Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/147248
Title: Magnetic-assisted initialization for infrastructure-free mobile robot localization
Authors: Wu, Zhenyu
Wen, Mingxing
Peng, Guohao
Tang, Xiaoyu
Wang, Danwei
Keywords: Engineering
Issue Date: 2019
Source: Wu, Z., Wen, M., Peng, G., Tang, X. & Wang, D. (2019). Magnetic-assisted initialization for infrastructure-free mobile robot localization. 2019 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), 518-523. https://dx.doi.org/10.1109/CIS-RAM47153.2019.9095809
Abstract: Most of the existing mobile robot localization solutions are either heavily dependent on pre-installed infrastructures or having difficulty working in highly repetitive environments which do not have sufficient unique features. To address this problem, we propose a magnetic-assisted initialization approach that enhances the performance of infrastructure-free mobile robot localization in repetitive featureless environments. The proposed system adopts a coarse-to-fine structure, which mainly consists of two parts: magnetic field-based matching and laser scan matching. Firstly, the interpolated magnetic field map is built and the initial pose of the mobile robot is partly determined by the k-Nearest Neighbors (k-NN) algorithm. Next, with the fusion of prior initial pose information, the robot is localized by laser scan matching more accurately and efficiently. In our experiment, the mobile robot was successfully localized in a featureless rectangular corridor with a success rate of 88% and an average correct localization time of 6.6 seconds.
URI: https://hdl.handle.net/10356/147248
ISBN: 9781728134581
DOI: 10.1109/CIS-RAM47153.2019.9095809
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/CIS-RAM47153.2019.9095809
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

Files in This Item:
File Description SizeFormat 
1911.09313.pdf2.03 MBAdobe PDFView/Open

Page view(s)

143
Updated on Jun 30, 2022

Download(s)

12
Updated on Jun 30, 2022

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.