一种不确定环境下移动机器人的避障规划算法
A AVOIDING OBSTACLE ALGORITHM OF MOBILE ROBOTUNDER UNCERTAIN ENVIRONMENT
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摘要: 本文提出了在不确定的环境中,移动机器人的一种全局路径规划算法.将全局路径规划分解为局部路径规划的组合.为提高规划的效率,在局部规划中,采用了基于案例的学习方法.以ART-2神经网络实现案例的匹配、学习和扩充,满足了规划的实时性要求,仿真结果说明了本算法的有效性.Abstract: This paper presents a global path-planning algorithm of mobile robot under uncertain environment. Global path planning is divided into local path-planning combinations. In order to enhance planning efficiency,case based learning method is applied. ART-2 neural network is used to realize the cases match,learning and increasing. The need of time is met. The algorithm's efficiency is proved by the simulation results.