Asynchronous and Dynamic Coverage Control Scheme for Persistent Surveillance Missions
This addresses the challenge of efficient and reliable surveillance for applications like security or monitoring in settings with limited communication, though it appears incremental as it builds on existing coverage control methods.
The paper tackles the problem of multi-agent persistent surveillance in communication-constrained, dynamic environments by proposing a decomposition-based coverage control scheme that decouples task assignment from motion planning. The result is a framework that guarantees connected coverage, bounded uncovered periods, collision avoidance, and Pareto-optimal convergence under static conditions, as demonstrated in simulations.
A decomposition-based coverage control scheme is proposed for multi-agent, persistent surveillance missions operating in a communication-constrained, dynamic environment. The proposed approach decouples high-level task assignment from low-level motion planning in a modular framework. Coverage assignments and surveillance parameters are managed by a central base station, and transmitted to mobile agents via unplanned and asynchronous exchanges. Coverage updates promote load balancing, while maintaining geometric and temporal characteristics that allow effective pairing with generic path planners. Namely, the proposed scheme guarantees that (i) coverage regions are connected and collectively cover the environment, (ii) subregions may only go uncovered for bounded periods of time, (iii) collisions (or sensing overlaps) are inherently avoided, and (iv) under static event likelihoods, the collective coverage regions converge to a Pareto-optimal configuration. This management scheme is then paired with a generic path planner satisfying loose assumptions. The scheme is illustrated through simulated surveillance missions.