even at low speed, leading to long detours. Moreover, sensing only terrain geometry fails to reveal mechanical properties of terrain that are critical to assessing its traversability, such as potential for slippage, sinkage, and the degree of compliance of potential obstacles. Rovers in the Mars Exploration Rover (MER) mission have got stuck in sand dunes and experienced significant downhill slippage in the vicinity of large rock hazards. Earth-based off-road robots today have very limited ability to discriminate traversable vegetation from non-traversable vegetation or rough ground. It is impossible today to preprogram a system with knowledge of these properties for all types of terrain and weather conditions that might be encountered.

Integrated Navigation System Design for Micro Planetary Rovers: Comparison of Absolute Heading Estimation Algorithms and Nonlinear Filtering

Science.gov (United States)

Ilyas, Muhammad; Hong, Beomjin; Cho, Kuk; Baeg, Seung-Ho; Park, Sangdeok

2016-01-01

This paper provides algorithms to fuse relative and absolute microelectromechanical systems (MEMS) navigation sensors, suitable for micro planetary rovers, to provide a more accurate estimation of navigation information, specifically, attitude and position. Planetary rovers have extremely slow speed (~1 cm/s) and lack conventional navigation sensors/systems, hence the general methods of terrestrial navigation may not be applicable to these applications. While relative attitude and position can be tracked in a way similar to those for ground robots, absolute navigation information is hard to achieve on a remote celestial body, like Moon or Mars, in contrast to terrestrial applications. In this study, two absolute attitude estimation algorithms were developed and compared for accuracy and robustness. The estimated absolute attitude was fused with the relative attitude sensors in a framework of nonlinear filters. The nonlinear Extended Kalman filter (EKF) and Unscented Kalman filter (UKF) were compared in pursuit of better accuracy and reliability in this nonlinear estimation problem, using only on-board low cost MEMS sensors. Experimental results confirmed the viability of the proposed algorithms and the sensor suite, for low cost and low weight micro planetary rovers. It is demonstrated that integrating the relative and absolute navigation MEMS sensors reduces the navigation errors to the desired level. PMID:27223293

High precision estimation of inertial rotation via the extended Kalman filter

Science.gov (United States)

Liu, Lijun; Qi, Bo; Cheng, Shuming; Xi, Zairong

2015-11-01

Recent developments in technology have enabled atomic gyroscopes to become the most sensitive inertial sensors. Atomic spin gyroscopes essentially output an estimate of the inertial rotation rate to be measured. In this paper, we present a simple yet efficient estimation method, the extended Kalman filter (EKF), for the atomic spin gyroscope. Numerical results show that the EKF method is much more accurate than the steady-state estimation method, which is used in the most sensitive atomic gyroscopes at present. Specifically, the root-mean-squared errors obtained by the EKF method are at least 103 times smaller than those obtained by the steady-state estimation method under the same response time.

Loose Coupling of Wearable-Based INSs with Automatic Heading Evaluation

OpenAIRE

Bousdar Ahmed, Dina; 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...

SGA-WZ: A New Strapdown Airborne Gravimeter

DEFF Research Database (Denmark)

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

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...... and discussion of the airborne field test results are also given....

Concept of AHRS Algorithm Designed for Platform Independent Imu Attitude Alignment

Science.gov (United States)

Tomaszewski, Dariusz; Rapiński, Jacek; Pelc-Mieczkowska, Renata

2017-12-01

Nowadays, along with the advancement of technology one can notice the rapid development of various types of navigation systems. So far the most popular satellite navigation, is now supported by positioning results calculated with use of other measurement system. The method and manner of integration will depend directly on the destination of system being developed. To increase the frequency of readings and improve the operation of outdoor navigation systems, one will support satellite navigation systems (GPS, GLONASS ect.) with inertial navigation. Such method of navigation consists of several steps. The first stage is the determination of initial orientation of inertial measurement unit, called INS alignment. During this process, on the basis of acceleration and the angular velocity readings, values of Euler angles (pitch, roll, yaw) are calculated allowing for unambiguous orientation of the sensor coordinate system relative to external coordinate system. The following study presents the concept of AHRS (Attitude and heading reference system) algorithm, allowing to define the Euler angles.The study were conducted with the use of readings from low-cost MEMS cell phone sensors. Subsequently the results of the study were analyzed to determine the accuracy of featured algorithm. On the basis of performed experiments the legitimacy of developed algorithm was stated.

