一种基于混合学习策略的移动机器人路径规划方法

针对未知环境下移动机器人路径规划问题,以操作条件反射学习机制为基础,根据模糊推理系统和学习自动机的原理,提出一种应用于移动机器人导航的混合学习策略.运用仿生的自组织学习方法,通过不断与外界未知环境交互从而使机器人具有自学习和自适应的功能.仿真结果表明,该方法能使机器人学会避障和目标导航任务,与传统的人工势场法相比,能有效地克服局部极小和振荡情况.

Path planning method for mobile robot based on a hybrid learning approach

Aim to solve the path planning problem of mobile robot in the unknown environment, a hybrid learning approach
is proposed for the robot navigation based on the operant conditioning theory and the principle of fuzzy inference system and
learning automata. The robot is endowed with the capabilities of self-learning and self-adapting with unknown environment
by using a bionic self-organizing method. Simulation results show that, compared with the method of artifical potential field,
the proposed method can make the robot learn the ability of obstacle avoidance and goal seeking without being stuck in local
minima and oscillation.