基于改进A^(*)算法和DWA融合的机器人路径规划研究  

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

作　　者：赵久强 赵庭辉 冯毅萍[1] 曹峥[1] 仲玉芳[1] ZHAO Jiuqiang;ZHAO Tinghui;FENG Yiping;CAO Zheng;ZHONG Yufang(College of Control Science and Engineering,Zhejiang University,Hangzhou 310027,China)

机构地区：[1]浙江大学控制科学与工程学院,浙江杭州310027

出　　处：《实验技术与管理》2023年第3期87-92,共6页Experimental Technology and Management

基　　金：2021年浙江大学实验技术研究项目(SYB202119);教育部产学合作协同育人项目(201902262041)。

摘　　要：传统的A^(*)算法存在未考虑移动机器人实际行驶时间,路径规划转折点多,且无法处理复杂环境中出现随机障碍物等问题。针对上述问题,提出了一种将移动机器人行驶时间作为代价且能根据障碍物信息调整启发函数权重的改进A^(*)算法,有效地减少了路径规划时的转弯次数和转弯角度。使用Floyd算法进一步进行优化,删除冗余转折点,减少转弯次数以及提升路径的平滑度。改进后的A^(*)算法规划的路径相较于传统A^(*)算法平均转弯次数减少49.0%,转弯角度减少50.8%,路径长度减少1.7%。融合DWA算法后,能够在改进A^(*)算法规划的全局路径基础上进行局部路径修正,实现动态避障,最后经过仿真验证了算法的可行性和有效性。The traditional A^(*) algorithm does not take into account the actual travel time of the mobile robot,there are many turning points in path planning,and it is unable deal with random obstacles in complex environments.Aiming at the above problems,an improved A^(*)algorithm that takes the travel time of the mobile robot as the cost and can adjust the weight of the heuristic function according to the obstacle information is proposed,which effectively reduces the number of turns and the turning angle in path planning.Further optimization is carried out using the Floyd algorithm to remove redundant turning points,reduce the number of turns and improve the smoothness of the path.Compared with the traditional A^(*)algorithm,the path planned by the improved A^(*)algorithm reduces the average number of turns by 49.0%,the turning angle by 50.8%,and the path length by 1.7%.After integrating the DWA algorithm,the local path correction can be performed on the basis of the global path planned by the improved A^(*)algorithm to achieve dynamic obstacle avoidance.Finally,the feasibility and effectiveness of the algorithm are verified by simulation.

关 键 词：路径规划 改进A^(*)算法 动态窗口法 动态避障 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]