Research on Energy-Efficient Path Planning for Tugboat Based on Ant Colony Optimization Integrated with Potential Field Maps

To address the problems of high energy consumption and excessive navigation time in autonomous tugboat operations during cross-regional missions, an Ant Colony Optimization algorithm integrated with Potential Field Maps (PFM-ACO) is proposed. The proposed method is capable of planning routes that satisfy navigation time constraints, thereby improving navigation efficiency while minimizing voyage energy consumption. Specifically, time-based and energy-consumption-based potential field maps are constructed using ocean current data. The initial pheromone matrix and heuristic function are further redesigned to enhance target-oriented guidance. In addition, an adaptive heuristic factor based on a goal-biased strategy is introduced to strengthen the global search capability of the algorithm. Finally, the proposed PFM-ACO algorithm is compared with the A*, A*-DCE and NDACA algorithms. Experimental results demonstrate that, under navigation time constraints, the paths generated by PFM-ACO achieve both the lowest energy consumption and the highest path smoothness. Overall, the proposed algorithm outperforms the comparative methods, indicating its effectiveness and superiority in energy-efficient path planning for tugboat navigation.