A Kalman Filter-Based Control Strategy for Dynamic Coverage Control

In this paper, a control strategy based on the discrete Kalman filter is developed for a dynamic coverage control problem. The goal is to estimate a spatially-decoupled scalar field using a network of finite-range sensor vehicles. The approach relies on using the Kalman filter to estimate the field and on the filter's prediction step to plan the vehicles' next move to maximize the quality of the field estimate. Finally, the algorithm is modified to avoid converging to local minima of the coverage cost, and to guarantee full estimation of the field over the entire domain. Numerical simulations are provided to show the performance of the proposed control strategies.