改进A^(*)和DWA的机器人路径规划研究  

Research on robot path planning based on improved A^(*) and DWA

作　　者：马自勇 朱星光 马立东 MA Ziyong;ZHU Xingguang;MA Lidong(School of Mechanical Engineering,Taiyuan University of Science and Technology,Taiyuan 030024,China;Shanxi Provincial Key Laboratory of Intelligent Technology and System for Heavy-Duty Equipment Operation,Taiyuan 030024,China;High-End Equipment and Rail Transit Technology Research and Development Center of Haian,Taiyuan University of Science and Technology,Haian 226600,China)

机构地区：[1]太原科技大学机械工程学院,山西太原030024 [2]重载装备作业智能化技术与系统山西省重点实验室,山西太原030024 [3]海安太原科大高端装备及轨道交通技术研发中心,江苏海安226600

出　　处：《现代电子技术》2024年第20期177-186,共10页Modern Electronics Technique

基　　金：国家自然科学基金面上项目(52274389);山西省重点研发计划项目(202102010101003);山西省重点研发计划项目(202202150401010);山西省科技合作交流专项项目(202104041101031);山西省留学人员科技活动择优资助项目(20220028);山西省省筹资助留学回国人员项目(2022-160)。

摘　　要：针对复杂环境中移动机器人路径规划效率低、环境适应能力差等问题,提出一种融合改进A*算法和动态窗口法(DWA)的路径规划算法。首先,在全局规划中采用自适应参数因子和安全半径路径优劣评价函数对冗余节点进行优化,提取关键节点,再使用圆弧处理法对已规划路径进行平滑度优化;然后,采用改进安全距离评价子函数的动态窗口法进行局部规划,提升了移动机器人的避障性能;最后,对融合算法进行仿真和实物实验。结果表明:改进的A^(*)算法在路径长度和转折角度方面均得到优化;融合改进动态窗口法后,移动机器人在复杂环境中能够找到最短无障碍路径,实时避开未知障碍,安全到达目标点位,验证了该算法的有效性和实用性。In allusion to the problems of low efficiency and poor environmental adaptability of mobile robot path planning in complex environment,a path planning algorithm combining improved A*algorithm and dynamic window approach(DWA)is proposed.In the global planning stage,adaptive weighting factor and the safety radius path evaluation function are used to optimize the redundant node and extract the key nodes,and the arc processing method is used to optimize the smoothness of the planned path.The DWA with improved safety distance evaluation subfunction is used for local planning,which can improve the obstacle avoidance performance of the mobile robot.The fusion algorithm is simulated and tested.The results show that the improved A^(*) algorithm is optimized in both of path length and turning angle.After integrating the improved DWA,the mobile robot can find the shortest obstacle-free path in complex environments,dynamically avoid unknown obstacles,and safely reach the target position.These findings validate the effectiveness and practicality of the proposed algorithm.

关 键 词：移动机器人 路径规划 A^(*)算法 动态窗口法 自适应参数 安全距离 动态障碍物 

分 类 号：TN820.4-34[电子电信—信息与通信工程] TP242[自动化与计算机技术—检测技术与自动化装置] TP18[自动化与计算机技术—控制科学与工程]