Robot Assisted 3D Point Cloud Object Registration

Abstract

In this paper we describe a method for registration of 3D point clouds that represent objects of interest. A stereovision system is used to capture point clouds of a static environment, robot arm and an unknown object. By moving the robot arm in the environment the proposed system defines known occupied zones and is able to identify the robot arm. In order to identify a complete point cloud presentation of the robot gripper it is rotated in front of a stereovision camera and its geometry is captured from different angles. Iterative closest point algorithm is used to determine a rigid transformation between every new robot pose so the original point cloud can be appended with the transformed one. When the robot is holding a new object the registration procedure is repeated and known elements (environment, robot arm and gripper) are removed so that the object can be identified.