Bolt Detection and Precise Positioning Method for High-Voltage Live Working Robot

A bolt detection and precise positioning method combining neural network and RGB-D camera is proposed for the disassembly and installation task of distribution line insulators, which is used to assist the robot to quickly determine the accurate location of insulator bolts. An improved YOLOv5s network is used to detect the target bolt, after which the bolt end center is predicted by a bolt end center prediction network, and finally the three-dimensions coordinates of the bolt end center are obtained by combining the depth information of the RGB-D camera. The improved YOLOv5s reduces the detection time of a single image by 25.3% and reduces the number of parameters by 22.2%. The average prediction error of the bolt end center prediction network is 8.6 pixels, and the maximum prediction error is 12.4 pixels. Combined with the RGB-D camera for testing, the XY plane positioning error is no more than 4.2mm, and the depth error is no more than 2mm. At experimental site, the method is tested on a live working robot and meets the requirements of practical operations.