Research on Multi-Target Path Planning for UUV Based on Estimated Path Cost

The precision and efficiency of multi-target path planning are crucial factors influencing the performance anti-mine operations using unmanned underwater vehicles (UUVs). Addressing inadequacies in computation time solution quality present existing algorithms, this study proposes a novel cost estimation strategy based on neural networks. This swiftly generates an accurate matrix, ensuring attainment high-quality traversal orders when utilized as input for traveling salesman problem, thereby yielding globally optimal path. Simulation experiments demonstrate that while maintaining solutions, proposed significantly enhances computational algorithm. Furthermore, practical application effectiveness algorithm have been demonstrated through actual UUV prototype experiment lake environment.