In this paper, we rst review research results of camera self-calibration achieved in photogrammetry, robotics and computer vision. Then we propose a method for selfcalibration of robotic hand cameras by means of active motion. Through tracking a set of world points of unknown coordinates during robot motion, the internal parameters of the cameras (including distortions), the mounting parameters as well as the coordinates of the world points are estimated. The approach is fully autonomous, in that no initial guesses of the unknown parameters are to be provided from the outside by humans for the solution of a set of nonlinear equations. Su cient conditions for a unique solution are derived in terms of controlled motion sequences. Methods to improve accuracy and robustness are proposed by means of best model identi cation and motion planning. Experimental results in both a simulated and a real environments are reported.
Wei et al. REF proposed a method of calibrating robotic hand cameras by active motion, which does not require metric control points nor the initial values of the unknowns in non-linear equations.
Active Self-calibration of Robotic Eyes and Hand-eye Relationships with Model Identification
IEEE Trans. Robotics and Automation
IEEE Trans. Robotics and Automation
Computer Science Mathematics