Area-Optimal Control Strategies for Heterogeneous Multi-Agent Pursuit
Abstract
This paper presents a novel strategy for a multi-agent pursuit-evasion game involving multiple faster pursuers with heterogenous speeds and a single slower evader. We define a geometric region, the evader's safe-reachable set, as the intersection of Apollonius circles derived from each pursuer-evader pair. The capture strategy is formulated as a zero-sum game where the pursuers cooperatively minimize the area of this set, while the evader seeks to maximize it, effectively playing a game of spatial containment. By deriving the analytical gradients of the safe-reachable set's area with respect to agent positions, we obtain closed-form, instantaneous optimal control laws for the heading of each agent. These strategies are computationally efficient, allowing for real-time implementation. Simulations demonstrate that the gradient-based controls effectively steer the pursuers to systematically shrink the evader's safe region, leading to guaranteed capture. This area-minimization approach provides a clear geometric objective for cooperative capture.
Keywords
Cite
@article{arxiv.2511.15036,
title = {Area-Optimal Control Strategies for Heterogeneous Multi-Agent Pursuit},
author = {Kamal Mammadov and Damith C. Ranasinghe},
journal= {arXiv preprint arXiv:2511.15036},
year = {2025}
}
Comments
Published as a conference paper at the Fortieth AAAI Conference on Artificial Intelligence (AAAI-26)