Area-constrained coverage optimization by robotic sensor networks

This paper studies robotic sensor networks performing coverage optimization tasks with area constraints. The network coverage of the environment is a function of the robot locations and the partition of the space. The area of the region assigned to each robot is constrained to be a pre-specified amount. We characterize the optimal configurations as center generalized Voronoi configurations. The generalized Voronoi partition depends on a set of weights, one per robot, assigned to the network. We design a Jacobi iterative algorithm to find the weight assignment whose corresponding generalized Voronoi partition satisfies the area constraints. This algorithm is distributed over the generalized Delaunay graph. We also design the ¿move-to-center-and-compute-weight¿ coordination algorithm that steers the robotic network towards the set of center generalized Voronoi configurations while monotonically optimizing coverage. Various simulations illustrate our results.