Distributed Coverage Control for Surveillance and Target Tracking
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Solution Overview
Problem
Monitoring systems with multiple moving bodies face challenges in optimizing the selection of monitoring targets, particularly when targets are unknown or require continued monitoring, as existing technologies do not effectively manage regions without pre-defined monitoring targets.
Innovation Solution
A coverage device with a sensor section, a defining section, and an instruction section that determines target regions based on prediction results to achieve predetermined surveillance and tracking performance levels, allocating actuators to ensure optimal coverage of both unknown and known target regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If distributed control with Voronoi regions is used for multiple moving bodies, then collision avoidance and autonomous decision-making are improved, but the ability to optimize selection of monitoring targets including unknown regions deteriorates
Solution Approach 1:
The monitoring region is divided into multiple Voronoi regions based on the positions of multiple moving bodies, with each region being independently managed by a corresponding moving body. This segmentation enables distributed autonomous decision-making while maintaining the ability to optimize target selection within each region through local uncertainty and importance level assessments.
2Adaptability or versatility
If centralized management is used for monitoring control, then optimization of monitoring target selection is improved, but device complexity and calculation load increase
Solution Approach 1:
The centralized monitoring system is segmented into multiple independent decision-making units, each responsible for a specific Voronoi region. Each moving body independently evaluates uncertainty and importance levels within its region, eliminating the need for complex centralized management while maintaining optimization capabilities through distributed processing.
Solution Approach 2:
The system transitions from a single centralized decision-making dimension to multiple parallel distributed decision-making dimensions. Each moving body operates in its own dimensional space (Voronoi region), making autonomous decisions based on local information while collectively achieving comprehensive monitoring optimization without centralized coordination overhead.
3Measurement precision
If monitoring focuses on known targets only, then tracking performance is improved, but surveillance performance for unknown regions deteriorates
Solution Approach 1:
Different quality metrics are applied to different regions: known monitoring targets are evaluated using importance levels for precise tracking, while unknown regions are evaluated using uncertainty measures for surveillance. This local quality differentiation enables simultaneous optimization of both tracking performance for known targets and surveillance performance for unknown regions within the same distributed control framework.
Data Source
AI summary
A surveillance performance (information expressing uncertainty of information relating to a potential risk area in a region that requires monitoring) and a tracking performance (information expressing the product of an importance level of a potential risk area and a coverage ratio (an overlap rate between potential risk areas and moving bodies)) are mutually analyzed, and plural moving bodies are allotted to either surveillance or tracking. Potential risk areas that require monitoring are determined such that the surveillance performance and the tracking performance respectively satisfy predetermined levels. The plural moving bodies are allocated to potential risk areas determined to be potential risk areas that require monitoring (simultaneous optimization). The respective moving bodies subject to simultaneous optimization start moving toward their allocated potential risk areas to monitor the potential risk areas.