The Control Strategy for Vehicle Transfer Robots in RO/RO Terminal Environments

Abstract

In the labor-intensive Roll-On/Roll-Off (RO/RO) terminal environment, research on vehicle transport robots with mobility, stability, and reliability is receiving increasing attention. This paper presents a novel control framework for a Straddle-Type Dual-Body vehicle transfer robot. Initially, fine segmentation and processing of point clouds from different areas of the robot are performed, switching perception strategies for different areas based on event triggers. For target pose estimation, a traversal-based point cloud matrix fitting algorithm is designed. Additionally, for loading and unloading operations, a docking controller based on real-time target detection is developed to ensure minimal lateral and angular errors during target docking. Finally, the proposed control framework is validated through operations of the vehicle transfer robot in outdoor RO/RO terminal yards. Experimental results indicate that the average docking error remains within 3cm, with a 6.5% reduction in docking time under the same conditions. The docking precision and stability performance of the vehicle transfer robot surpass traditional methods, demonstrating satisfactory performance.