• Title/Summary/Keyword: pedestrian localization

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Sensor fusion based ambulatory system for indoor localization

  • Lee, Min-Yong;Lee, Soo-Yong
    • Journal of Sensor Science and Technology
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    • v.19 no.4
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    • pp.278-284
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    • 2010
  • Indoor localization for pedestrian is the key technology for caring the elderly, the visually impaired and the handicapped in health care districts. It also becomes essential for the emergency responders where the GPS signal is not available. This paper presents newly developed pedestrian localization system using the gyro sensors, the magnetic compass and pressure sensors. Instead of using the accelerometer, the pedestrian gait is estimated from the gyro sensor measurements and the travel distance is estimated based on the gait kinematics. Fusing the gyro information and the magnetic compass information for heading angle estimation is presented with the error covariance analysis. A pressure sensor is used to identify the floor the pedestrian is walking on. A complete ambulatory system is implemented which estimates the pedestrian's 3D position and the heading.

Pedestrian Navigation System in Mountainous non-GPS Environments

  • Lee, Sungnam
    • Journal of information and communication convergence engineering
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    • v.19 no.3
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    • pp.188-197
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    • 2021
  • In military operations, an accurate localization system is required to navigate soldiers to their destinations, even in non-GPS environments. The global positioning system is a commonly used localization method, but it is difficult to maintain the robustness of GPS-based localization against jamming of signals. In addition, GPS-based localization cannot provide important terrain information such as obstacles. With the widespread use of embedded sensors, sensor-based pedestrian tracking schemes have become an attractive option. However, because of noisy sensor readings, pedestrian tracking systems using motion sensors have a major drawback in that errors in the estimated displacement accumulate over time. We present a group-based standalone system that creates terrain maps automatically while also locating soldiers in mountainous terrain. The system estimates landmarks using inertial sensors and utilizes split group information to improve the robustness of map construction. The evaluation shows that our system successfully corrected and combined the drift error of the system localization without infrastructure.

Sensor Information Filter for Enhancing the Indoor Pedestrian Localization Accuracy (보행자의 실내 위치 추정 정확도 향상을 위한 다양한 센서 정보 필터)

  • Kim, Jooyoung;Lee, Sooyong
    • The Journal of Korea Robotics Society
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    • v.7 no.4
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    • pp.276-283
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    • 2012
  • Due to the low localization accuracy and the requirement of special infrastructure, current LBS(Localization Based Service) is limited to show P.O.I.(Point of Interest) nearby. Improvement of IMU(Inertial Measurement Unit) based deadreckoning is presented in this paper. Additional sensors such as the magnetic compass and magnetic flux sensors are used as well as the accelerometer and the gyro for getting more information of movement. Based on the pedestrian movement, appropriate sensor information is selected and the complementary filter is used in order to enhance the accuracy of the localization.

Real Time Indoor Localization Using Geomagnetic Fingerprinting and Pedestrian Dead Reckoning (지구 자기장 기반 지문인식 및 추측 항법을 결합한 실시간 실내 위치정보 서비스)

  • Jang, HoJun;Choi, Lynn
    • KIISE Transactions on Computing Practices
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    • v.23 no.4
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    • pp.210-216
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    • 2017
  • In the paper we propose and implement a new indoor localization system where the techniques of magnetic field based fingerprinting and pedestrian dead reckoning are combined. First, we determine a target's location by comparing acquired magnetic field values with a magnetic field map containing pre-collected field values at different locations and choosing the location having the closest value. As the target moves, we use pedestrian dead reckoning to estimate the expected moving path, reducing the maximum positioning error of the initial location. The system eliminates the problem of localization error accumulation in pedestrian dead reckoning with the help of the fingerprinting and does not require Wi-Fi AP infrastructure, enabling cost-effective localization solution.

Gait Estimation System for Leg Diagnosis and Rehabilitation using Gyroscopes (하지 진단 및 재활을 위한 각속도계 기반 측정시스템)

  • Lee, Min-Young;Lee, Soo-Yong
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.9
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    • pp.866-871
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    • 2010
  • Gait analysis is essential for leg diagnosis and rehabilitation for the patients, the handicapped and the elderly. The use of 3D motion capture device for gait analysis is very common for gait analysis. However, this device has several shortcomings including limited workspace, visibility and high price. Instead, we developed gait estimation system using gyroscopes. This system provides gait information including the number of gaits, stride and walking distance. With four gyroscope (one for each leg's thigh and calf) outputs, the proposed gait modeling estimates the movements of the hip, the knees and the feet. Complete pedestrian localization is implemented with gait information and the heading angle estimated from the rate gyro and the magnetic compass measurements. The developed system is very useful for diagnosis and the rehabilitation of the pedestrian at the hospital. It is also useful for indoor localization of the pedestrians.

