AutoMoDe: A Modular Approach to the Automatic Off-Line Design and Fine-Tuning of Control Software for Robot Swarms

Abstract

Although swarm robotics is widely recognized as a promising approach to coordinating large groups of robots, a general methodology for designing collective behaviors for robot swarms is still missing. Automatic off-line design is an appealing solution but it is prone to the so-called reality gap, which is the reason for performance drops when control software developed in simulation is deployed on real robots. We present here our research on AutoMoDe, a novel approach to the automatic off-line design of robot swarms, which is based on the principle of modularity. AutoMoDe produces control software for robot swarms by selecting, combining, instantiating, and fine-tuning predefined parametric modules that represent low-level behaviors defined in a mission-agnostic way. By restricting the generation of control software to the instances that can be produced with the given modules, we effectively inject a bias in the design process and consequently reduce its variance. As confirmed by the empirical studies realized so far, this reduces the risk of overfitting simulation models and improves the chances of crossing the reality gap successfully.