Multi-objective multi-robot deployment in a dynamic environment

Finding a distribution of a group of robots in an environment is known as Deployment problem, which is one of the challenges in multi-robot systems. In real applications, the environment may change over time and thus deployment must be repeated periodically in order to redistribute the robots. In this paper, we propose a multi-objective optimization method to deploy/redeploy robots in the environment by considering two objectives for the deployment. One objective represents a good estimation of final positions, where the robots will be located, while the second objective is finding the shortest path from the robots initial location to these positions. Thus, our problem is modeled as a multi-objective optimization problem, which is approached with a multi-objective optimization evolutionary algorithm. To deal with the deployment problem, a discrete setup of locational optimization framework and Voronoi partitioning technique are employed. Simulation results on real application testify the performance of our proposed method in comparison with other methods.