摘要
在动态未知环境下对机器人进行路径规划,传统A*算法可能出现碰撞或者路径规划失败问题。为了满足移动机器人全局路径规划最优和实时避障的需求,提出一种改进A*算法与Morphin搜索树算法相结合的动态路径规划方法。首先通过改进A*算法减少路径规划过程中关键节点的选取,在规划出一条全局较优路径的同时对路径平滑处理。然后基于移动机器人传感器采集的局部信息,利用Morphin搜索树算法对全局路径进行动态的局部规划,确保更好的全局路径的基础上,实时避开障碍物行驶到目标点。MATLAB仿真实验结果表明,提出的动态路径规划方法在时间和路径上得到提升,在优化全局路径规划的基础上修正局部路径,实现动态避障提高机器人达到目标点的效率。
The traditional A*algorithm can experience collisions or path-planning failure in dynamic complicated environments.To meet global optimal requirements and achieve real-time obstacle avoidance in mobile-robot path planning,we propose a novel method that fuses an improved A*algorithm with a Morphin search tree algorithm.First,we improved the A*algorithm by reducing the selection of key nodes in the path-planning process and performing path smoothing when planning the global optimal path.Then,based on the local information obtained by the mobile-robot sensor,the Morphin search tree algorithm is used to dynamically localize the global path.Thus,obstacles are avoided both by ensuring a better global path and by real-time obstacle avoidance as the robot moves to the target.The MATLAB simulation results show that the proposed dynamic path-planning method improves both the time and path.The local path is corrected via the optimized global-path planning,dynamic obstacle avoidance,and the improved efficiency with which the robot reaches the target point.
作者
成怡
肖宏图
CHENG Yi;XIAO Hongtu(School of Electrical Engineering and Automation,University of Tianjin Polytechnic,Tianjin 300387,China)
出处
《智能系统学报》
CSCD
北大核心
2020年第3期546-552,共7页
CAAI Transactions on Intelligent Systems
基金
天津市自然科学基金项目(18JCYBJC88400,18JCYBJC88300)
天津市高等学校创新团队培养计划项目(TD13-5036).
