Cooperative Multi-agent Systems for the Multi-target κ -Coverage Problem

When multiple robots are required to collaborate in order to accomplish a specific task, they need to be coordinated in order to operate efficiently. To allow for scalability and robustness, we propose a novel distributed approach performed by autonomous robots based on their willingness to interact with each other. This willingness, based on their individual state, is used to inform a decision process of whether or not to interact with other robots within the environment. We study this new mechanism to form coalitions in the on-line multi-object κ -coverage problem, and evaluate its performance through two sets of experiments, in which we also compare to other methods from the state-of-art. In the first set we focus on scenarios with static and mobile targets, as well as with a different number of targets. Whereas in the second, we carry out an extensive analysis of the best performing methods focusing only on mobile targets, while also considering targets that appear and disappear during the course of the experiments. Results show that the proposed method is able to provide comparable performance to the best methods under study.