UUV Surfacing Path Planning Under Maritime Traffic Risk
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Solution Overview
Problem
Existing UUV navigation systems fail to minimize surfacing in high-risk maritime traffic regions, leading to increased collision risk and navigation uncertainty due to inadequate path planning that does not consider surface vessel traffic and path length.
Innovation Solution
A method and system that uses historical maritime traffic data to create a spatial point process model, identifying safe surfacing locations based on void probability and incorporating INS uncertainty to minimize collision risk and path length.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the UUV surfaces frequently to reset inertial navigation errors, then navigation accuracy is improved, but collision risk with surface vessels increases
Solution Approach 1:
The patent applies local quality by creating a spatially-varying risk map where different geographic locations have different surfacing risk levels. The system identifies low-risk zones within high-traffic regions by analyzing historical AIS data to find areas with lower vessel traffic density, allowing the UUV to surface safely in specific local areas while maintaining overall mission efficiency.
Solution Approach 2:
The system performs preliminary action by pre-computing risk maps and identifying safe surfacing locations before the UUV executes its mission. Historical maritime traffic data is processed in advance to create spatial point process models that predict future traffic patterns, enabling the UUV to plan surfacing events at predetermined safe locations rather than making ad-hoc decisions.
2Object-affected harmful factors
If the UUV surfaces less frequently to reduce collision risk, then collision risk is reduced, but navigation uncertainty increases
Solution Approach 1:
The patent implements feedback by continuously updating the risk assessment based on the UUV's accumulated navigation uncertainty. As the UUV travels between surfacing points, its position uncertainty increases, and this feedback triggers the need to surface sooner rather than later. The system balances the increasing navigation uncertainty against the collision risk of surfacing, dynamically adjusting the optimal surfacing point based on current uncertainty levels.
3Object-affected harmful factors
If the UUV takes longer paths to avoid high traffic regions, then collision risk is reduced, but path length increases
Solution Approach 1:
The system applies dynamics by making the surfacing location selection adaptive rather than static. The risk map and surfacing point selection are dynamically adjusted based on the UUV's current position, accumulated navigation uncertainty, and predicted future traffic patterns. This allows the UUV to optimize its path in real-time, taking longer routes only when necessary to reach safe surfacing zones while minimizing overall mission duration.
4Productivity
If known path-planning methods optimize for efficiency and obstacle avoidance, then mission efficiency is improved, but surfacing safety is not explicitly addressed
Solution Approach 1:
The patent merges multiple path-planning objectives into a unified framework by combining traditional efficiency and obstacle avoidance considerations with explicit surfacing safety requirements. The risk map integration allows the UUV to simultaneously optimize for mission efficiency while ensuring that all surfacing events occur in safe locations, creating a multi-objective path planning system that addresses both productivity and reliability.
Data Source
AI summary
Methods and systems are provided for planning locations to surface an unmanned underwater vehicle (UUV) to reset inertial navigation errors by obtaining a GPS fix. A spatial point process model for historical maritime traffic is used to quantify surfacing risk throughout an operational area. Accumulated navigation uncertainty for each candidate surfacing point of a feasible path is modeled and penalized. This allows autonomy to balance the tradeoff between surfacing risk, navigation performance and pathlength. The planning method results in minimizing the path length the UUV travels and the number of times the UUV surfaces, while satisfying a defined constraint on maximum allowable risk.