New self-calibration approach to space robots based on hand-eye vision

Abstract

To overcome the influence of on-orbit extreme temperature environment on the tool pose (position and orientation) accuracy of a space robot, a new self-calibration method based on a measurement camera (hand-eye vision) attached to its end-effector was presented. Using the relative pose errors between the two adjacent calibration positions of the space robot, the cost function of the calibration was built, which was different from the conventional calibration method. The particle swarm optimization algorithm (PSO) was used to optimize the function to realize the geometrical parameter identification of the space robot. The above calibration method was carried out through self-calibration simulation of a six-DOF space robot whose end-effector was equipped with hand-eye vision. The results showed that after calibration there was a significant improvement of tool pose accuracy in a set of independent reference positions, which verified the feasibility of the method. At the same time, because it was unnecessary for this method to know the transformation matrix from the robot base to the calibration plate, it reduced the complexity of calibration model and shortened the error propagation chain, which benefited to improve the calibration accuracy.

Keywords

space robot / self-calibration / cost function / hand-eye vision / particle swarm optimization algorithm

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