Improving interoperability in robot digital twinning for facility management: An industry foundation class-represented RoboAvatar approach

Abstract

With its bi-directional information flow, a digital twin offers the potential to enhance predictability and controllability of robots for facility management (FM). The implementation of FM involves frequent robot-building interactions, necessitating information exchanges between a robot digital twin (RDT) and a building information model (BIM). However, such information exchanges are prohibited by the different data formats used by the RDT and BIM. Our recent study has proven the viability of industry foundation class (IFC) in digitally representing robots as Avatars, and seamlessly integrating the resulting RoboAvatars into BIM-based software. Building upon that, this paper explores how the IFC-represented RoboAvatars can be used to improve interoperability of RDTs for FM. A lab experiment was conducted with an indoor trash picking robot. It demonstrates effectiveness of IFC-based RDTs in FM via the freely exchangeable robot-building information. The robot movements can be mirrored with high granularity within a BIM context. Information from BIM can be directly retrieved to trigger robot movements remotely. The research contributes to the field of FM robotics by providing the world’s first methodology to directly develop and deploy RDTs in a mainstream BIM-based environment. • Develop robot digital twins interoperable with building information models. • Propose a novel twinning solution to leverage existing environment information. • Achieve robot-building interoperability via industry foundation classes. • Verify the solution with a vivid use case in facility management.