Enhancing Body-Mounted LiDAR SLAM using an IMU-based Pedestrian Dead Reckoning (PDR) Model [PDF]
2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS), 2020 Simultaneous localization and mapping for human body-mounted platforms have been recently the focus of navigation research to support a wide range of applications such as rescue, first-responders, mining, and defense. For vehicular platforms, wheel odometry has been used to enhance the accuracy of SLAM.
Hamza Sadruddin +2 more
core +4 more sources
Smartphone-Based Pedestrian Dead Reckoning for 3D Indoor Positioning
Sensors, 2021 Indoor localization based on pedestrian dead reckoning (PDR) is drawing more and more attention of researchers in location-based services (LBS). The demand for indoor localization has grown rapidly using a smartphone.
Jijun Geng +5 more
doaj +2 more sources
Sensors, 2019 Pedestrian dead reckoning (PDR) systems based on a microelectromechanical-inertial measurement unit (MEMS-IMU) providing advantages of full autonomy and strong anti-jamming performance are becoming a feasible choice for pedestrian indoor positioning.
Qigao Fan +8 more
doaj +2 more sources
Drift Control of Pedestrian Dead Reckoning (PDR) for Long Period Navigation under Different Smartphone Poses [PDF]
The 8th International Electronic Conference on Sensors and Applications, 2021 The inherent errors of low-cost inertial sensors cause significant heading drift that accumulates over time, making it difficult to rely on Pedestrian Dead Reckoning (PDR) for navigation over a long period.
Ahmed Mansour +5 more
openaire +2 more sources
Pedestrian Dead-Reckoning Indoor Localization Based on OS-ELM
IEEE Access, 2018 Smartphone-based pedestrian dead-reckoning (PDR) has become promising in indoor localization since it locates users with a smartphone only. However, existing PDR approaches are still facing the problem of accumulated localization errors due to low-cost ...
Mingyang Zhang +2 more
exaly +3 more sources
Pedestrian Dead Reckoning with Low-Cost Foot-Mounted IMU Sensor
Micromachines, 2022 In this paper, we researched Pedestrian Dead Reckoning (PDR) with one foot-mounted IMU sensor. The issues of PDR are magnetism noise and accumulated error due to the noise included in acceleration and gyro data.
Shunsei Yamagishi, Lei Jing
doaj +2 more sources
SHAKF-PU: Sage–Husa Adaptive Kalman Filtering-Based Pedestrian Characteristic Parameter Update Mechanism for Enhancing Step Length Estimation in Pedestrian Dead Reckoning [PDF]
Applied Bionics and BiomechanicsStep length estimation (SLE) is the core process for pedestrian dead reckoning (PDR) for indoor positioning. Original SLE requires accurate estimations of pedestrian characteristic parameter (PCP) by the linear update, which may cause large distance ...
Chinyang Henry Tseng, Jiunn-Yih Wu
doaj +2 more sources
Robust Pedestrian Dead Reckoning Based on MEMS-IMU for Smartphones
Sensors, 2018 This paper proposes a pedestrian dead reckoning (PDR) algorithm based on the strap-down inertial navigation system (SINS) using the gyros, accelerometers, and magnetometers on smartphones. In addition to using a gravity vector, magnetic field vector, and
Jian Kuang, Xiaoji Niu, Xingeng Chen
doaj +2 more sources
IMPROVEMENT OF PEDESTRIAN DEAD RECKONING ALGORITHM FOR INDOOR POSITIONING BY USING STEP LENGTH ESTIMATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Pedestrian dead reckoning (PDR) can solve the position information by its inertial measurement unit (IMU), which is a method to achieve indoor autonomous positioning without deploying positioning base stations in advance.
L. Huang, H. Li, W. Li, W. Wu, X. Kang
doaj +1 more source
Ultrasound-aided pedestrian dead reckoning for indoor navigation [PDF]
, 2008 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.
Muthukrishnan, Kavitha +3 more
core +5 more sources