Heterogeneity in the Coevolved Behaviors of Mobile Robots: The Emergence of Specialists

Abstract

Many mobile robot tasks can be most efficiently solved when a group of robots is utilized. The type of organization, and the level of coordination and communication within a team of robots affects the type of tasks that can be solved. This paper examines the tradeoff of homogeneity versus heterogeneity in the control systems by allowing a team of robots to coevolve their high-level controllers given different levels of difficulty of the task. Our hypothesis is that simply increasing the difficulty of a task is not enough to induce a team of robots to create specialists. The key factor is not difficulty per se, but the number of skill sets necessary to successfully solve the task. As the number of skills needed increases, the more beneficial and necessary heterogeneity becomes. We demonstrate this in the task domain of herding, where one or more robots must herd another robot into a confined space. 1