Activity Recognition Using Inertial Sensing for Healthcare, Wellbeing and Sports Applications: A Survey

NARCIS (Netherlands)

Avci, A.; Bosch, S.; Marin Perianu, Mihai; Marin Perianu, Raluca; Havinga, Paul J.M.

This paper surveys the current research directions of activity recognition using inertial sensors, with potential application in healthcare, wellbeing and sports. The analysis of related work is organized according to the five main steps involved in the activity recognition process: preprocessing,

Wearable sensor system for human localization and motion capture

OpenAIRE

Zihajehzadeh, Shaghayegh

2017-01-01

Recent advances in MEMS wearable inertial/magnetic sensors and mobile computing have fostered a dramatic growth of interest for ambulatory human motion capture (MoCap). Compared to traditional optical MoCap systems such as the optical systems, inertial (i.e. accelerometer and gyroscope) and magnetic sensors do not require external fixtures such as cameras. Hence, they do not have in-the-lab measurement limitations and thus are ideal for ambulatory applications. However, due to the manufacturi...

Exploration and Navigation for Mobile Robots With Perceptual Limitations

Directory of Open Access Journals (Sweden)

Leonardo Romero

2006-09-01

Full Text Available To learn a map of an environment a mobile robot has to explore its workspace using its sensors. Sensors are noisy and have perceptual limitations that must be considered while learning a map. This paper considers a mobile robot with sensor perceptual limitations and introduces a new method for exploring and navigating autonomously in indoor environments. To minimize the risk of collisions as well as to not exceed the range of sensors, we introduce the concept of a travel space as a way to associate costs to grid cells of the map, based on distances to obstacles. During exploration the mobile robot minimizes its movements, including rotations, to reach the nearest unexplored region of the environment, using a dynamic programming algorithm. Once the exploration ends, the travel space is used to form a roadmap, a net of safe roads that the mobile robot can use for navigation. These exploration and navigation method are tested using a simulated and a real mobile robot with promising results.

Exploration and Navigation for Mobile Robots With Perceptual Limitations

Directory of Open Access Journals (Sweden)

Eduardo F. Morales

2008-11-01

Full Text Available To learn a map of an environment a mobile robot has to explore its workspace using its sensors. Sensors are noisy and have perceptual limitations that must be considered while learning a map. This paper considers a mobile robot with sensor perceptual limitations and introduces a new method for exploring and navigating autonomously in indoor environments. To minimize the risk of collisions as well as to not exceed the range of sensors, we introduce the concept of a travel space as a way to associate costs to grid cells of the map, based on distances to obstacles. During exploration the mobile robot minimizes its movements, including rotations, to reach the nearest unexplored region of the environment, using a dynamic programming algorithm. Once the exploration ends, the travel space is used to form a roadmap, a net of safe roads that the mobile robot can use for navigation. These exploration and navigation method are tested using a simulated and a real mobile robot with promising results.

Development of a facility using robotics for testing automation of inertial instruments

Science.gov (United States)

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.

