Achieving Connectivity Between Wide Areas Through Self-Organising Robot Swarm Using Embodied Evolution

TL;DR

This paper explores autonomous robot swarms using embodied evolution to establish communication links in disaster or war scenarios, reducing human risk through self-organising multi-robot systems.

Contribution

It introduces a novel approach integrating embodied evolution and self-organisation in robot swarms for connectivity tasks, with comparative heuristics including neuroevolution.

Findings

Embodied evolution shows promising results in connectivity tasks.

Neuroevolution-based heuristics outperform other methods.

The approach provides guidelines for deploying autonomous communication relays.

Abstract

Abruptions to the communication infrastructure happens occasionally, where manual dedicated personnel will go out to fix the interruptions, restoring communication abilities. However, sometimes this can be dangerous to the personnel carrying out the task, which can be the case in war situations, environmental disasters like earthquakes or toxic spills or in the occurrence of fire. Therefore, human casualties can be minimised if autonomous robots are deployed that can achieve the same outcome: to establish a communication link between two previously distant but connected sites. In this paper we investigate the deployment of mobile ad hoc robots which relay traffic between them. In order to get the robots to locate themselves appropriately, we take inspiration from self-organisation and emergence in artificial life, where a common overall goal may be achieved if the correct local rules on the agents in system are invoked. We integrate the aspect of connectivity between two sites into the multirobot simulation platform known as JBotEvolver. The robot swarm is composed of Thymio II robots. In addition, we compare three heuristics, of which one uses neuroevolution (evolution of neural networks) to show how self-organisation and embodied evolution can be used within the integration. Our use of embodiment in robotic controllers shows promising results and provide solid knowledge and guidelines for further investigations.