Path Planning of Surface vessel based on improved IRRT* algorithm
• Introducing a two-way exploration mechanism to improve search efficiency • Dynamic KD tree optimizes nearest neighbor search • Adaptive B-spline curve smooth path • Comprehensive improvements, taking into account the characteristics of ship motion This study addresses the limitations of traditional path planning algorithms, such as lengthy path planning, prolonged planning time, and non-compliance with the kinematic laws of surface vessels, an improved IRRT* algorithm suitable for Surface vessel path planning in complex water environment is proposed to make it conform to the kinematic characteristics of Surface vessels. By introducing two-way exploration mechanism, dynamic KD-Tree nearest neighbor search and adaptive B-spline curve optimization. It effectively improves the efficiency and quality of path planning. The bi-directional exploration mechanism speeds up the search speed, KD-Tree optimizes the nearest neighbor search, and B-spline curve optimization ensures the smoothness of the path and the ability to avoid obstacles. Simulation experiments and actual sea area tests show that compared with the existing algorithms, the average Computation time of the improved algorithm is reduced by 71%, 69% and 79% respectively, and the planned path length is reduced by 28%, 28% and 1%, respectively. the number of search nodes is reduced by 88%, 86% and 81%. The number of path turns has been reduced by 86%, 90% and 90% respectively, which provides an effective solution for the path planning of Surface vessels in complex water environment.
Authors
- Peng Hao (ORCID: https://orcid.org/0000-0001-5864-7358)
- Xin Wang (ORCID: https://orcid.org/0000-0003-3352-6829)
- Hao Yu (ORCID: https://orcid.org/0000-0001-8447-2272)
Institutions
- Jimei University (CN)
- Shanghai Shipbuilding Technology Research Institute (CN)
- Fujian Institute of Oceanography (CN)
Publication Details
- Journal
- Results in Engineering
- Published
- 2025-05-18
- DOI
- https://doi.org/10.1016/j.rineng.2025.105325
- Citations
- 3
- Primary Topic
- Robotic Path Planning Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 3.83
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Fujian Province