基于双光源连续反射的新型机器人全局路径规划方法

ISA transactions Pub Date : 2024-07-01 Epub Date: 2024-05-09 DOI:10.1016/j.isatra.2024.05.006
Jintao Ye, Lina Hao, Hongtai Cheng, Xingchen Li
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引用次数: 0

摘要

为了解决机器人在包含狭窄通道的环境中的路径规划问题,本文提出了一种新颖的全局路径规划方法:DSR(双源光连续反射探索)算法。该算法受到光的自然反射的启发,采用连续反射的概念进行路径规划。它能在包含狭窄通道的地图上高效生成渐近最优路径。DSR 算法已在含有狭窄通道的不同地图上进行了评估,并与其他算法进行了比较。与双向快速探索随机树算法相比,DSR 算法显著减少了路径长度(27.08% 和 34.35%)和时间消耗(98.47% 和 91.03%)。数值模拟和实验分析证明了 DSR 算法的卓越性能。
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A novel global path planning method for robot based on dual-source light continuous reflection.

Aiming to address the problem of robot path planning in environments containing narrow passages, this paper proposes a novel global path planning method: the DSR (Dual-source Light Continuous Reflection Exploration) algorithm. This algorithm, inspired by the natural reflection of light, employs the concept of continuous reflection for path planning. It can efficiently generate an asymptotically optimal path on the map containing narrow passages. The DSR algorithm has been evaluated on different maps with narrow passages and compared with other algorithms. In comparison with the bidirectional Rapidly-exploring Random Tree algorithm, the DSR algorithm achieves a significant reduction in both path length (by 27.08% and 34.35%) and time consumption (by 98.47% and 91.03%). Numerical simulations and experimental analysis have demonstrated the excellent performance of the DSR algorithm.

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