Abstract:

A path planning method for rescuing ships was proposed to address the challenges associated with navigating in waters containing numerous obstacles, while ensuring safety and efficiency. The proposed method incorporated the safe distance constraint approach and an improved ant colony algorithm to enhance the applicability of rescue ships in complex environments. The method involved determining the target water area range based on the initial and target positions of the rescue ship, employing a grid-based approach to divide the operational environment into navigable and non-navigable areas, and enforcing a minimum safe distance between the rescue ship and obstacles through safety distance constraints. To further improve the efficiency of the path planning process, the ant colony algorithm was enhanced by optimizing the initial concentration of pheromone, heuristic factor and volatilization factor. Additionally, the expected value heuristic factor and distance heuristic function were introduced to enhance the search purpose and speed of the improved ant colony algorithm. The proposed method was applied to a grid map to plan the path of the rescue ship. The waters near the Zhoushan Islands were selected as the experimental waters, and the Donghai Rescue 102 rescue ship was used as the experimental vessel for verification. Experimental results demonstrate that the proposed path planning method exhibits faster convergence compared to the comparison model, resulting in shorter path lengths, fewer turning points and reduced running time. This method overcomes the challenges of slow convergence speed and local optimization in the path planning of rescue ships, thereby enhancing robustness.

Key words: waters with multiple navigational obstacles, rescue ship, path planning, improved ant colony optimization algorithms, minimum safe distance