中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Biologically Inspired Complete Coverage Path Planning Algorithm Based on Q-Learning

文献类型:期刊论文

作者X. Tan, L. Han, H. Gong and Q. Wu
刊名Sensors
出版日期2023
卷号23期号:10
ISSN号14248220
DOI10.3390/s23104647
英文摘要Complete coverage path planning requires that the mobile robot traverse all reachable positions in the environmental map. Aiming at the problems of local optimal path and high path coverage ratio in the complete coverage path planning of the traditional biologically inspired neural network algorithm, a complete coverage path planning algorithm based on Q-learning is proposed. The global environment information is introduced by the reinforcement learning method in the proposed algorithm. In addition, the Q-learning method is used for path planning at the positions where the accessible path points are changed, which optimizes the path planning strategy of the original algorithm near these obstacles. Simulation results show that the algorithm can automatically generate an orderly path in the environmental map, and achieve 100% coverage with a lower path repetition ratio. © 2023 by the authors.
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源URL[http://ir.ciomp.ac.cn/handle/181722/67881]  
专题中国科学院长春光学精密机械与物理研究所
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GB/T 7714
X. Tan, L. Han, H. Gong and Q. Wu. Biologically Inspired Complete Coverage Path Planning Algorithm Based on Q-Learning[J]. Sensors,2023,23(10).
APA X. Tan, L. Han, H. Gong and Q. Wu.(2023).Biologically Inspired Complete Coverage Path Planning Algorithm Based on Q-Learning.Sensors,23(10).
MLA X. Tan, L. Han, H. Gong and Q. Wu."Biologically Inspired Complete Coverage Path Planning Algorithm Based on Q-Learning".Sensors 23.10(2023).

入库方式: OAI收割

来源:长春光学精密机械与物理研究所

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