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Swarm robot SLAM with point-line matching in weak information environments

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Abstract

Simultaneous Localization and Mapping (SLAM) in weak information environment scenarios where there are only sparse and ambiguous references are available presents significant challenges. This paper introduces a swarm robots based point-line matching based solution to enhance the accuracy and robustness of localization and mapping within such environments. Our approach employs a centralized serverbased architecture for the swarm robot system and utilizes an ORB-based Distributed Bag-of-Words (DBoW) algorithm to construct point and line feature dictionaries. By generating point-line pairs, the proposed method effectively addresses perceptual overlap issues, thereby improving the overall performance of localization and mapping for swarm robots. Experimental results validate the superiority of the proposed approach in comparison to traditional methods, highlighting its potential for real-world applications in challenging environments for swarm robot SLAM.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 85-90 (6 pages)

Publication milestones

  • Published - 07/11/2023

Publication status

Published - 07/11/2023

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

Publication series

  • Publication series name: 2023 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale, 3M-NANO 2023 - Proceedings

ISBN (Print)

9798350344486

ISBN (Electronic)

9798350344486

External Publication IDs

  • handle.net: 10547/626155
  • Scopus: 85179009235

Host publication title

2023 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale, 3M-NANO 2023 - Proceedings

Host publication editors

  • Zuobin Wang
  • Dongxu Wang

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