Distributed Coverage Control By Robot Networks In Unknown Environments Using A Modified Em Algorithm

Abstract

In this paper, we study a distributed control algorithm<br> for the problem of unknown area coverage by a network of robots.<br> The coverage objective is to locate a set of targets in the area and<br> to minimize the robots’ energy consumption. The robots have no<br> prior knowledge about the location and also about the number of the<br> targets in the area. One efficient approach that can be used to relax<br> the robots’ lack of knowledge is to incorporate an auxiliary learning<br> algorithm into the control scheme. A learning algorithm actually<br> allows the robots to explore and study the unknown environment<br> and to eventually overcome their lack of knowledge. The control<br> algorithm itself is modeled based on game theory where the network<br> of the robots use their collective information to play a non-cooperative<br> potential game. The algorithm is tested via simulations to verify its<br> performance and adaptability.