Abstract-In this paper we study a non-cooperative zerosum game where one player performs reconnaissance while the second player constantly observes the first. This game has implications for teams of UAVs operating within aural and visual detection range of threat forces. In particular, the threat can potentially react dynamically to UAV observations and endanger future movements. We propose a specific behavior essential to an optimal policy for a team of agents, and create a randomized algorithm inspired by these heuristics. Implementation of this path planner onto a team of autonomous helicopters demonstrated the utility of the algorithm in real time applications.

We propose a framework for intelligence, reconnaissance, and surveillance using an aerial vehicle with multiple sensor payloads to provide autonomous and continuous security operations at a fixed location. A control scheme and a graphical user interface between the vehicle and operator is strictly mandated for tasks requiring remote and unattended inspection. By leveraging existing navigation and path planning algorithms, the system can autonomously patrol large areas, automatically recharge when required, and relay on-demand data back to the user. This paper presents recent validation results of the system and its sensors using the proposed framework.

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