不确定动态环境下移动机器人的完全遍历路径规划

基于生物激励神经网络、滚动窗口和启发式搜索，提出了一种新的完全遍历路径规划方法．该方法用Grossberg的生物神经网络实现移动机器人的局部环境建模，将滚动窗口的概念引入到局部路径规划，由启发式算法决定滚动窗口内的局域路径规划目标．该方法能在不确定动态环境中有效地实现机器人自主避障的完全遍历路径规划．仿真研究证明了该方法的可用性和有效性．

A Complete Coverage Path Planning Method for Mobile Robots in Uncertain Dynamic Environments

A new approach to complete coverage path planning for mobile robots,which integrates biologically inspired neural network,rolling window and heuristic searching,is presented.The local environment of mobile robot is modeled with Grossberg's biological neural networks.The concept of rolling window is introduced into local path planning,and the local path planning goal in the rolling window can be determined by heuristic searching methods.The complete coverage path planning with dynamic obstacle avoidance for mobile robots can be efficiently implemented by the proposed method in uncertain dynamic environments.The effectiveness and feasiblity of the proposed method are illustrated by simulations.