HA-RRT: A heuristic and adaptive RRT algorithm for ship path planning

With the continuous development of maritime transportation, it is increasingly vital for ships to navigate quickly and safely. The Rapid Exploration Random Tree (RRT) algorithm currently used in ship path planning still has many disadvantages, such as slow convergence speed, low path quality, and many turning points. To address the above issues, we design a HA-RRT algorithm that can heuristically and adaptively plan navigation paths. Firstly, we propose to combine the heuristic search scheme with the RRT algorithm to improve the convergence speed. In addition, we introduce a dynamic factor alpha into this heuristic search scheme and enhance the flexibility and adaptability of the algorithm through this dynamic factor. Then, we introduce adaptive tuning strategies to adapt to complex marine environments. Next, we optimize the trajectory using a third-order Bezier curve data smoothing algorithm. Finally, we compare the performance and effectiveness of the HA-RRT algorithm with other algorithms in the same ocean environment. The final experimental results demonstrate that our proposed HA-RRT algorithm is more adaptable and efficient than others. The resulting smooth path ensures a more reasonable turning radius, making the ship navigation safer and more stable.