Pedestrian Gait Estimation and Localization using an Accelerometer (가속도 센서를 이용한 보행 정보 및 보행자 위치 추정)

  • Kim, Hui-Sung;Lee, Soo-Yong
    • The Journal of Korea Robotics Society
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    • v.5 no.4
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    • pp.279-285
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    • 2010
  • This paper presents the use of 3 axis accelerometer for getting the gait information including the number of gaits, stride and walking distance. Travel distance is usually calculated from the double integration of the accelerometer output with respect to time; however, the accumulated errors due to the drift are inevitable. The orientation change of the accelerometer also causes error because the gravity is added to the measured acceleration. Unless three axis orientations are completely identified, the accelerometer alone does not provide correct acceleration for estimating the travel distance. We proposed a way of minimizing the error due to the change of the orientation. Pedestrian localization is implemented with the heading angle and the travel distance. Heading angle is estimated from the rate gyro and the magnetic compass measurements. The performance of the localization is presented with experimental data.

Localization of Mobile Users with the Improved Kalman Filter Algorithm using Smart Traffic Lights in Self-driving Environments

  • Jung, Ju-Ho;Song, Jung-Eun;Ahn, Jun-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.5
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    • pp.67-72
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    • 2019
  • The self-driving cars identify appropriate navigation paths and obstacles to arrive at their destinations without human control. The autonomous cars are capable of sensing driving environments to improve driver and pedestrian safety by sharing with neighbor traffic infrastructure. In this paper, we have focused on pedestrian protection and have designed an improved localization algorithm to track mobile users on roads by interacting with smart traffic lights in vehicle environments. We developed smart traffic lights with the RSSI sensor and built the proposed method by improving the Kalman filter algorithm to localize mobile users accurately. We successfully evaluated the proposed algorithm to improve the mobile user localization with deployed five smart traffic lights.

BtPDR: Bluetooth and PDR-Based Indoor Fusion Localization Using Smartphones

  • Yao, Yingbiao;Bao, Qiaojing;Han, Qi;Yao, Ruili;Xu, Xiaorong;Yan, Junrong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.8
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    • pp.3657-3682
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    • 2018
  • This paper presents a Bluetooth and pedestrian dead reckoning (PDR)-based indoor fusion localization approach (BtPDR) using smartphones. A Bluetooth and PDR-based indoor fusion localization approach can localize the initial position of a smartphone with the received signal strength (RSS) of Bluetooth. While a smartphone is moving, BtPDR can track its position by fusing the localization results of PDR and Bluetooth RSS. In addition, BtPDR can adaptively modify the parameters of PDR. The contributions of BtPDR include: a Bluetooth RSS-based Probabilistic Voting (BRPV) localization mechanism, a probabilistic voting-based Bluetooth RSS and PDR fusion method, and a heuristic search approach for reducing the complexity of BRPV. The experiment results in a real scene show that the average positioning error is < 2m, which is considered adequate for indoor location-based service applications. Moreover, compared to the traditional PDR method, BtPDR improves the location accuracy by 42.6%, on average. Compared to state-of-the-art Wireless Local Area Network (WLAN) fingerprint + PDR-based fusion indoor localization approaches, BtPDR has better positioning accuracy and does not need the same offline workload as a fingerprint algorithm.

Gaussian Interpolation-Based Pedestrian Tracking in Continuous Free Spaces (연속 자유 공간에서 가우시안 보간법을 이용한 보행자 위치 추적)

  • Kim, In-Cheol;Choi, Eun-Mi;Oh, Hui-Kyung
    • The KIPS Transactions:PartB
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    • v.19B no.3
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    • pp.177-182
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    • 2012
  • We propose effective motion and observation models for the position of a WiFi-equipped smartphone user in large indoor environments. Three component motion models provide better proposal distribution of the pedestrian's motion. Our Gaussian interpolation-based observation model can generate likelihoods at locations for which no calibration data is available. These models being incorporated into the particle filter framework, our WiFi fingerprint-based localization algorithm can track the position of a smartphone user accurately in large indoor environments. Experiments carried with an Android smartphone in a multi-story building illustrate the performance of our WiFi localization algorithm.

Estimation of the User's Location/Posture for Mobile Augmented Reality (모바일 증강현실 구현을 위한 사용자의 위치/자세 추정)

  • Kim, Jooyoung;Lee, Sooyong
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.11
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    • pp.1011-1017
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    • 2012
  • Augmented Reality is being widely used not only for Smartphone users but also in industries such as maintenance, construction area. With smartphone, due to the low localization accuracy and the requirement of special infrastructure, current LBS (Localization Based Service) is limited to show P.O.I. (Point of Interest) nearby. Improvement of IMU (Inertial Measurement Unit) based deadreckoning is presented in this paper. Additional sensors such as the magnetic compass and magnetic flux sensors are used as well as the accelerometer and the gyro for getting more movement information. Based on the pedestrian movement, appropriate sensor information is selected and the complementary filter is used in order to enhance the accuracy of the localization. Additional sensors are used to measure the movements of the upper body and the head and to provide the user's line of sight.