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Download fileValue-Driven Robotic Digital Twins in Cyber-Physical Applications
preprint
posted on 2021-01-19, 04:10 authored by Eric Guiffo KaigomEric Guiffo Kaigom, Juergen Rossmann
To appear in IEEE Transactions on Industrial Informatics
Abstract: Although the skills of robot manipulators are becoming technically more
complex, the unprecedented cost-effective access to recently unveiled
intelligent robots has the potential to unleash as yet unimagined
automation capabilities. A key technology behind this opportunity for
companies to gain a competitive edge through an informed and intelligent
robotized automation is the robotic digital twin (RDT). As such, the
RDT will be instrumental in mirroring targeted properties of a physical
robot to obtain a digital sibling flexibly harnessed in virtual testbeds
to understand, predict, and shape the robot performance. However, these
objectives remain challenging to well-established simulators. This is
because the architectural and functional capabilities they support are
not sufficiently in-line with ever-growing and varying demands for agile
and cost-efficient manipulations. As a consequence, robot stakeholders
can hardly use RDTs to unlock opportunities and meet needs from
prospective markets. This paper contributes to addressing this gap. We
introduce a novel concept for the development of a RDT that helps create
and add value to current and future robotized cyber-physical
applications. Hereinafter referred to as the value-driven RDT (vdRDT),
it systematically captures the robot dynamics and purposefully farms
data, about which its services reason to facilitate insight and deliver
capabilities and benefits to stakeholders. Experiment results show that
vdRDTs enlarge the scope of, adapt to, and revitalize robotized
applications carried out in different fields.
Funding
BMWi/DLR (ProDemo-2, IBOSS-3), EU (ReconCell)
History
Email Address of Submitting Author
eric.kaigom@gmx.netSubmitting Author's Institution
IndustrySubmitting Author's Country
- Germany