Pedestrian Navigation System with Trinal-IMUs for Drastic Motions.

Yiming Ding,Zhiguo Cao,Zhi Xiong,Zhengchun Wang,Wanling Li

doi:10.3390/s20195570

Yiming Ding, Zhiguo Cao + Show 3 more

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https://doi.org/10.3390/s20195570

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Abstract

The combination of biomechanics and inertial pedestrian navigation research provides a very promising approach for pedestrian positioning in environments where Global Positioning System (GPS) signal is unavailable. However, in practical applications such as fire rescue and indoor security, the inertial sensor-based pedestrian navigation system is facing various challenges, especially the step length estimation errors and heading drift in running and sprint. In this paper, a trinal-node, including two thigh-worn inertial measurement units (IMU) and one waist-worn IMU, based simultaneous localization and occupation grid mapping method is proposed. Specifically, the gait detection and segmentation are realized by the zero-crossing detection of the difference of thighs pitch angle. A piecewise function between the step length and the probability distribution of waist horizontal acceleration is established to achieve accurate step length estimation both in regular walking and drastic motions. In addition, the simultaneous localization and mapping method based on occupancy grids, which involves the historic trajectory to improve the pedestrian’s pose estimation is introduced. The experiments show that the proposed trinal-node pedestrian inertial odometer can identify and segment each gait cycle in the walking, running, and sprint. The average step length estimation error is no more than 3.58% of the total travel distance in the motion speed from 1.23 m/s to 3.92 m/s. In combination with the proposed simultaneous localization and mapping method based on the occupancy grid, the localization error is less than 5 m in a single-story building of 2643.2 m.

Highlights

The inertial pedestrian navigation system has a wide range of applications in hotspots such as firefighting, indoor security, tunnel patrols, and other fields
The zero-velocity update (ZUPT) algorithm has been widely applied in the field of inertial pedestrian navigation because it is suitable for the foot-mounted inertial measurement units (IMU) case to compensate for traveled distance error during normal walking by introducing heuristic periodic zero velocity corrections [1]
To enhance the capability of the inertial pedestrian navigation system in dealing with the drastic motions and address the unbounded accumulated positioning error, this paper proposed a triple-node IMUs pedestrian inertial navigation system with an occupancy grid-based FastSLAM

Summary

Introduction

The inertial pedestrian navigation system has a wide range of applications in hotspots such as firefighting, indoor security, tunnel patrols, and other fields. These practical applications typically require pedestrians to repeatedly move vigorously in the same indoor environment, such as running and sprint, rather than just regular walking. The zero-velocity update (ZUPT) algorithm has been widely applied in the field of inertial pedestrian navigation because it is suitable for the foot-mounted IMU case to compensate for traveled distance error during normal walking by introducing heuristic periodic zero velocity corrections [1]. A method fusing the navigation information of dual foot-mounted ZUPT-aided INSs was proposed [2]. This method is based on the intuition that the distance of separation between right and left foot INSs cannot be longer than a quantity known as foot-to-foot maximum separation

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