融合改进A^(*)算法与DWA算法的机器人实时路径规划  

Real Time Path Planning of Robot by Combing Improved A^(*)Algorithm and Dynamic Window Approach

作　　者：张振 张华良[2,3] 邓永胜[1] 白士宇[4] ZHANG Zhen;ZHANG Hualiang;DENG Yongsheng;BAI Shiyu(School of Mechanical Engineering and Automation,Northeastern University,Shenyang 110819,China;Industrial Control Network and System Laboratory,Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110015,China;Institute of Robotics and Intelligent Manufacturing Innovation,Chinese Academy of Sciences,Shenyang 110000,China;School of Automation and Electrical Engineering,Shenyang Ligong University,Shenyang 110168,China)

机构地区：[1]东北大学机械工程与自动化学院,辽宁沈阳110819 [2]中国科学院沈阳自动化研究所工业控制网络与系统研究室,辽宁沈阳110015 [3]中国科学院机器人与智能制造创新研究院,辽宁沈阳110000 [4]沈阳理工大学自动化与电气工程学院,辽宁沈阳110168

出　　处：《无线电工程》2022年第11期1984-1993,共10页Radio Engineering

基　　金：国家自然科学基金(91648204)。

摘　　要：对于利用传统A^(*)算法规划的路径存在搜索效率低下、节点冗余且不平滑及转弯易靠近障碍物等缺点,基于全向移动机器人提出了一种改进A^(*)算法与动态窗口法(Dynamic Window Approach,DWA)相融合的实时路径规划方法。在传统A^(*)算法的评价函数中加入环境中障碍物信息和父节点到目标点的代价信息,提高路径搜索效率;对当前节点扩展时进行安全检测,优化节点扩展方向;基于安全阈值提取路径关键点,优化搜索路径;将优化后的关键点作为DWA算法的临时目标点,将2种算法融合规划出一条基于全局最优的圆滑曲线路径。实验结果表明,基于融合导航算法规划的路径能安全快速地躲避动态障碍物。Considering the disadvantages of traditional A^(*)algorithm,such as low search efficiency,more redundant nodes and approaching obstacles easily,a real-time path planning method combining improved A*algorithm with Dynamic Window Approach(DWA)is proposed.In the evaluation function of traditional A^(*)algorithm,the obstacle information in the environment and the cost information from the parent node to the target point are added to improve the efficiency of path search.The security threshold value is introduced to detect the safety of the current node when expanding the current node.The search path is optimized by extracting the key points of the search path based on the security threshold value.Finally,the key point is taken as the temporary target point of DWA algorithm,and the two algorithms are fused to plan a smooth curve path based on global optimization.The experimental results show that the path planning based on fusion navigation algorithm can avoid dynamic obstacles safely and quickly.

关 键 词：路径规划 A^(*)算法 DWA算法 安全阈值 融合导航算法 

分 类 号：TP391.7[自动化与计算机技术—计算机应用技术]