机器人避障路径规划优化控制仿真

摘要

研究动态环境下机器人的避障路径规划问题.为了解决A*避障规划存在搜索时间长、动态环境下的不适应性问题,提出了一种改进的跳点搜索路径模糊控制方法.从起始点的水平、垂直和对角方向同时进行跳点搜索,采用二叉堆优化open表,不断进行跳点搜索和添加,直至搜索到目标节点.将搜索到的路径节点作为子目标点与模糊控制结合,对局部未知障碍物进行检测避障,实现逐点地向目标点运动,完成全局路径规划.仿真结果验证了算法的有效性和可靠性,路径点搜索速度得到提高,在动态环境下能有效地避开突现的未知障碍物,避免了机器人穿越障碍物移动和路径重规划.%To solve the problems of long search time and inadaptability in dynamic environments for A * obstacle avoidance planning,a path planning algorithm is proposed based on the combination of improved jump point search and fuzzy control.The search begins from the horizontal,vertical and diagonal directions of the start point for jump point at the same time,using binary heap to optimize the open table.Keeping on jump point search and addition until search to the goal point.The path nodes are combined with fuzzy control as sub-goals to detect and avoid obstacles,achieving point to point motion and completing the global path planning.The simulation results verify the validity and reliability of the algorithm.The path search speed is improved,and it can effectively avoid the emergence of unknown obstacles in dynamic environments,avoid crossing obstacles and path replanning.