Linking physical objects to their digital twins via fiducial markers designed for invisibility to humans

Mathew Schwartz (Corresponding author), Yong Geng, Hakam Agha, Rijeesh Kizhakidathazhath, Danqing Liu, Gabriele Lenzini, Jan P.F. Lagerwall (Corresponding author)

Research output: Contribution to journalReview articlepeer-review

13 Citations (Scopus)
125 Downloads (Pure)

Abstract

The ability to label and track physical objects that are assets in digital representations of the world is foundational to many complex systems. Simple, yet powerful methods such as bar-A nd QR-codes have been highly successful, e.g. in the retail space, but the lack of security, limited information content and impossibility of seamless integration with the environment have prevented a large-scale linking of physical objects to their digital twins. This paper proposes to link digital assets created through building information modeling (BIM) with their physical counterparts using fiducial markers with patterns defined by cholesteric spherical reflectors (CSRs), selective retroreflectors produced using liquid crystal self-assembly. The markers leverage the ability of CSRs to encode information that is easily detected and read with computer vision while remaining practically invisible to the human eye. We analyze the potential of a CSR-based infrastructure from the perspective of BIM, critically reviewing the outstanding challenges in applying this new class of functional materials, and we discuss extended opportunities arising in assisting autonomous mobile robots to reliably navigate human-populated environments, as well as in augmented reality.

Original languageEnglish
Article number022002
Number of pages19
JournalMultifunctional Materials
Volume4
Issue number2
DOIs
Publication statusPublished - Jun 2021

Funding

We thank Dr Jose Luis Sanchez-Lopez and Professor Holger Voos for valuable discussions concerning the implementation of CSR fiducials in robotic navigation. We gratefully acknowledge financial support from the European Research Council (ERC, Proof of Concept project VALIDATE, Grant Code 862315), the Office of Naval Research Global (Project LAB’RINTH), and the Luxembourg National Research Fund (C17/MS/11688643/SSh).

FundersFunder number
European Union's Horizon 2020 - Research and Innovation Framework Programme862315
H2020 European Research Council

    Keywords

    • Autonomous robots
    • Building information modeling
    • Cholesteric liquid crystals
    • Construction
    • Digital twin
    • Fiducial markers
    • Localization

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