Autonomous transfer robot system for commercial vehicles at Ro-Ro terminals

Lin Zhang, Yongkang Xu, Jinge Si, Runjiao Bao, Yichen An, Shoukun Wang*, Junzheng Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

With the rapid development of smart port infrastructure, ports such as Rotterdam and Ningbo have made significant progress in automating container handling. However, traditional manual transfer methods at roll-on/roll-off (Ro-Ro) terminals can no longer meet the growing demands for low-cost, high-efficiency, and standardized operations, driven by increased port throughput, labor shortages, and operational complexity. This study introduces a novel autonomous robot transfer system comprising commercial vehicle transfer robots, a cloud scheduling system, and robotic operation systems. An electric transfer robot with independent four-wheel drive and steering was developed for heavy-duty commercial vehicle transfers, featuring a modular software architecture with cloud-based scheduling and planning, and robot perception and control modules. To support multi-robot cooperative transfer in open yard environments, we propose a task allocation algorithm based on an adaptive particle swarm genetic algorithm and an enhanced conflict-aware path planning method under kinematic constraints. For precise and safe vehicle pick-up and drop-off under complex conditions, a multi-stage fusion algorithm is introduced for vehicle body localization, orientation estimation, and wheel alignment, together with a predictive docking control algorithm using virtual transfer vehicle tracking. The system was deployed at the Ro-Ro terminal of Yantai Port, Shandong Province, China, where targeted experiments were conducted. Results demonstrate centimeter-level accuracy in vehicle handling, a transfer efficiency of 91 % compared to manual operations, and the operating time reaches 2–3 times. These findings validate the effectiveness and practical value of the proposed robot system and its key technologies.

Original languageEnglish
Article number128347
JournalExpert Systems with Applications
Volume289
DOIs
Publication statusPublished - 15 Sept 2025
Externally publishedYes

Keywords

  • Autonomous docking
  • Autonomous transfer of commercial vehicles
  • Robot system
  • Scheduling planning
  • Straddle-structured robots

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