Multi-USV Target Assignment With Constraint-Aware Route Planning
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Solution Overview
Problem
Current target assignment and route planning systems for multi-agent unmanned surface vehicles do not adequately consider the unique maneuverability and hydrodynamic constraints of USVs, nor do they effectively handle cooperative obstacle avoidance and sea area restrictions, leading to inefficient task completion and potential collisions.
Innovation Solution
A method involving an adjusted distance-based assignment strategy using a penalty term for restricted areas, combined with route planning that avoids obstacles and dynamic obstacle avoidance through navigation controllers, ensuring smooth and efficient navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional distance-based assignment algorithms are used for multi-agent USVs, then task assignment can be completed efficiently, but the algorithms do not consider the special maneuverability and hydrodynamic constraints of USVs, leading to suboptimal task completion
Solution Approach 1:
The patent modifies the distance calculation by introducing performance-based adjustment terms that account for USV-specific parameters such as speed, turning rate, and acceleration capabilities. This transforms the simple Euclidean distance metric into a performance-aware adjusted distance metric, allowing the assignment algorithm to consider USV maneuverability while maintaining computational efficiency.
Solution Approach 2:
The patent pre-calculates performance adjustment terms and route characteristics for all USV-target pairs before executing the assignment algorithm. This preliminary computation of adjusted distances incorporating maneuverability constraints enables the Hungarian algorithm to make optimal assignments without considering USV performance characteristics during the actual assignment process.
2Device complexity
If simple straight-line routing is used for USVs, then route planning is computationally simple, but it does not account for restricted areas and sea constraints, causing potential collisions and inefficient paths
Solution Approach 1:
The patent performs preliminary route planning that accounts for restricted areas and sea constraints before task assignment is executed. By pre-calculating adjusted distances that incorporate route characteristics and constraint penalties, the system ensures that subsequent navigation follows pre-vetted safe paths without requiring complex real-time collision avoidance computations.
3Device complexity
If multi-agent USVs operate without cooperative obstacle avoidance, then navigation control is simpler, but collisions between USVs and with targets cannot be prevented
Solution Approach 1:
The patent implements a feedback mechanism where the task allocator continuously monitors USV positions, velocities, and assigned targets, then adjusts velocity commands for each USV to maintain safe separation distances. This real-time feedback control ensures cooperative obstacle avoidance while maintaining relatively simple navigation control through centralized coordination.
Data Source
AI summary
The present disclosure discloses a method for target assignment and route planning for multi-agent unmanned surface vehicles (USVs). Task information is transmitted to a task allocator, which identifies unassigned targets and available USVs. Based on a comprehensive cost function considering navigation distance and turning penalties between targets and USVs, a target is assigned to each USV A path planner then generates a smooth waypoint sequence for each assigned USV and target pair, serving as the navigation path. During navigation, a navigation controller constructs a velocity optimization model according to cooperative collision avoidance and maritime boundary constraints, and controls the USVs in real-time to navigate along the waypoint sequences. The present disclosure achieves efficient matching of multiple targets and multi-agent USVs, generates smooth navigation paths satisfying constraints, and enables intelligent navigation control while meeting cooperative collision avoidance requirements and maritime boundary constraints.