Decentralized Minimum-Energy Coverage Control for Time-Varying Density Functions

This paper introduces a minimum-energy approach to the problem of time-varying coverage control. The coverage objective, encoded by a locational cost, is reformulated as a constrained optimization problem that can be solved in a decentralized fashion. This allows the robots to achieve a centroidal Voronoi tessellation by running a decentralized controller even in case of a time-varying density function. We demonstrate that this approach makes no assumptions on the rate of change of the density function and performs the computations in an approximation-free manner. The performance of the algorithm is evaluated in simulation as well as on a team of mobile robots.

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