On task-oriented criteria for configurations selection in robot calibration

This paper studies different criteria for selecting configurations for the task of calibrating a robotic system. Given an automatic and self-contained procedure which allows the robot to calibrate itself without the need of external tools, we are interested in how to select the set of configurations that maximize calibration accuracy while minimizing calibration time. We experiment with the active calibration of a multi-sensorial humanoid´s upper body and report that determinant-based criteria should be preferred when a greedy selection is used. In addition to criteria comparison, we further propose a new criterion for configuration selection. Its novelty stems from a direct treatment of the robot´s end-effector tool variance. This is contrary to previous approaches which target the variance indirectly via calibration parameters. Our proposed objective function is derived as a compact formulation from the mean error of the robot´s end-effector tool from which its variance can be computed using traditional criteria known from the theory of optimal experimental design (e.g. A-optimality).