  Coverage control has been widely used for constructing mobile sensor network
such as for environmental monitoring, and one of the most commonly used methods
is the Lloyd algorithm based on Voronoi partitions. However, when this method
is used, the result sometimes converges to a local optimum. To overcome this
problem, game theoretic coverage control has been proposed and found to be
capable of stochastically deriving the optimal deployment. From a practical
point of view, however, it is necessary to make the result converge to the
global optimum deterministically. In this paper, we propose a global optimal
coverage control along with collision avoidance in continuous space that
ensures multiple sensors can deterministically and smoothly move to the global
optimal deployment. This approach consists of a cut-in algorithm based on
neighborhood importance of measurement and a modified potential method for
collision avoidance. The effectiveness of the proposed algorithm has been
confirmed through numerous simulations and some experiments using multiple
aerial robots.
