基于模糊Elman网络的避障机器人全局路径规划  

Global Path Planning of Obstacle Avoidance Robot Based on Fuzzy Elman Network

作　　者：孟祥伟 Meng Xiangwei(College of Mechanical and Electrical Engineering,Hebi Polytechnic,Hebi Henan 458030,China)

机构地区：[1]鹤壁职业技术学院机电工程学院,河南鹤壁458030

出　　处：《现代工业经济和信息化》2024年第9期130-131,134,共3页Modern Industrial Economy and Informationization

摘　　要：为了进一步提高避障效率,设计了一种基于模糊Elman网络的避障机器人全局路径规划方法,并开展增加临时障碍物时路径规划仿真分析。研究结果表明,模糊Elman网络路径规划方法相比于Elman神经网络模型成功概率更高,平均路径长度及最优路径长度依次减少7.8%和4.2%,能最有效的避让障碍物。通过模糊Elman网络对障碍物的避障目的可更好实现,针对工作空间环境不同机器人还可灵活完成调整。该研究有助于提高机器人在众多工业领域的应用效率,具有很高的拓宽价值。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.

关 键 词：避障机器人 模糊Elman网络 全局规划 最优路径 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]