Relative Positioning Error Minimization of the Dual-Robot System With Kinematic and Base Frame Transformation Parameter Identification

With the increasing use of robots in industry, the use of multi-robot systems, i.e., systems in which multiple robots work together to perform a single task, has become common. In an environment where multiple robots cooperate, the relative position and orientation error between robots must be minimized to improve the accuracy of tasks. In multi-robot systems, accurate kinematic parameters (KP) and base frame transformation (BFT) are required to minimize the position and orientation error between the robots. In this study, a method for KP and BFT identification method that can minimize the position and orientation error of the multi-robot system without using a position measurement device is proposed. A cost function representing the position and orientation error of the multi-robot system was constructed, and the differential evolution algorithm was used to determine the parameters that minimize the cost function. Furthermore, a system consisting of two industrial robots was constructed to verify the effectiveness of the proposed identification method. Experimental results show that the proposed identification method can reduce the relative position error of the dual-robot system by 79% compared to before calibration.