Highly-Accurate Robot Calibration Based on Plane Constraint via Integrating Square-Root Cubature Kalman filter and Levenberg-Marquardt Algorithm

In the field of modern industrial manufacturing, industrial robots are indispensable intelligent automatic mechanical equipment for advanced industrial production. However, due to long-term mechanical wear and structural deformation, the absolute positioning accuracy is low, which greatly hinders the development of the manufacturing industry. Calibrating the kinematic parameters of the robot is an effective way to address it. However, the main measuring equipment such as laser trackers and coordinate measuring machines are expensive and need special personnel to operate. Additionally, in the measurement process, due to the influence of extensive environmental factors, measurement noises are generated affecting the calibration accuracy of the robot. Based on these, we have done the following work: a) developing a robot calibration method based on plane constraint to simplify measurement steps; b) employing square-root culture Kalman filter (SCKF) algorithm for reducing the influence of measurement noises; c) proposing a novel algorithm for identifying kinematic parameters based on SCKF algorithm and Levenberg-Marquardt (LM) algorithm to achieve the high calibration accuracy; d) adopting the dial indicator as the measuring equipment for slashing costs. Enough experiments verify the effectiveness of the proposed calibration algorithm and experimental platform.