Multi-objective Rapidly-Exploring Random Tree Robot Patrol Path Optimization Method
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This work is supported by National Natural Science Foundation of China (U21A20487), Shenzhen Technology Project (JCYJ20180507182610734, KCXFZ20201221173411032), CAS Key Technology Talent Program

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    Abstract:

    A multi-objective rapidly-exploring random tree path optimization method is proposed for the multiobjective patrol path planning of mobile robots. According to the provided environment map and patrol target points, a new method RRT-Connect-ACO is used to obtain the patrol sequence and feasible path of the target points. Then the optimal path is obtained by introducing informed subset to optimize the path. The experiment results show that the method considers the influence of terrain and obtains an optimal path that is more consistent with the actual situation, which is different from the existing multi-objective path planning algorithms.

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ZHANG Ke, SONG Chengqun, CHENG Jun, et al. Multi-objective Rapidly-Exploring Random Tree Robot Patrol Path Optimization Method[J]. Journal of Integration Technology,2023,12(4):32-41

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  • Received:
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  • Online: July 27,2023
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