A navigation and mapping method for mobile robots based on 2D laser simultaneous localization and mapping algorithm

Fuxiang Zhang; Jianxiang Liu; Xiangpeng Kong; Yunfeng Sun; Yulu Wu; Ling Li

doi:10.1117/12.3004677

9 October 2023 A navigation and mapping method for mobile robots based on 2D laser simultaneous localization and mapping algorithm

Fuxiang Zhang, Jianxiang Liu, Xiangpeng Kong, Yunfeng Sun, Yulu Wu, Ling Li

Author Affiliations +

Proceedings Volume 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023); 127910C (2023) https://doi.org/10.1117/12.3004677
Event: Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 2023, Qingdao, SD, China

Abstract

Simultaneous localization and mapping (SLAM) and path planning are key technologies for robot navigation. The grid map generated by SLAM technology is a prerequisite for the path planning algorithm of mobile robots, playing an important role in autonomous robot navigation. 2D laser SLAM relies on distance information perceived by 2D laser radar to perform pose estimation and map construction, with advantages of high mapping accuracy and stable performance. In this article, we built an experimental platform using the ROS robot operating system, simulated and validated the Gmapping algorithm, and applied the validated algorithm to the Autolabor Pro1 robot platform for indoor mapping. The results show that the algorithm requires less computation and has higher accuracy in constructing small-scale maps, with good mapping effects.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Fuxiang Zhang, Jianxiang Liu, Xiangpeng Kong, Yunfeng Sun, Yulu Wu, and Ling Li "A navigation and mapping method for mobile robots based on 2D laser simultaneous localization and mapping algorithm", Proc. SPIE 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 127910C (9 October 2023); https://doi.org/10.1117/12.3004677

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