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对于利用传统A*算法规划的路径存在搜索效率低下、节点冗余且不平滑及转弯易靠近障碍物等缺点,基于全向移动机器人提出了一种改进A*算法与动态窗口法(Dynamic Window Approach, DWA)相融合的实时路径规划方法。在传统A*算法的评价函数中加入环境中障碍物信息和父节点到目标点的代价信息,提高路径搜索效率;对当前节点扩展时进行安全检测,优化节点扩展方向;基于安全阈值提取路径关键点,优化搜索路径;将优化后的关键点作为DWA算法的临时目标点,将2种算法融合规划出一条基于全局最优的圆滑曲线路径。实验结果表明,基于融合导航算法规划的路径能安全快速地躲避动态障碍物。
Abstract：Considering the disadvantages of traditional A* algorithm,such as low search efficiency,more redundant nodes and approaching obstacles easily,a real-time path planning method combining improved A * algorithm with Dynamic Window Approach(DWA) is proposed. In the evaluation function of traditional A* algorithm,the obstacle information in the environment and the cost information from the parent node to the target point are added to improve the efficiency of path search. The security threshold value is introduced to detect the safety of the current node when expanding the current node. The search path is optimized by extracting the key points of the search path based on the security threshold value. Finally,the key point is taken as the temporary target point of DWA algorithm,and the two algorithms are fused to plan a smooth curve path based on global optimization. The experimental results show that the path planning based on fusion navigation algorithm can avoid dynamic obstacles safely and quickly.
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基本信息:
DOI：
中图分类号:TP242;TP18
引用信息:
[1]张振,张华良,邓永胜等.融合改进A~*算法与DWA算法的机器人实时路径规划[J].无线电工程,2022,52(11):1984-1993.
基金信息:
国家自然科学基金(91648204)~~