Pedestrian Tracking and Navigation Using Neural Networks and Fuzzy Logic

Toth, Charles K.; Grejner‐Brzezinska, Dorota A.; Moafipoor, Shahram

doi:10.1109/wisp.2007.4447525

Cited by 34 publications

(17 citation statements)

References 7 publications

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“…The study ends with a recommendation for designing mobile pedestrian navigation systems. Toth et al (2007) present an artificial neural network and fuzzy logic-based theoretical foundation and implementation algorithms, which integrate GPS, micro-electro-mechanical inertial measurement unit (MEMS IMU), digital barometer, electronic compass and human pedometry to provide navigation and tracking of military and rescue ground personnel. Chen et al (2009) propose an integrated GPS and multi-sensor pedestrian positioning system to bridge the gaps of GPS signal outages.…”

Section: Global Positioning System-based Navigation Systemsmentioning

confidence: 99%

A GPS-based real-time avalanche path warning and navigation system

Dewali

Joshi

Ganju

et al. 2013

Geomatics, Natural Hazards and Risk

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Frequent avalanche activity and poor route visibility due to bad weather make snow bound mountainous regions quite unsafe for travel during the winter months. Hence, there is a need for an accurate navigation device that can help in the safe movement of mountain travellers in avalanche prone areas. This paper presents the design and implementation of a portable GPS-based warning and navigation system, capable of providing safe navigation to mountain travellers in avalanche-prone regions. The system uses a hand-held GPS with a positional accuracy of 2-5 m. A customized application has been developed for the visualization of maps, navigation, positioning, tracking and issuing avalanche path warning. On the basis of registered avalanche path data, this application updates the traveller at predefined time intervals on whether the current position of the traveller is inside or outside an avalanche path. When the traveller enters an avalanche prone area, a warning in the form of text and voice messages is generated by the device. For the testing and accuracy analysis of this application, a part of the Manali-Dhundi highway was designated as the study area. In numerous track tests, the system has demonstrated a high level of accuracy and a repetition in locating registered avalanche sites in open slopes/bare lands but accuracy deteriorated in narrow valley/forested areas. An analysis of the trial results shows that the system can help travellers in snowbound mountain regions as a warning and navigation tool, using accurately registered avalanche sites and an appropriate buffer size around these sites.

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Section: Global Positioning System-based Navigation Systemsmentioning

confidence: 99%

A GPS-based real-time avalanche path warning and navigation system

Dewali

Joshi

Ganju

et al. 2013

Geomatics, Natural Hazards and Risk

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“…Coley et al [6] use wavelets to detect steps using gyroscopes only. In the work of Toth et al [25], a prototype for pedestrian dead-reckoning and their general concept of sensor fusion is discussed. The HeadSLAM approach by Cinaz and Kenn [5] employs a laser scanner together with an IMU mounted on a helmet.…”

Section: Related Workmentioning

confidence: 99%

Activity-Based Estimation of Human Trajectories

et al. 2012

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Abstract-We present a novel approach to incrementally determine the trajectory of a person in 3D based on its motions and activities in real-time. In our algorithm, we estimate the motions and activities of the user given the data obtained from a motion capture suit equipped with several inertial measurement units (IMUs). These activities include walking up and down staircases as well as opening and closing doors. We interpret the first two types of activities as motion constraints and door handling events as landmark detections in a graph-based simultaneous localization and mapping (SLAM) framework. Since we cannot distinguish between individual doors, we employ a multihypothesis tracking approach on top of the SLAM procedure to deal with the high data-association uncertainty. As a result, we are able to accurately and robustly recover the trajectory of the person. Additionally we present an algorithm to build approximate geometrical and the topological maps based on the estimated trajectory and detected activities. We evaluate our approach in practical experiments carried out with different subjects and in various environments.

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“…There are six parameters that contain the information about a step length. They are step frequency, peak-to-peak mean acceleration, peak-to-peak variation in acceleration, terrain slope, change in barometric height during a single gait cycle, and subject's height [28]. The results showed that the accuracy of this system is 3-5 m CEP (circular error probable) 50%.…”

Section: Introductionmentioning

confidence: 97%

“…Nevertheless, since GNSS signals are not available indoors, various navigation methods relying on different technologies, such as proximity, triangulation, fingerprinting, and dead reckoning, have been proposed [5]. Since the dead reckoning method requires little or no infrastructure to be using a knowledge-based method to model human locomotion, and the adopted sensors of this system are continuously calibrated when GNSS signals are available [28]. There are six parameters that contain the information about a step length.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Knowledge-Based Step Length Estimation Method Based on Fuzzy Logic and Multi-Sensor Fusion Algorithms for a Pedestrian Dead Reckoning System

Lai

Chang

Tsai

et al. 2016

IJGI

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Abstract:The demand for pedestrian navigation has increased along with the rapid progress in mobile and wearable devices. This study develops an accurate and usable Step Length Estimation (SLE) method for a Pedestrian Dead Reckoning (PDR) system with features including a wide range of step lengths, a self-contained system, and real-time computing, based on the multi-sensor fusion and Fuzzy Logic (FL) algorithms. The wide-range SLE developed in this study was achieved by using a knowledge-based method to model the walking patterns of the user. The input variables of the FL are step strength and frequency, and the output is the estimated step length. Moreover, a waist-mounted sensor module has been developed using low-cost inertial sensors. Since low-cost sensors suffer from various errors, a calibration procedure has been utilized to improve accuracy. The proposed PDR scheme in this study demonstrates its ability to be implemented on waist-mounted devices in real time and is suitable for the indoor and outdoor environments considered in this study without the need for map information or any pre-installed infrastructure. The experiment results show that the maximum distance error was within 1.2% of 116.51 m in an indoor environment and was 1.78% of 385.2 m in an outdoor environment.

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Pedestrian Tracking and Navigation Using Neural Networks and Fuzzy Logic

Cited by 34 publications

References 7 publications

A GPS-based real-time avalanche path warning and navigation system

A GPS-based real-time avalanche path warning and navigation system

Activity-Based Estimation of Human Trajectories

A Knowledge-Based Step Length Estimation Method Based on Fuzzy Logic and Multi-Sensor Fusion Algorithms for a Pedestrian Dead Reckoning System

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