Eye-to-hand calibration of an industrial robotic arm with structured light 3D cameras

Abstract

Computer vision is gaining more and more importance in the world of industrial robotics, since it is necessary to carry out increasingly precise and autonomous tasks, which is why a more exact positioning of the robot is needed. This requires the support of a vision system that is the one that gives the robot precision in its pose, calibrating said system with respect to the robot. This work presents a simple methodology to approach this form of calibration, called hand-eye, using a structured light 3D camera that obtains information from the real world and a six-axis industrial robotic arm. The method uses the RANSAC algorithm for the determination of the planes, which represents a notable reduction in errors, since the coordinates of the points sought come from planes adjusted to thousands of points. This allows the system to always have the ability to obtain a transformation matrix from the coordinates of the camera to the base of the robot. In addition, the proposed method is ideal for making a precision comparison between cameras, due to its simplicity and speed of use. In this study, the resulting error analysis was performed using two different 3D cameras: a basic one (Kinect 360) and an industrial one (Zivid ONE + M).