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 language | English |
---|---|
Title of host publication | Artificial Life Conference Proceedings |
Editors | Josh Bongard, Juniper Lovato, Laurent Hebert-Dufresne, Radhakrishna Dasari, Lisa Soros |
Publisher | Massachusetts Institute of Technology (MIT) Press |
Pages | 549-557 |
Number of pages | 9 |
Volume | 32 |
DOIs | |
Publication status | Published - 14 Jul 2020 |
Event | Conference on Artificial Life: New Frontiers in AI: What can ALIFE offer AI? - Hosted online Duration: 13 Jul 2020 → 18 Jul 2020 http://2020.alife.org/ |
Conference
Conference | Conference on Artificial Life |
---|---|
Abbreviated title | ALIFE 2020 |
Period | 13/07/20 → 18/07/20 |
Internet address |