ICP registration with SHOT descriptor for arresters point clouds

Abstract

Abstract Arresters are one of the critical components of the power system. However, due to the arrester’s regular and uniform umbrella skirt, both traditional manual detection methods and existing computer vision approaches exhibit limitations in accuracy and efficiency. This paper proposes an automatic, robust, efficient arrester point cloud registration method to address this problem. First, a robotic arm maneuvers a depth camera to capture point cloud data from various perspectives. Then, the fast global registration point cloud coarse registration method based on the signature of histograms of orientations descriptor to produce preliminary registration results. This result is ultimately used as the initial value of the improved iterative closest point algorithm to refine the registration further. Experimental results on various data sets collected from arrester and public data sets show that the algorithm’s root mean square error is less than 0.1 mm, meeting the requirements of the engineering application of arrester detection.