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Autonomous ship navigation with an enhanced safety collision avoidance technique.
Hub Ali1, Gang Xiong2, Qu Tianci1
1State Key Laboratory of Multimodal Artificial Intelligence Systems, Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China.
This study introduces safety-enhanced path planning (SPP) for autonomous ships, improving navigation safety by avoiding static and dynamic obstacles. SPP enhances collision avoidance for safer maritime autonomous navigation.
Area of Science:
- Robotics
- Maritime Navigation
- Artificial Intelligence
Background:
- Autonomous ship motion differs from other robots due to unique maneuvering and environmental constraints.
- Existing path planning techniques face challenges with complex static and dynamic obstacles in maritime environments.
Purpose of the Study:
- To present a novel safety-enhanced path planning (SPP) technique for autonomous ships.
- To improve global and local navigation planning, focusing on collision avoidance with static and dynamic obstacles.
Main Methods:
- SPP employs map pre-processing with safety outlines and offset safety lines (OSL) for shore proximity.
- Global path planning uses an enhanced A* multi-directional algorithm with kinematic constraints and a smoothing filter.
- Local navigation utilizes polynomial trajectories and the distance closest point approach (DCPA) for dynamic obstacle avoidance.
Main Results:
- The proposed SPP technique effectively avoids collisions with underwater and offshore obstacles.
- The method successfully navigates complex scenarios involving dynamic obstacles like other ships.
- Simulations in MATLAB demonstrate the effectiveness of SPP compared to existing maritime path planning methods.
Conclusions:
- SPP offers a robust solution for autonomous ship navigation, enhancing safety and efficiency.
- The integration of global and local planning strategies addresses complex maritime challenges.
- This approach contributes to the advancement of safe and reliable autonomous maritime systems.
