Sun, P; Chen, B; Li, W; Liu, Y; Wang, J; Li, J; Zhou, C; (2025) Research on autonomous positioning and adaptive compliant plugging strategies of intelligent charging robots. Computers in Industry , 168 , Article 104287. 10.1016/j.compind.2025.104287.

Text Zhou_Revised Manuscript.pdf - Accepted Version Access restricted to UCL open access staff until 28 March 2027. Download (1MB)

Abstract

With the continuous increase in the number of EVs, intelligent charging has become a critical challenge for power supply infrastructure. Charging robots, equipped with batteries and charging guns, are capable of performing autonomous charging and have emerged as a focal point for research for leading robotics companies. However, during the autonomous charging process, several challenges remain, particularly with regard to the precise positioning of the charging port and the compliance of the manipulator during the plug-in operation. We introduce an autonomous charging strategy for charging robots, tailored for EV charging tasks. The existing two-dimensional image registration technology is extended to three dimensions, and a novel autonomous positioning method based on point cloud information is proposed, enabling real-time attitude estimation of the robot in the vehicle coordinate system. ArUco markers are employed to locate the charging port, and a segmented PID control strategy is proposed to adjust the robot's posture, ensuring it correctly faces the charging port. By integrating fuzzy logic with impedance control, the compliance of the robot's plugging action is enhanced. Furthermore, a charging robot platform is developed, and experimental tests for charging EVs are conducted, demonstrating the feasibility and effectiveness of the proposed approach.

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