Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/141856
Title: UWB/LiDAR fusion for cooperative range-only SLAM
Authors: Song, Yang
Guan, Mingyang
Tay, Wee Peng
Law, Choi Look
Wen, Changyun
Keywords: Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics
Issue Date: 2019
Source: Song, Y., Guan, M., Tay, W. P., Law, C. L., & Wen, C. (2019). UWB/LiDAR fusion for cooperative range-only SLAM. Proceedings of 2019 International Conference on Robotics and Automation (ICRA), 6568-6574. doi:10.1109/ICRA.2019.8794222
Abstract: We equip an ultra-wideband (UWB) node and a 2D LiDAR sensor a.k.a. 2D laser rangefinder on a mobile robot, and place UWB beacon nodes at unknown locations in an unknown environment. All UWB nodes can do ranging with each other thus forming a cooperative sensor network. We propose to fuse the peer-to-peer ranges measured between UWB nodes and laser scanning information, i.e., range measured between robot and nearby objects/obstacles, for simultaneous localization of the robot, all UWB beacons and LiDAR mapping. The fusion is inspired by two facts: 1) LiDAR may improve UWB-only localization accuracy as it gives a more precise and comprehensive picture of the surrounding environment; 2) on the other hand, UWB ranging measurements may remove the error accumulated in the LiDAR-based SLAM algorithm. Our experiments demonstrate that UWB/LiDAR fusion enables drift-free SLAM in real-time based on ranging measurements only.
URI: https://hdl.handle.net/10356/141856
ISBN: 978-1-5386-8176-3
ISSN: 1050-4729
DOI: 10.1109/ICRA.2019.8794222
Rights: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/ICRA.2019.8794222.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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