摘要
生物激励神经网络算法是一种路径规划算法,在用于全覆盖路径规划时,当前点的局部侧连接点,容易出现相同的神经元活性值。导致规划出的路径长度长、重复率高、转弯次数多,在遇到阻塞点时,容易陷入死区,或规划的逃离路线不是最优路径等问题。针对路径重复率高、转弯次数多等问题,提出移动规则法对机器人的移动方向进行引导,针对机器人陷入死区和无法规划最优逃离路线等问题,结合A*搜寻算法,让机器人能以最优的路径逃离死区。仿真实验表明,该改进方法是有效的。
Biologically Inspired Neural Network is a kind of path planning algorithm.When it is used for complete cover path planning,the local side junction of the current point tends to have the same neuron activity value.As a result,the planned path traversal length is long,the path repetition rate is high,and the number of turns is high,it is easy to get stuck in the dead zone when the blocking point is encountered,and the planned escape route is not optimal.In order to solve the problems of high path repetition rate and many turns,this paper proposes the moving rule method to guide the robot’s moving direction,aiming at the problem of the robot getting stuck in the dead zone and planning the optimal escape route.This paper combines with A*search algorithm to enable the robot to escape the dead zone in the optimal path.Simulation results show that the improved method is effective.
出处
《工业控制计算机》
2019年第12期52-54,共3页
Industrial Control Computer
关键词
移动机器人
遍历路径规划
生物激励神经网络
A*算法
mobile robots
complete cover path planning
biologically inspired neural network
A star algorithm
