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Swarm Metaverse for Multi-Level Autonomy Using Digital Twins

Authors :
Hung Nguyen
Aya Hussein
Matthew A. Garratt
Hussein A. Abbass
Source :
Sensors, Vol 23, Iss 10, p 4892 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Robot swarms are becoming popular in domains that require spatial coordination. Effective human control over swarm members is pivotal for ensuring swarm behaviours align with the dynamic needs of the system. Several techniques have been proposed for scalable human–swarm interaction. However, these techniques were mostly developed in simple simulation environments without guidance on how to scale them up to the real world. This paper addresses this research gap by proposing a metaverse for scalable control of robot swarms and an adaptive framework for different levels of autonomy. In the metaverse, the physical/real world of a swarm symbiotically blends with a virtual world formed from digital twins representing each swarm member and logical control agents. The proposed metaverse drastically decreases swarm control complexity due to human reliance on only a few virtual agents, with each agent dynamically actuating on a sub-swarm. The utility of the metaverse is demonstrated by a case study where humans controlled a swarm of uncrewed ground vehicles (UGVs) using gestural communication, and via a single virtual uncrewed aerial vehicle (UAV). The results show that humans could successfully control the swarm under two different levels of autonomy, while task performance increases as autonomy increases.

Details

Language :
English
ISSN :
14248220
Volume :
23
Issue :
10
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.73977483db5843768d17591e570a4674
Document Type :
article
Full Text :
https://doi.org/10.3390/s23104892