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A Path Planning Method for Intelligent Ships Based on the Improved Artificial Potential Field Algorithm
Xiao Liu1,2, Hua Deng1, Xingya Zhao2
1Navigation College, Jiangsu Maritime Institute, Nanjing 211100, China.
Sensors (Basel, Switzerland)
|July 28, 2026
Summary
This study introduces an improved artificial potential field (IAPF) method for safer unmanned ship navigation. The IAPF method enhances path smoothness and ensures compliance with collision regulations for dynamic obstacle avoidance.
Area of Science:
- Maritime technology
- Robotics
- Navigation systems
Background:
- Path planning for unmanned ships is crucial for navigation safety.
- Existing methods face challenges with dynamic obstacles and path oscillations.
Purpose of the Study:
- To propose an improved artificial potential field (IAPF) method for enhanced unmanned ship path planning.
- To improve collision avoidance, path smoothness, and adaptability to dynamic scenarios.
Main Methods:
- Introduced a route gravitational force for route recovery.
- Optimized repulsive forces for smoother paths and stability.
- Developed a collision-risk-index-based repulsive force with COLREGs-compliant direction.
- Integrated APF and velocity obstacle algorithms in a time-sequential rolling framework.
Main Results:
- Validated in head-on, crossing, and multiple-obstacle scenarios.
- Achieved minimum passing distances over 1000 m.
- Demonstrated a maximum decision time of 148 ms.
- Generated smooth, COLREGs-compliant paths, avoiding local minima.
Conclusions:
- The proposed IAPF method effectively enhances unmanned ship navigation safety.
- The method adapts to dynamic encounters and satisfies real-time collision-avoidance requirements.
- It offers a robust solution for complex maritime path planning challenges.
