A virtual reality inspection method for main equipment of converter station based on slam technology and posi-tion fusion is proposed to improve the inspection path planning effect.Based on the virtual reality inspection framework of the main equipment of the converter station of the intelligent robot,the IMU carried by the intelligent robot is used to collect its acceleration and angular rate data.After the fuzzy adaptive PI algorithm compensates the heading angle error of the intel-ligent robot,the position and attitude estimation results are obtained.The camera and lidar sensor are used to collect the en-vironmental image data of the converter station,and the RGB-Dslam method based on binocular structured light is used to process it to obtain the camera pose estimation.The extended Kalman filter is used to realize the fusion positioning of intelli-gent robots,determine their position points and direction angles at all times,and after synchronizing them to the virtual space,draw the environment map of the converter station.The heuristic path search method is used to determine the optimal inspection path,and the inspection and obstacle avoidance strategy is formulated according to the minimum cost function,so as to realize the obstacle avoidance inspection path planning of the virtual space of the main equipment of the converter sta-tion.The experimental results show that the method can compensate the robot's heading angle error.The optimal inspection route of the main equipment of the converter station is planned,and the error is only centimeter level.
slam technologyposition fusionmain equipment of converter stationvirtual realityfuzzy adaptive PIex-tended Kalman filter
万方数据
维普
