Decentralized Adaptive Coverage Control of Heterogeneous Mobile Robots

This paper proposes an algorithm for decentralized adaptive coverage control of a heterogeneous group of agents in a convex environment. The kinematics of each agent can be described by either a single integrator, a double integrator, or a unicycle. The function defining the relative importance of points in the environment is not known to the agents, and an adaptation law is used by the agents to learn about the relative importance over time. A Lyapunov based stability and convergence proof is provided for the proposed algorithm and it is verified through several relevant simulations.