Unmanned tugboat path planning in obstacle-cluttered environments with enhanced probabilistic road map method
Haibin Wang, Rui Zhao, Xie Wenbo, Zhang Jingyan, Mingyang Li · Ships and Offshore Structures · 2025
This paper addresses the path planning problem for unmanned tugboats navigating toward a designated towing point in an obstacle-rich environment. We propose a path planning strategy based on an enhanced probabilistic road map (EPRM) method, which integrates Bezier curves and the A* algorithm. The initial towing point allocation for the unmanned tugboat is determined using a predefined towing scheme. The optimal path is then computed using the Hungarian algorithm, considering safety domain constraints to minimize total path distance and optimize energy consumption. Furthermore, a novel probability factor interval was introduced as a constraint within the existing PRM framework, effectively reducing the likelihood of generating invalid paths in the presence of static obstacles. Finally, the effectiveness and practicality of the proposed path planning strategy are validated through simulation experiments. The results provide valuable insights for engineering applications, particularly in navigating obstacle-laden marine environments.