改进A*与DWA的交通隔离机器人路径规划研究OA
Traffic isolation robot path planning based on improved A* and dynamic window approach
针对交通隔离机器人应用传统A*算法存在搜索时间长、路径危险点较多等问题,文中提出一种融合改进A*与动态窗口(DWA)算法.首先,采用四邻域结合左右对称凸邻域搜索策略、配合角度搜索策略与动态权重ODMW方案,对全局路径中冗余节点进行优化,并引入双向A*方案来提高搜索效率;然后,将改进后的A*全局路径算法与动态窗口法相融合,提升机器人实时避障能力;最后,通过仿真与实物验证对改进算法进行性能评估.实验结果显示,改进后的A*算法极大地降低了路径上的危险点个数,平均搜索时间减少68.22%,平均扩展节点数减少55.76%.同时,改进后的A*与DWA融合算法能够引导交通隔离机器人准确到达目标点,并有效避让未知障碍物,满足了交通隔离机器人实际应用场景的需求.
In view of the prolonged search time and excessive hazardous points in paths when applying the traditional A*algorithm to traffic isolation robots,this study proposes a hybrid algorithm integrating improved A* with the dynamic window approach(DWA).Firstly,a four-neighborhood combined with left-right symmetric convex neighborhood search strategy is employed,along with an angular search strategy and the obstacle-distance-map weighting strategy(ODMW),to optimize redundant nodes in global paths.A bidirectional A* scheme is introduced to enhance search efficiency.Subsequently,the enhanced A* global path planning algorithm is integrated with DWA to improve real-time obstacle avoidance capabilities.Finally,simulations and physical experiments were conducted to evaluate the performance of the improved algorithm.The results demonstrate that the optimized A* algorithm significantly reduces hazardous points along paths,decreases average search time by 68.22%,and reduces average expanded nodes by 55.76%.Moreover,the hybrid algorithm combining improved A* with DWA enables traffic isolation robots to accurately reach targets while effectively avoiding unknown obstacles.
李靖;徐海黎;蔡嘉俊;马守权;张思维;邢强
南通大学 机械工程学院,江苏 南通 226019南通大学 机械工程学院,江苏 南通 226019南通大学 机械工程学院,江苏 南通 226019南通天承光电科技有限公司,江苏 南通 226100南通天承光电科技有限公司,江苏 南通 226100南通大学 机械工程学院,江苏 南通 226019
信息技术与安全科学
交通隔离机器人路径规划改进A*算法DWA算法算法融合动态避障
traffic isolation robotpath planningimproved A* algorithmDWAalgorithm fusiondynamic obstacle avoidance
《现代电子技术》 2026 (13)
191-198,8
南通市自然科学基金(JC2023062)
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