基于模糊Elman网络算法的移动机器人路径规划分析

为了调正移动机器人避障线路,建立了基于模糊Elman网络算法的移动机器人路径规划模型,并应用进行Matlab仿真分析。利用现有障碍物的距离信息来实现机器人步长的实施可控制与调节,防止移动机器人在做出准确避障行为之后因为没有设定合适的步长而导致撞上障碍物,以0.5作为机器人的最初运动步长。仿真结果表明,采用模糊Elman网络可以获得比其它两种方法更优的路径规划效果,同时对障碍物进行高效避让,由此实现最优的路径规划。采用模糊Elman网络来构建得到的路径规划算法能够满足规划任务的要求,同时还能够根据机器人处于不同工作空间中的情况进行灵活调整。

Path Planning Analysis of Mobile Robot Based on Fuzzy Elman Network Algorithm

In order to raise the obstacle avoidance line,a path planning model of mobile robot based on fuzzy Elman network algorithm was established,and Matlab simulation analysis was carried out.In this study,distance information of existing obstacles was used to realize controllable and adjustable robot step length,so as to prevent the mobile robot from colliding with obstacles due to not setting appropriate step length after making accurate obstacle avoidance behavior.0.5 is taken as the initial movement step length of the robot.Simulation results show that the fuzzy Elman network can achieve better path planning effect than the other two methods,and at the same time,avoid obstacles efficiently,so as to achieve the optimal path planning.The path planning algorithm constructed by fuzzy Elman network can meet the requirements of planning tasks,and can be flexibly adjusted according to different working spaces of robots.