A Correlated Random Walk Model to Rapidly Approximate Hitting Time Distributions in Multi-robot Systems

Yi Zhang, Daniel Boley, John Harwell, Maria L. Gini

Abstract: Multi-robot systems are frequently used for tasks involving searching, so it is important to be able to estimate the searching time. Yet, simulation approaches and real-world experiments to determine searching time can be cumbersome and even impractical. In this work, we propose a correlated-random-walk based model to efficiently approximate hitting time distributions of multi-robot systems in large arenas. We verified the computational results by using ARGoS, a physics-based simulator. We found that the Gamma distribution can provide a good fit to the hitting time distributions of random walkers.