轨道交通车辆吹扫机器人智能路径规划研究OACSTPCD

With regard to the path-planning of urban rail transit vehicle purging robot,a full-coverage path-planning algorithm based on CHNN neural network was proposed.The raster map was established by integrating obstacle information and purging information in the robot's moving direction.The whole workspace was divided into different rectangular sub-regions by rectangular decomposition method,and in each sub-region,the full coverage path was obtained based on grid information,and CHNN neural network was used for traversal optimization between sub-regions.The simulation results show that the proposed algorithm can effectively solve the problems of path winding and cleaning dead zone in the process of full coverage path planning of the robot,reduce the path repetition rate and improve the efficiency of the robot,which has a good prospect of engineering application.