Calibration of Collaborative Robots Based on Position Information and Local Product of Exponentials. (4th March 2022)

• Record Type: Journal Article
• Authors: Gao, Guanbin; Gao, Yangtao; Liu, Fei; Na, Jing
• Other Names: Jin Xue-bo Academic Editor.
• Is Part Of: Journal of sensors. Volume 2022(2022)
• Publication Date: 2022-03-04
• Subjects: Detectors -- Periodicals; 681.205
• DOI: 10.1155/2022/2815164
• Languages: English
• ISSNs: 1687-725X

Abstract

Abstract : To improve the positioning accuracy of collaborative robots, a novel modeling and calibration method for collaborative robots is proposed based on position information and modified local product of exponentials (LPoE). The kinematic error model is derived from the kinematic model through differential transformation. To solve the problem of the high redundancy and complexity of the error model that is difficult to identify, the errors of the kinematic parameters are all transferred to the initial position and posture matrix of the local coordinate system, which simplifies the error model and improves the speed and accuracy of the identification calculation. However, the simplified error model still requires posture data which are very difficult to acquire in practice. For this reason, the position error is separated from the kinematic model, and an error model based on position data is established. Then, a kinematic calibration method of the collaborative robot based on position data is proposed, which simplifies the measurement process and improves the efficiency of calibration. The effectiveness of the method is verified by simulations and experiments on a six degree-of-freedom collaborative robot.