Distributed Multi-Robot Coverage using Micro Aerial Vehicles
In this paper we present a solution to the problem of positioning a team of Micro Aerial Vehicles for a surveillance task in an environment of arbitrary and unknown morphology. The problem is addressed taking into account physical and environmental constraints like limited sensor capabilities and obstacle avoidance. The goal is to maximize the area monitored by the team, by identifying the best configuration of the team members. The proposed method is a distributed extension of our previous work based on the Cognitive Adaptive Optimization (CAO) algorithm. This distributed and scalable approach allows us to obtain coordinated and safe trajectories to accomplish the task in 3D environments. The different formulation of the problem considered in this paper allows also dealing with communication constraints. We provide extensive experimental results using data collected by a team of aerial robots and compare the efficiency of the distributed and centralized approach.