基于改进A*和DWA算法的机器人动态路径规划

Chenxi Guan, Shuying Wang
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引用次数: 6

摘要

将传统的A*算法应用于机器人路径规划时,存在效率低、不能动态避障等问题。为了解决上述问题,提出了一种基于改进a *算法和DWA算法的融合算法。对A*算法进行了三方面的改进:减小A*算法的搜索方向,减少搜索时间;增加路径信息参数,动态调整启发式函数的权重;引入重要节点提取策略,减少匝数,缩短路径。最后,将改进的A*算法与DWA算法进行融合。实验结果表明,改进的融合算法可以实现全局最优路径规划和局部实时避障。
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Robot Dynamic Path Planning Based on Improved A* and DWA Algorithms
When the traditional A* algorithm is applied to robot path planning, it has the problems of low efficiency and unable to avoid obstacles dynamically. In order to solve the above problems, a fusion algorithm based on improved A* algorithm and DWA algorithm is proposed. The A* algorithm is improved in three aspects: reducing the search direction of A* algorithm to reduce the search time, adding path information parameters to dynamically adjust the weight of heuristic function, and introducing important node extraction strategy to reduce the number of turns and shorten the path. Finally, the improved A* algorithm is fused with DWA algorithm. The experimental results show that the improved fusion algorithm can realize global optimal path planning and local real-time obstacle avoidance.
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