Improving interoperability in robot digital twinning for facility management: An industry foundation class-represented RoboAvatar approach
研究了用工业基础类（IFC）表示机器人化身（RoboAvatar），实现机器人数字孪生与建筑信息模型间的信息自由交换，并通过室内垃圾捡拾机器人实验验证了其在设施管理中的有效性。
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.