Optimal Measurement Configurations for Gough Platform Calibration

The robustness of robot calibration with respect to sensor noise is sensitive to the manipulator poses used to collect measurement data. The present paper proposes an algorithm based on a constrained optimization method which allows one to choose an set of measurement configurations. It works by selecting iteratively one pose after another inside the workspace, and after a few steps a set of N configurations is obtained which maximizes an index of observability associated to the parameter Jacobian. Our algorithm converges to a set of poses that are localized at the boundary of the articular workspace. Finally, a validation through simulation of a calibration experience shows that selected configurations improve significatively the kinematic parameters identification by dividing by 10 to 15 the noise associated to the results.