摘要
为解决传统A^(*)算法和传统动态窗口法(Dynamic window approach,DWA)在移动机器人路径规划中存在的问题,提出一种改进A^(*)算法和改进DWA相结合的动态路径规划方法。首先,采用16邻域16方向的路径搜索方式扩大路径搜索视野,减少节点访问量和转角度数;其次,对启发函数进行优化,增强路径搜索的目的性;接着,采用冗余点删除策略,减少转折点数目,路径平滑度进一步提高,再使用B样条曲线对路径拐角进行处理,得到的路径较为平滑;然后,在DWA的评价函数中对障碍物进行分类并区别对待以及添加速度自适应因子,能够提高避障灵敏度;最后,通过与其他算法进行三部分仿真实验以及优先级策略仿真实验,验证改进A^(*)算法的有效性和融合方法避障的优越性。
To solve the problems of the traditional A^(*)algorithm and the traditional dynamic window approach(DWA)in mobile robot path planning,a dynamic path planning method combining the improved A^(*)algorithm and the improved DWA is proposed.First,the 16‑neighborhood and 16‑direction path search method is adopted to expand the path search field and reduce the number of the nodes accessed and the turning angles.Second,the heuristic function is optimized to enhance the purpose of the path search.Next,the redundant point deletion strategy is adopted to reduce the number of the turning points and further improve the smoothness of the path.Third,the path corner is processed by the B-spline curve,and the path is relatively smooth.Then,the sensitivity of obstacle avoidance can be improved by classifying and treating obstacles differently and adding the speed adaptive factor in the evaluation function of DWA.Finally,through three parts of the simulation experiments with the other algorithms,and the priority strategy simulation experiments,the effectiveness of the improved A^(*)algorithm and the superiority of the fusion method in obstacle avoidance are verified.
作者
齐款款
李二超
毛玉燕
QI Kuankuan;LI Erchao;MAO Yuyan(College of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou 730050,China)
出处
《数据采集与处理》
CSCD
北大核心
2023年第2期451-467,共17页
Journal of Data Acquisition and Processing
基金
甘肃省教育厅项目(2021CXZX-507)
国家自然科学基金(62063019,61763026)
甘肃省自然科学基金(20JR10RA152)。
