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Article type: Research Article
Authors: Liu, Ziweia | Xu, Ziyua; b | Zheng, Xiyua | Zhao, Yongxinga | Wang, Jinghuaa; c; *
Affiliations: [a] College of Mechanical and Electric Engineering, Changchun University of Science and Technology, Changchun, P.R. China | [b] School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, P.R. China | [c] Ministry of Education Key Laboratory for Cross-Scale Micro and Nano Manufacturing, Changchun University of Science and Technology, Changchun, P.R. China
Correspondence: [*] Corresponding author. Jinghua Wang, College of Mechanical and Electric Engineering, Changchun University of Science and Technology, Changchun 130022, Jilin P.R. China. E-mail: hit1920s@163.com.
Abstract: Ground mobile robots can replace human beings to perform special tasks in threatened areas. Path planning technology provides mobile robots with the ability to reach the target position autonomously. When there are threats in the environment, the ground mobile robot needs to be able to reach the target position quickly and safely. Because threats are often difficult to calculate in such environments, and planned paths are difficult to use for path tracing. Therefore, path planning should comprehensively consider the distance, continuity and possible threats when moving. Aiming at the problem that the threat in the environment cannot be accurately calibrated usually, this paper proposes a method to mark the threat degree on the global elevation map by using the fuzzy logic system. In order to verify the feasibility of the algorithm, the improved algorithm with the classical algorithm in different environments and the current similar algorithm are compared with the current simulation experiment. The simulation results show that the algorithm has achieved good results, which proves the superiority of the algorithm. The path planning results of the algorithm in the threatened 3D environment not only have less threat, but also have better adaptability to the natural environment, and the planning path quality is better than that of the same type of algorithm.
Keywords: Mobile robot, fuzzy logic system, threat assessment, Hybrid-A*, path planning
DOI: 10.3233/JIFS-232076
Journal: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 3, pp. 7021-7034, 2024
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