Sea-Aerial Cooperative Path Planning for Underwater Target Tracking
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Solution Overview
Problem
Existing technologies face inefficiencies and inaccuracies in coordinating aerial monitoring devices, unmanned surface vessels (USVs), and unmanned underwater vehicles (UUVs) for accurate underwater target tracking, particularly in complex and unidentified waters.
Innovation Solution
A path planning system and method that involves a collaborative effort between aerial monitoring devices, sea surface monitoring devices, and underwater monitoring devices, where each cluster performs sequential path planning to acquire target position information, construct navigation maps, and transmit obstacle data to optimize tracking, using a particle swarm algorithm for efficient navigation and obstacle avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If USVs rely on surface vessel tracking alone, then the system is simple to operate, but the detection area is small and tracking efficiency is very inefficient
Solution Approach 1:
The system segments the monitoring task into three distinct clusters operating at different levels: aerial monitoring devices for macro-level surveillance, sea surface monitoring devices (USVs) for medium-level coordination and map construction, and underwater monitoring devices (UUVs) for micro-level target tracking. This segmentation allows each component to specialize in specific tasks, dramatically improving overall tracking efficiency while maintaining manageable complexity through modular architecture.
Solution Approach 2:
The system transitions from traditional two-dimensional surface tracking to three-dimensional sea-aerial-underwater cooperative monitoring. By adding the aerial dimension for wide-area detection and the underwater dimension for concealed target tracking, the system expands the detection space from a flat surface to a volumetric environment, significantly increasing the effective detection area and tracking capability.
2Reliability
If USVs navigate in complex waters with timely obstacle avoidance, then the safety is improved, but the path planning process becomes very complicated and the ability to identify the optimal channel is very limited
Solution Approach 1:
The system merges the path planning capabilities of aerial, sea surface, and underwater monitoring devices into a unified collaborative planning framework. The aerial devices provide macro-level route guidance, sea surface devices construct detailed navigation maps with obstacle information, and underwater devices execute precise local path adjustments. This merging allows complex obstacle avoidance to be distributed across multiple agents, reducing the computational burden on any single device while improving overall navigation safety.
Solution Approach 2:
The sea surface monitoring devices perform preliminary actions by constructing water surface navigation maps that include target position information and obstacle data before underwater vehicles begin their tracking missions. This advance preparation of navigation information allows underwater devices to start with pre-planned routes, reducing the complexity of real-time path planning during actual target tracking operations.
3Measurement precision
If UUVs navigate underwater with strong concealment, then the detection capability for underwater targets is improved, but the detection efficiency is low and they are only suitable for short-range channel detection
Solution Approach 1:
The system introduces aerial monitoring devices and sea surface monitoring devices as intermediaries between the target and underwater monitoring devices. Aerial devices perform long-range macro detection to locate targets, sea surface devices construct navigation maps and coordinate intermediate positioning, and underwater devices execute precise final approach and tracking. This intermediary chain allows underwater devices to maintain concealment while achieving high detection accuracy, as they only need to operate in the final short-range phase rather than performing long-range detection alone.
4Productivity
If aerial monitoring devices navigate in the air with wide detection field of vision, then the detection efficiency for surface channel environment is improved, but the ability to track underwater targets directly is weak
Solution Approach 1:
The system segments the detection task by altitude and function: aerial devices handle macro-level surface environment detection and target location, sea surface devices handle medium-level navigation map construction and coordination, and underwater devices handle micro-level precise underwater target tracking. This segmentation allows each device type to optimize for its specific operational domain, with aerial devices maximizing surface detection efficiency while underwater devices achieve precise tracking accuracy in their specialized domain.
Data Source
AI summary
Disclosed is path planning system and method for sea-aerial cooperative underwater target tracking, the method comprises: obtaining the position information of a detection target, carrying out a first path planning along a channel of sea surface monitoring device according to the position information of the detection target; carrying out a second path planning along the channel of sea surface monitoring device according to the water surface navigation map and its own position information, constructing an underwater obstacle map; performing a third path planning according to the underwater obstacle map, and tracking to the position of the detection target to complete the tracking task. This disclosure adopts the collaborative optimization of several clusters to reduce the number of iterations and improve the optimization efficiency, making the path planning reasonable, as a result, the target position can be quickly tracked, and the autonomous collaborative tracking capability is improved.