A Simple Real-Time Method For Calibrating A Camera Mounted On A Robot For Three Dimensional Machine Vision

摘要

For a vision system to infer 3D object features (e.g., point features or line features) from 2D image features and to predict 2D image features from 3D object features, the transformation between the 2D image coordinate system and the 3D object coordinate system must be known. Determining this transformation is called (geometric) camera calibration. This 2D-3D transformation varies when the camera is moved by a robot. This paper presents a simple two-stage (off-line stage and on-line stage) method for calibrating a camera mounted on a robot. The off-line stage includes off-line calibration of the camera, the robot, and the robot-camera (or hand-eye) relation. The on-line stage can be divided into an initial calculation step and a re-calibration step. The initial step is computationally simple since it only involves one or two matrix multiplications of dimension less than four. The derived calibration accuracy from this initial step depends on the accuracy of the off-line camera/robot calibration. Experimental results show that the calibration accuracy is better than "1 part in 1000" without special robot calibration. Higher accuracy can be obtained with more sophisticated robot calibration, or with the re-calibration step using the extended Kalman filtering techniques. Some new insights to the conventional camera calibration methods are also given.