our control policies in a real-world scenario.

Many applications such as weather monitoring, geographical surveys and extra-terrestrial exploration have created research interest in the control of multiple autonomous vehicles. The task of persistent surveillance is a particularly interesting problem in that the target area needs to be continuously surveyed, minimizing the time between visitations to the same region. This distinction from one-time coverage does not allow a straightforward ap-plication of most exploration techniques to the problem, though ideas from these methods can still be used. The dynamics of air vehicles add additional complexity to the autonomous control problem, while stochastic environments and Unmanned Air Vehicle (UAV) failures enrich the problem by adding uncertainties. In this research, we investigate techniques for high-level control, that are scalable, reliable, efficient, and robust to problem dynamics. We also suggest a modification to the control policy to account for dynamic constraints. We then describe the Vehicle Swarm Technology Laboratory (VSTL)- a hardware testbed developed at Boeing Research and Technology for evaluating a swarm of UAVs- and tes