Vision Based Navigation for Autonomous Cooperative Docking of CubeSats

Science.gov (United States)

Pirat, Camille; Ankersen, Finn; Walker, Roger; Gass, Volker

2018-05-01

A realistic rendezvous and docking navigation solution applicable to CubeSats is investigated. The scalability analysis of the ESA Autonomous Transfer Vehicle Guidance, Navigation & Control (GNC) performances and the Russian docking system, shows that the docking of two CubeSats would require a lateral control performance of the order of 1 cm. Line of sight constraints and multipath effects affecting Global Navigation Satellite System (GNSS) measurements in close proximity prevent the use of this sensor for the final approach. This consideration and the high control accuracy requirement led to the use of vision sensors for the final 10 m of the rendezvous and docking sequence. A single monocular camera on the chaser satellite and various sets of Light-Emitting Diodes (LEDs) on the target vehicle ensure the observability of the system throughout the approach trajectory. The simple and novel formulation of the measurement equations allows differentiating unambiguously rotations from translations between the target and chaser docking port and allows a navigation performance better than 1 mm at docking. Furthermore, the non-linear measurement equations can be solved in order to provide an analytic navigation solution. This solution can be used to monitor the navigation filter solution and ensure its stability, adding an extra layer of robustness for autonomous rendezvous and docking. The navigation filter initialization is addressed in detail. The proposed method is able to differentiate LEDs signals from Sun reflections as demonstrated by experimental data. The navigation filter uses a comprehensive linearised coupled rotation/translation dynamics, describing the chaser to target docking port motion. The handover, between GNSS and vision sensor measurements, is assessed. The performances of the navigation function along the approach trajectory is discussed.

A Multiple-Model Particle Filter Fusion Algorithm for GNSS/DR Slide Error Detection and Compensation

Directory of Open Access Journals (Sweden)

Rafael Toledo-Moreo

2018-03-01

Full Text Available Continuous accurate positioning is a key element for the deployment of many advanced driver assistance systems (ADAS and autonomous vehicle navigation. To achieve the necessary performance, global navigation satellite systems (GNSS must be combined with other technologies. A common onboard sensor-set that allows keeping the cost low, features the GNSS unit, odometry, and inertial sensors, such as a gyro. Odometry and inertial sensors compensate for GNSS flaws in many situations and, in normal conditions, their errors can be easily characterized, thus making the whole solution not only more accurate but also with more integrity. However, odometers do not behave properly when friction conditions make the tires slide. If not properly considered, the positioning perception will not be sound. This article introduces a hybridization approach that takes into consideration the sliding situations by means of a multiple model particle filter (MMPF. Tests with real datasets show the goodness of the proposal.

Quantification of Hand Motor Symptoms in Parkinson's Disease: A Proof-of-Principle Study Using Inertial and Force Sensors.

Science.gov (United States)

van den Noort, Josien C; Verhagen, Rens; van Dijk, Kees J; Veltink, Peter H; Vos, Michelle C P M; de Bie, Rob M A; Bour, Lo J; Heida, Ciska T

2017-10-01

This proof-of-principle study describes the methodology and explores and demonstrates the applicability of a system, existing of miniature inertial sensors on the hand and a separate force sensor, to objectively quantify hand motor symptoms in patients with Parkinson's disease (PD) in a clinical setting (off- and on-medication condition). Four PD patients were measured in off- and on- dopaminergic medication condition. Finger tapping, rapid hand opening/closing, hand pro/supination, tremor during rest, mental task and kinetic task, and wrist rigidity movements were measured with the system (called the PowerGlove). To demonstrate applicability, various outcome parameters of measured hand motor symptoms of the patients in off- vs. on-medication condition are presented. The methodology described and results presented show applicability of the PowerGlove in a clinical research setting, to objectively quantify hand bradykinesia, tremor and rigidity in PD patients, using a single system. The PowerGlove measured a difference in off- vs. on-medication condition in all tasks in the presented patients with most of its outcome parameters. Further study into the validity and reliability of the outcome parameters is required in a larger cohort of patients, to arrive at an optimal set of parameters that can assist in clinical evaluation and decision-making.

