启发式RRT融合A*用于无人机三维路径规划

Qiang Fu, Xinghui Lan, Yuanfa Ji, Xiyan Sun, Fenghua Ren
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引用次数: 1

摘要

路径规划是实现无人机自主飞行的关键。针对三维空间环境下路径规划中存在的盲目搜索、路径长、曲折等问题,提出了一种启发式双向目标RRT融合A*算法。首先,该算法结合了启发式概率和偏置展开策略,提高了采样的目标方位;在得到完整路径点后,通过A*算法的完整路径融合冗余节点得到最短路径。最后利用b样条算法对路径进行平滑处理,得到光滑可行路径。实验结果表明,与传统B-RRT算法相比,改进的B-RRT算法的节点利用率提高了9.6倍,扩展节点减少了86.9%,搜索时间缩短了21.46%,路径缩短了7.9%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Heuristic RRT fusion A* for 3D path planning of UAV
Path planning is the key to the autonomous flight of unmanned aerial vehicle (UAV). Aiming at the problems of blind search, long and zigzag path in the path planning of three-dimensional space environment, A heuristic bidirectional target RRT fusion A* algorithm was proposed. Firstly, the algorithm combines heuristic probability and bias expansion strategy to improve the target orientation of sampling. After obtaining the complete path point, the shortest path is obtained by fusing redundant nodes in the complete path of A* algorithm. Finally, B-spline algorithm is used to smooth the path, which obtains a smooth feasible path. Experimental results show that compared with the traditional B-RRT algorithm, the improved B-RRT algorithm improves the node utilization by 9.6 times, reduces the extension nodes by 86.9%, shorts the search time by 21.46%, and shorts the path by 7.9%.
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