Kinematic Self-Calibration Method for Dual-Manipulators Based on Optical Axis Constraint

Abstract

Kinematic parameters’ calibration is a powerful method to improve the accuracy of the robot. This paper proposes an effective kinematic self-calibration method for dual-manipulators based on virtual constraints to estimate the actual kinematic parameters of the robots. This method only needs a camera mounted on one robot end-effector (EE) and a calibration target attached to another robot EE. First, a new calibration error model based on the straight line constraint is established to formulate the positions’ misalignment error with the kinematic parameters’ error. Then, the particle swarm optimization algorithm is developed to generate the optimal calibration poses of the robots under the constraints, which are used to ensure the poses feasible and the measurement errors acceptable. Finally, the kinematic parameter errors are identified with the Levenberg–Marquardt algorithm. The experiments of the kinematic parameters’ calibration with the dual-manipulators system are designed. The experimental results showed that the high positional accuracy of both robots can be achieved.