Global Path Planning of Obstacle Avoidance Robot Based on Fuzzy Elman Network
Obstacle avoidance robots have been widely used in many industrial fields.In order to further improve the obstacle avoidance efficiency,a global path planning method of obstacle avoidance robot based on fuzzy Elman network is designed,and the path planning simulation analysis is carried out when temporary obstacles are added.The results show that compared with the Elman neural network model,the fuzzy Elman network path planning method has a higher probability of success,and the average path length and the optimal path length are reduced by 7.8％and 4.2％respectively,which can effectively avoid obstacles.The obstacle avoidance through fuzzy Elman network can be better realized,and the robot can flexibly adjust according to different working space environment.This research is helpful to improve the application efficiency of robots in many industrial fields and has high broadening value.
万方数据
维普
