论文部分内容阅读
研究多移动机器人的运动规划问题．针对机器人模型未知或不精确以及环境的动态变化，提出一种自学习模糊控制器（ＦＬＣ）来进行准确的速度跟踪．首先通过神经网络的学习训练构造ＦＬＣ，再由再励学习算法来在线调节ＦＬＣ的输出，以校正机器人运动状态，实现安全协调避撞
Research on motion planning of multi-mobile robots. Aiming at the unknown or inaccurate robot model and the dynamic change of the environment, a self-learning fuzzy controller (FLC) is proposed to perform accurate velocity tracking. Firstly, the FLC is constructed by learning and training of neural network, and the output of FLC is adjusted online by re-learning algorithm to correct the robot’s movement state and achieve safety coordination and collision avoidance