Cooperative Multi-Robot System for Infrastructure Security Tasks

Abstract

As a result of terrorist attacks in the last years, new efforts have raised trying to solve challenges related to security task automation using robotic platforms. In this paper we present the results of a cooperative multi-robot approach for infrastructure security applications at critical facilities. We formulate our problem using a Ms. Pac-Mac like environment. In this implementation, multiple robotic agents define policies with the objective to increase the number of explored states in a grid world. This is through the application of the off-policy learning algorithm from reinforcement learning area, known as Q-learning. We validate experimentally our approach with a group of agents learning a patrol task and we present results obtained in simulated environments.