Unmanned Surface Vessel Route Replanning for Dynamic Collision Avoidance
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Solution Overview
Problem
Current autonomous intelligent technologies for unmanned surface vessels lack effective dynamic collision avoidance methods, particularly in complex marine environments, which is critical for safe navigation and widespread adoption in military and civil applications.
Innovation Solution
A dynamic collision avoidance method based on route replanning is introduced, using a geometric model of a speed barrier region and a moving model with uncertainty, combined with dynamic characteristics and international regulations, to calculate an optimum collision avoidance speed and replan routes, ensuring collision-free navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional collision avoidance methods are used, then the system complexity is low, but the collision avoidance reliability is insufficient in complex marine environments
Solution Approach 1:
The collision avoidance system is segmented into multiple functional modules: risk assessment module that evaluates collision probability, route planning module that generates alternative paths, and speed adjustment module that modifies vessel velocity. This modular segmentation improves reliability by allowing each module to specialize in specific tasks while maintaining overall system manageability despite increased complexity.
Solution Approach 2:
The system performs preliminary risk assessment and route planning before actual collision threats materialize. By continuously evaluating potential collision scenarios in advance and pre-computing alternative routes, the system enhances collision avoidance reliability without requiring complex real-time reactions, thus managing system complexity through proactive rather than reactive operations.
2Productivity
If the unmanned surface vessel maintains high speed, then the navigation efficiency is improved, but the collision risk increases in complex marine environments
Solution Approach 1:
The vessel's speed is made dynamic rather than fixed. The speed adjustment module continuously modifies the vessel's velocity based on real-time risk assessments and environmental conditions. This allows the system to maintain high speeds in safe conditions for navigation efficiency while automatically reducing speed when collision risks are detected, thus balancing productivity and reliability dynamically.
Solution Approach 2:
The system changes the speed parameter adaptively based on environmental parameters such as vessel density, current, and predicted collision probability. By linking the speed parameter to environmental conditions, the system achieves high navigation efficiency in favorable conditions while ensuring collision avoidance reliability when environmental parameters indicate increased risk.
3Reliability
If the collision avoidance system incorporates comprehensive environmental factors and regulations, then the collision avoidance reliability is improved, but the computational complexity increases
Solution Approach 1:
The risk assessment and route planning operations run continuously rather than intermittently. This continuous operation allows the system to maintain up-to-date knowledge of collision risks and available routes, improving reliability by ensuring that the latest environmental information is always considered. The computational complexity is managed by using efficient algorithms that can operate continuously without requiring excessive computational resources at any single moment.
Solution Approach 2:
The system autonomously integrates environmental factors and maritime regulations without requiring external intervention. The route planning module automatically queries environmental data, applies relevant collision avoidance regulations, and generates compliant routes independently. This self-service capability improves reliability by ensuring comprehensive consideration of all factors while managing computational complexity through automated rather than manual processes.
4Adaptability or versatility
If the system performs real-time route replanning, then the adaptability to dynamic environments is improved, but the processing time increases
Solution Approach 1:
Route replanning is performed periodically at optimized intervals rather than continuously or only on-demand. This periodic approach maintains adaptability by regularly updating routes to reflect changing environmental conditions while managing processing time by avoiding unnecessary replanning operations. The system adjusts the replanning frequency based on environmental dynamics, increasing frequency when conditions change rapidly and decreasing it when conditions are stable.
Data Source
AI summary
Disclosed is a dynamic collision avoidance method for an unmanned surface vessel based on route replanning. The method comprises the following steps: acquiring navigation information and pose information of a neighboring ship of an unmanned vessel itself via a vessel-borne sensor; constructing a collision cone between the unmanned vessel and the neighboring ship; introducing a degree of uncertainty with respect to observing movement information of the neighboring ship and applying a layer of soft constraint to the collision cone; applying a speed and a heading limit range of the unmanned vessel; acquiring an ultimate candidate speed set; introducing a cost function to select an optimum collision avoidance speed; and performing an internal recycle of navigation simulation with the optimum collision avoidance speed to obtain a route replanning point for dynamic collision avoidance of the unmanned vessel. According to the present invention, a dynamic collision avoidance strategy of the unmanned surface vessel is output in form of route replanning to meet constraints of international regulations for preventing collisions at sea, and it is well adapted to manipulate and control the unmanned vessel itself, so that a dynamic collision avoidance requirement of the unmanned vessel is met.