Integrating GPS, GYRO, vehicle speed sensor, and digital map to provide accurate and real-time position in an intelligent navigation system

Science.gov (United States)

Li, Qingquan; Fang, Zhixiang; Li, Hanwu; Xiao, Hui

2005-10-01

The global positioning system (GPS) has become the most extensively used positioning and navigation tool in the world. Applications of GPS abound in surveying, mapping, transportation, agriculture, military planning, GIS, and the geosciences. However, the positional and elevation accuracy of any given GPS location is prone to error, due to a number of factors. The applications of Global Positioning System (GPS) positioning is more and more popular, especially the intelligent navigation system which relies on GPS and Dead Reckoning technology is developing quickly for future huge market in China. In this paper a practical combined positioning model of GPS/DR/MM is put forward, which integrates GPS, Gyro, Vehicle Speed Sensor (VSS) and digital navigation maps to provide accurate and real-time position for intelligent navigation system. This model is designed for automotive navigation system making use of Kalman filter to improve position and map matching veracity by means of filtering raw GPS and DR signals, and then map-matching technology is used to provide map coordinates for map displaying. In practical examples, for illustrating the validity of the model, several experiments and their results of integrated GPS/DR positioning in intelligent navigation system will be shown for the conclusion that Kalman Filter based GPS/DR integrating position approach is necessary, feasible and efficient for intelligent navigation application. Certainly, this combined positioning model, similar to other model, can not resolve all situation issues. Finally, some suggestions are given for further improving integrated GPS/DR/MM application.

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

Science.gov (United States)

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.

Map matching and heuristic elimination of gyro drift for personal navigation systems in GPS-denied conditions

International Nuclear Information System (INIS)

Aggarwal, Priyanka; Thomas, David; Ojeda, Lauro; Borenstein, Johann

2011-01-01

This paper introduces a method for the substantial reduction of heading errors in inertial navigation systems used under GPS-denied conditions. Presumably, the method is applicable for both vehicle-based and personal navigation systems, but experiments were performed only with a personal navigation system called 'personal dead reckoning' (PDR). In order to work under GPS-denied conditions, the PDR system uses a foot-mounted inertial measurement unit (IMU). However, gyro drift in this IMU can cause large heading errors after just a few minutes of walking. To reduce these errors, the map-matched heuristic drift elimination (MAPHDE) method was developed, which estimates gyro drift errors by comparing IMU-derived heading to the direction of the nearest street segment in a database of street maps. A heuristic component in this method provides tolerance to short deviations from walking along the street, such as when crossing streets or intersections. MAPHDE keeps heading errors almost at zero, and, as a result, position errors are dramatically reduced. In this paper, MAPHDE was used in a variety of outdoor walks, without any use of GPS. This paper explains the MAPHDE method in detail and presents experimental results

Lunar Navigator - A Miniature, Fully Autonomous, Lunar Navigation, Surveyor, and Range Finder System, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — Microcosm will use existing hardware and software from related programs to create a prototype Lunar Navigation Sensor (LNS) early in Phase II, such that most of the...

Influence of the whispering-gallery mode resonators shape on its inertial movement sensitivity

Science.gov (United States)

Filatov, Yuri V.; Kukaev, Alexander S.; Shalymov, Egor V.; Venediktov, Vladimir Yu.

2018-01-01

The optical whispering-gallery mode (WGM) resonators are axially symmetrical resonators with smooth edges, supporting the existence of the WGMs by the total internal reflection on the surface of the resonator. As of today, various types of such resonators have been developed, namely the ball shaped, tor shaped, bottle shaped, disk shaped, etc. The movement of WGM resonators in inertial space causes the changes in their shape. The result is a spectral shift of the WGMs. Optical methods allow to register this shift with high precision. It can be used in particular for the measurement of angular velocities in inertial orientation and navigation systems. However, different types of resonators react to the movement in different manners. In addition, their sensitivity to movement can be changed when changing the geometric parameters of these resonators. The work is devoted to investigation of these aspects.

Hybrid Transverse Polar Navigation for High-Precision and Long-Term INSs.

