Diversity and Intelligence in Multi-robot Teams

TL;DR

This paper introduces new tools for analyzing behavioral diversity in multi-robot systems and demonstrates their application through experiments in various robot tasks, emphasizing motor schema-based control.

Contribution

It presents novel tools for investigating behavioral diversity and applies them to real and simulated multi-robot experiments in different task scenarios.

Findings

Behavioral diversity can be effectively characterized in multi-robot systems.

The tools reveal insights into strategy variation and adaptability.

Motor schema-based control enhances task performance and robustness.

Abstract

This research proposes new tools for investigation of behavioral diversity in multi-robot systems and a significant body of results using these tools in simulated and real mobile robot experiments. The experiments specifically describe a framework of defining behavior-based strategies for multi-robot tasks as robot foraging, robot soccer and robot formation. The research focuses specifically on motor schema-based multi-robot systems, which are an important example of behavior-based control.