Path planning of a mobile robot using an improved mixed-method of potential field and wall following

Author:

Xing Qiang1ORCID,Xu Sheng1ORCID,Wang Hao2,Wang Jiajia1,Zhao Wei1,Xu Haili1

Affiliation:

1. School of mechanical engineering, Nantong University, Nantong, Jiangsu, China

2. College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China

Abstract

The existing Bug algorithms, which are the same as wall-following algorithms, offer good performance in solving local minimum problems caused by potential fields. However, because of the odometer drift that occurs in actual environments, the performance of the paths planned by these algorithms is significantly worse in actual environments than in simulated environments. To address this issue, this article proposes a new Bug algorithm. The proposed algorithm contains a potential field function that is based on the relative velocity, which enables the potential field method to be extended to dynamic scenarios. Using the cumulative changes in the internal and external angles and the reset point of the robot during the wall-following process, the condition for state switching has been redesigned. This improvement not only solves the problem of position estimation deviation caused by odometer noise but also enhances the decision-making ability of the robot. The simulation results demonstrate that the proposed algorithm is simpler and more efficient than existing wall-following algorithms and can realise path planning in an unknown dynamic environment. The experimental results for the Kobuki robot further validate the effectiveness of the proposed algorithm.

Funder

National Natural Science Foundation of China

Publisher

SAGE Publications

Subject

Artificial Intelligence,Computer Science Applications,Software

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Path Planning Optimization for Obstacle Avoidance in Unknown Environment;2024 36th Chinese Control and Decision Conference (CCDC);2024-05-25

2. Maritime Search Path Planning Method of an Unmanned Surface Vehicle Based on an Improved Bug Algorithm;Journal of Marine Science and Engineering;2023-12-07

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