  In this paper, we address the problem of collision avoidance for a swarm of
UAVs used for continuous surveillance of an urban environment. Our method,
LSwarm, efficiently avoids collisions with static obstacles, dynamic obstacles
and other agents in 3-D urban environments while considering coverage
constraints. LSwarm computes collision avoiding velocities that (i) maximize
the conformity of an agent to an optimal path given by a global coverage
strategy and (ii) ensure sufficient resolution of the coverage data collected
by each agent. Our algorithm is formulated based on ORCA (Optimal Reciprocal
Collision Avoidance) and is scalable with respect to the size of the swarm. We
evaluate the coverage performance of LSwarm in realistic simulations of a swarm
of quadrotors in complex urban models. In practice, our approach can compute
collision avoiding velocities for a swarm composed of tens to hundreds of
agents in a few milliseconds on dense urban scenes consisting of tens of
buildings.
