基于多行为的移动机器人路径规划

机器人由当前点向目标点运动的过程中,所处环境经常为动态变化且未知的,这使得传统的路径规划算法对于移动机器人避障过程很难建立精确的数学模型.为此,针对环境信息完全未知的情况,为移动机器人设计一种基于模糊控制思想的多行为局部路径规划方法.该方法通过对各种行为之间进行适时合理的切换,以保证机器人安全迅速地躲避静态和动态障碍物,并利用改进的人工势场法实现对变速目标点的追踪.对于模糊避障中常见的U型陷阱问题,提出一种边界追踪的陷阱逃脱策略,使得机器人成功解除死锁状态.另外,设计一个速度模糊控制器,实现了机器人的智能行驶.最后,基于Matlab平台的仿真结果验证了所提出算法的有效性和实时性,与A*势场法的对比结果更突出了该算法的可行性.

Mobile robot path planning based on multi-behaviours

When the robot moves from the current point to the target point, the environment is often dynamic and unknown, which makes it difficult for the traditional path planning algorithm to establish an accurate mathematical model for the mobile robot obstacle avoidance process. Aiming at the situation that the environment information is completely unknown, a multi-behaviour local path planning method based on fuzzy control is designed for the mobile robot. The method ensures that the robot avoids static and dynamic obstacles safely and promptly by switching various behaviours timely and reasonably. The improved artificial potential field method is used to track the variable speed target point. To deal with the common obstacle avoidance U-trap problem, a trap escaping strategy of the boundary tracking is proposed, which makes the robot successfully lift the deadlock state. In addition, a speed fuzzy controller is designed to realize the robot''s intelligent driving. Finally, the simulation results based on the Matlab platform verify the effectiveness and real-time performance of the proposed algorithm. Compared with the A* potential field method, the proposed algorithm is more feasible.