SLAM-ING: A Wearable SLAM Inertial NaviGation System
IEEE Sensors, December 2022
Renjie Wu, Matthew Pike, Xiaoqing Chai, Boon-Giin Lee, Xian Wu. 2022. SLAM-ING: A Wearable SLAM Inertial NaviGation System. In IEEE Sensors. DOI:https://doi.org/10.1109/SENSORS52175.2022.9967255
Renjie Wu and Matthew Pike and Xiaoqing Chai and Boon-Giin Lee and Xian Wu. (2022). SLAM-ING: A Wearable SLAM Inertial NaviGation System. IEEE Sensors. https://doi.org/10.1109/SENSORS52175.2022.9967255
Renjie Wu and Matthew Pike and Xiaoqing Chai and Boon-Giin Lee and Xian Wu. "SLAM-ING: A Wearable SLAM Inertial NaviGation System." IEEE Sensors, 2022. https://doi.org/10.1109/SENSORS52175.2022.9967255
Renjie Wu, Matthew Pike, Xiaoqing Chai, Boon-Giin Lee, Xian Wu. 2022. SLAM-ING: A Wearable SLAM Inertial NaviGation System. IEEE Sensors. doi:10.1109/SENSORS52175.2022.9967255
Renjie Wu and Matthew Pike and Xiaoqing Chai and Boon-Giin Lee and Xian Wu, "SLAM-ING: A Wearable SLAM Inertial NaviGation System," IEEE Sensors, 2022. doi: 10.1109/SENSORS52175.2022.9967255
@inproceedings{ieee-sensors-2022,
title={SLAM-ING: A Wearable SLAM Inertial NaviGation System},
author={Renjie Wu and Matthew Pike and Xiaoqing Chai and Boon-Giin Lee and Xian Wu},
booktitle={IEEE Sensors},
year={2022},
doi={10.1109/SENSORS52175.2022.9967255}
}
Inertial Navigation System, SLAM, Wearable Sensing, Occupancy Grid Map
Abstract
Indoor Location-Based Service (ILBS) shows great research promotions with wide applications e.g., indoor firefighting and cave exploration. Foot-mounted Inertial Navigation System (INS), one approach of ILBS, lacks a reference map of the environment, resulting in poor trajectory recognition. This paper introduces SLAM-ING, a novel wearable type SLAM via a Zero Angular rate Update (ZARU) aided Inertial NaviGation. SLAM-ING proposes a gravity center calculation method, merging the dual (left and right) foot trajectories. Moreover, the proposed polar projection and occupancy grid map method determines the map boundary, enabling the fusion of the trajectory and ultrasound range. The mapping results of SLAM-ING are demonstrated with the ground truth. The location performance is validated using a self-created database, the results of which indicate lower horizontal and spherical error compared with the traditional INS in all scenarios.