Robot Base Coordinate System Calibration Approach based on LM Iterative Algorithm

One major challenge for the robot base coordinate system calibration is how to improve accuracy and robustness of calibration results. The objective of this paper is to propose a pose relationship calibration approach between the multi-degree-of-freedom manipulator and external measuring equipment based on Levenberg-Marquadrdt (LM) algorithm. Specifically, a closed chain configuration is adopted to construct the pose relationship, with the coordinate transformation involving both rotation and translation transformations being formulated mathematically. The calibration solution is then estimated using the LM iteration method through least squares optimization. The proposed calibration approach possesses the advantage of not only reducing the impact of measurement noise on the calibration accuracy greatly, but also avoiding the non-orthogonalization problem encountered when solving for the rotation matrix. Numerical simulations are conducted to assess calibration accuracy and robustness in presence of different levels of noise.