Estimation and control of UAV swarms for distributed monitoring tasks

This paper proposes a distributed estimation and control strategy for cooperative monitoring by swarms of unmanned aerial vehicles (UAVs) modeled as constant-speed unicycles. The geometric moments, encoding an abstraction of the swarm, are controlled via a nonlinear gradient descent to match those of a discrete set of particles describing the occurrence of some event of interest to be monitored. Because of its limited sensing capabilities, each agent can measure the position of only a subset of the overall particles, from which it locally estimates the desired moments of the swarm running a proportional-integral (PI) average consensus estimator. The closed-loop stability of the system arising from the combination of the gradient-descent controllers and the consensus estimators is studied and simulation results are provided to illustrate the proposed theory.