Morphological communication for swarms

Asheesh Sharma, Sabine Hauert, Helmut Hauser

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

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Abstract

Robotic swarms rely on local communication between agents to exhibit cooperative emergent behaviours. Local communication is typically implemented with technologies that require dedicated electronics, that can be expensive and difficult to miniaturise or mass-produce. Computational resources are then needed to transform this information into a robot action following a set of rules, further limiting swarm lifetime (battery) and scalability. In this paper, we propose an alternative approach by using the concept of morphological computation (computation through morphology) for local communication in swarms. In such a swarm, local communication is implemented as simple mass-spring-damper systems between agents, instead of electronics. We test this approach in a simple scenario where a swarm has to squeeze through a narrow gap while floating on water. We tested different types of swarms (with different levels of control) and measured their average performance and energy efficiency. We found that by off loading the majority of communication and information processing to the morphology,swarms can exhibit interesting, emergent, cooperative behaviour to solve the given task.
Original languageEnglish
Title of host publicationArtificial Life Conference Proceedings
EditorsJosh Bongard, Juniper Lovato, Laurent Hebert-Dufresne, Radhakrishna Dasari, Lisa Soros
PublisherMassachusetts Institute of Technology (MIT) Press
Pages549-557
Number of pages9
Volume32
DOIs
Publication statusPublished - 14 Jul 2020
EventConference on Artificial Life: New Frontiers in AI: What can ALIFE offer AI? - Hosted online
Duration: 13 Jul 202018 Jul 2020
http://2020.alife.org/

Conference

ConferenceConference on Artificial Life
Abbreviated titleALIFE 2020
Period13/07/2018/07/20
Internet address

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