Autonomous UAV Surveillance in Complex Urban Environments

We address the problem of multi-UAV-based surveillance in complex urban environments with occlusions. The problem consists of controlling the flight of UAVs with on-board cameras so that the coverage and recency of the information about the designated area is maximized. In contrast to the existing work, sensing constraints due to occlusions and UAV motion constraints are modeled realistically and taken into account. We propose a novel \emph{occlusion-aware} surveillance algorithm based on a decomposition of the surveillance problem into a variant of the 3D art gallery problem and an instance of traveling salesman problem for Dubins vehicles. The algorithm is evaluated on the high-fidelity \textsc{AgentFly} UAV simulation testbed which accurately models all constraints and effects involved. The results confirm the importance of occlusion-aware flight path planning, in particular in the case of narrow-street areas and low UAV flight altitudes.