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This work explores a variation of the art gallery problem in which a team of static and mobile guards track a mobile intruder with unknown maximum speed. We consider the special case when the mobile guards are restricted to move along the diagonals of a polygonal environment. First, we present an algorithm to identify candidate vertices in a polygon at which either static guards can be placed or they can serve as an endpoint of the segment on which mobile guards move. Next, we present a technique to partition the environment based on the triangulation of the environment, and allocate guards to each partition to track the intruder. The allocation strategy leads to a classification of the mobile guards based on their task and coordination requirements. Finally, we present a strategy to activate/deactivate static guards based on the speed of the intruder. Simulation results are presented to validate the efficacy of the proposed techniques.
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This content will become publicly available on May 19, 2026
Scalable Multi-Agent Surveillance: a Kernel-Based Approach
In this work, we address the deployment problem for a team of mobile guards that tries to maintain a line-ofsight with an unpredictable mobile intruder. First, we present a computationally efficient strategy for generating a set of points, called kernel points, that covers the entire polygon. We then introduce a polygon partitioning technique based on the location of the kernel points. Next, we propose control laws for a free guard to track an intruder in general polygonal environments based on the analysis of a pursuit-evasion game around a single corner [1]. Finally, we present several variations of the proposed control laws that include capture and search, and illustrate the improvement in the overall visual footprint of the team of mobile guards based on extensive simulations
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- Award ID(s):
- 1816343
- PAR ID:
- 10650404
- Publisher / Repository:
- IEEE
- Date Published:
- Page Range / eLocation ID:
- 8915 to 8921
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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