期刊
IEEE ROBOTICS AND AUTOMATION LETTERS
卷 7, 期 2, 页码 4837-4844出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LRA.2022.3152687
关键词
Motion and path planning; nonholonomic motion planning; path quality evaluation
类别
资金
- National Key Research and Development Program of China [SQ2019YFB130016]
- Open Research Project of the State Key Laboratory of Industrial Control Technology [ICT2021B10]
This study proposes a general robust reference path selection method (RPSM) to improve the mobile performance of autonomous patrol robots. The experiments confirm that RPSM enriches the diversity and robustness of reference paths, and significantly improves the execution efficiency.
In this letter, a general robust reference path selection method (RPSM) that can be integrated into current existing motion planning algorithms is proposed to improve the mobile performance of autonomous patrol robots. The proposed RPSM maintains a dynamic array of path candidates that contains newly found paths, optimal historical paths, and hybrid paths that incorporate local trajectories. All these candidates will be evaluated in a unified criterion, and the best path with the minimal cost will he presented for trajectory tracking, ensuring the consistency and smoothness of the actual motion. Experiments with two different kinds of robots in various scenarios confirm that RPSM enriches the diversity and robustness of reference paths, and improves the execution efficiency by significantly reducing the average actual trajectory distance, orientation change, and total execution time, with an acceptable extra computational cost in comparison to the corresponding original hybrid A* algorithm.
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