轨道交通车辆吹扫机器人智能路径规划研究

Research on Intelligent Path Planning of Purging Robot for Rail Vehicles

针对城市轨道交通车辆吹扫机器人路径规划问题,提出一种基于CHNN神经网络的全覆盖路径规划算法,综合机器人运行方向上障碍物信息与吹扫信息建立栅格地图,采用矩形分解法将整个工作空间划分为不同矩形子区域,在各子区域内基于栅格信息分别得到全覆盖路径,各子区域之间则采用CHNN神经网络进行遍历寻优。仿真结果表明:所提出的算法可以有效解决吹扫机器人全覆盖路径规划过程中的路径缠绕和清洁死区问题,降低了路径重复率,提高机器人吹扫效率,具有较好的工程应用前景。

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.