Automatically designing robot swarms in environments populated by other robots: an experiment in robot shepherding

TL;DR

This paper explores automatic design of robot swarms that interact with other robots in their environment, specifically focusing on robot shepherding where a small swarm guides a larger group of pre-programmed robots.

Contribution

It introduces an automatic modular design and neuroevolution approach for creating robot swarms that coordinate with other active robots in their environment.

Findings

Automatic design enables effective coordination strategies.

Mission-specific interactions improve swarm performance.

Neuroevolution successfully produces control software for complex tasks.

Abstract

Automatic design is a promising approach to realizing robot swarms. Given a mission to be performed by the swarm, an automatic method produces the required control software for the individual robots. Automatic design has concentrated on missions that a swarm can execute independently, interacting only with a static environment and without the involvement of other active entities. In this paper, we investigate the design of robot swarms that perform their mission by interacting with other robots that populate their environment. We frame our research within robot shepherding: the problem of using a small group of robots, the shepherds, to coordinate a relatively larger group, the sheep. In our study, the group of shepherds is the swarm that is automatically designed, and the sheep are pre-programmed robots that populate its environment. We use automatic modular design and neuroevolution to produce the control software for the swarm of shepherds to coordinate the sheep. We show that automatic design can leverage mission-specific interaction strategies to enable an effective coordination between the two groups.