Science.gov (United States)

Wu, Ruonan; Wu, Qiuping; Han, Fengtian; Zhang, Rong; Hu, Peida; Li, Haixia

2018-05-12

Transverse navigation has been proposed to help inertial navigation systems (INSs) fill the gap of polar navigation ability. However, as the transverse system does not have the ability of navigate globally, a complicated switch between the transverse and the traditional algorithms is necessary when the system moves across the polar circles. To maintain the inner continuity and consistency of the core algorithm, a hybrid transverse polar navigation is proposed in this research based on a combination of Earth-fixed-frame mechanization and transverse-frame outputs. Furthermore, a thorough analysis of kinematic error characteristics, proper damping technology and corresponding long-term contributions of main error sources is conducted for the high-precision INSs. According to the analytical expressions of the long-term navigation errors in polar areas, the 24-h period symmetrical oscillation with a slowly divergent amplitude dominates the transverse horizontal position errors, and the first-order drift dominates the transverse azimuth error, which results from the gyro drift coefficients that occur in corresponding directions. Simulations are conducted to validate the theoretical analysis and the deduced analytical expressions. The results show that the proposed hybrid transverse navigation can ensure the same accuracy and oscillation characteristics in polar areas as the traditional algorithm in low and mid latitude regions.

Lunar Navigator - A Miniature, Fully Autonomous, Lunar Navigation, Surveyor, and Range Finder System, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Microcosm proposes to design and develop a fully autonomous Lunar Navigator based on our MicroMak miniature star sensor and a gravity gradiometer similar to one on a...

Polar Cooperative Navigation Algorithm for Multi-Unmanned Underwater Vehicles Considering Communication Delays

Directory of Open Access Journals (Sweden)

Zheping Yan

2018-03-01

Full Text Available To solve the navigation accuracy problems of multi-Unmanned Underwater Vehicles (multi-UUVs in the polar region, a polar cooperative navigation algorithm for multi-UUVs considering communication delays is proposed in this paper. UUVs are important pieces of equipment in ocean engineering for marine development. For UUVs to complete missions, precise navigation is necessary. It is difficult for UUVs to establish true headings because of the rapid convergence of Earth meridians and the severe polar environment. Based on the polar grid navigation algorithm, UUV navigation in the polar region can be accomplished with the Strapdown Inertial Navigation System (SINS in the grid frame. To save costs, a leader-follower type of system is introduced in this paper. The leader UUV helps the follower UUVs to achieve high navigation accuracy. Follower UUVs correct their own states based on the information sent by the leader UUV and the relative position measured by ultra-short baseline (USBL acoustic positioning. The underwater acoustic communication delay is quantized by the model. In this paper, considering underwater acoustic communication delay, the conventional adaptive Kalman filter (AKF is modified to adapt to polar cooperative navigation. The results demonstrate that the polar cooperative navigation algorithm for multi-UUVs that considers communication delays can effectively navigate the sailing of multi-UUVs in the polar region.

GPS surveying method applied to terminal area navigation flight experiments

Energy Technology Data Exchange (ETDEWEB)

Murata, M; Shingu, H; Satsushima, K; Tsuji, T; Ishikawa, K; Miyazawa, Y; Uchida, T [National Aerospace Laboratory, Tokyo (Japan)

1993-03-01

With an objective of evaluating accuracy of new landing and navigation systems such as microwave landing guidance system and global positioning satellite (GPS) system, flight experiments are being carried out using experimental aircraft. This aircraft mounts a GPS and evaluates its accuracy by comparing the standard orbits spotted by a Kalman filter from the laser tracing data on the aircraft with the navigation results. The GPS outputs position and speed information from an earth-centered-earth-fixed system called the World Geodetic System, 1984 (WGS84). However, in order to compare the navigation results with output from a reference orbit sensor or other navigation sensor, it is necessary to structure a high-precision reference coordinates system based on the WGS84. A method that applies the GPS phase interference measurement for this problem was proposed, and used actually in analyzing a flight experiment data. As referred to a case of the method having been applied to evaluating an independent navigation accuracy, the method was verified sufficiently effective and reliable not only in navigation method analysis, but also in the aspect of navigational operations. 12 refs., 10 figs., 5 tabs.