An Ontology Based Knowledge Representation for Coordinated SS-bots

Abstract

Collective behaviour empowers biological species  to achieve remarkable swarm level results through  distributed actions. For example, social spiders  achieve coordinated activities that can lead to  plausible outcomes such as preying, mating, or building webs. Developers of simulated swarm  systems are increasingly moving away from  insinuating individualistic robotic devices,  gravitating towards collective swarms to achieve  common goals. However, for this to happen, it is  imperative to understand the principles that underpin successful simulated coordination of  robotic devices in swarms. In this article, we investigate the principles behind artificial swarm systems built on the instinctive behaviours of  simulated social spider-like devices (SS-bots). We  classify these principles into six interconnected  knowledge domains, including (a) environment,  (b) SS-bot architecture, (c) SS-bot mission  planning, (d) SS-bot communication, (e) SS-bot operators, and (f) metadata and swarm-level data.  The key features of each domain are discussed, and an SS-bot ontology is proposed.  

https://doi.org/10.59200/ICONIC.2022.024