Building “RoboAvatar”: Industry Foundation Classes–Based Digital Representation of Robots in the Built Environment
Publication: Journal of Computing in Civil Engineering
Volume 38, Issue 4
Abstract
Digital representation of robots as Avatars, called “RoboAvatars,” is a premise for value-added construction applications such as simulation, layout design, and task planning. Existing RoboAvatars are described in data schemas predominantly from the robotics community, which prevents their smooth applications in the built environment. To fully unleash the power of robotics, this research aims to develop a Building RoboAvatar by adopting the industry foundation classes (IFC) as the de facto standard in the building industry. First, the Building RoboAvatar is defined from a built environment perspective, and then substantiated with IFC. A translator called RoboIFCTrans is developed to facilitate the exploitation of the numerous readily available RoboAvatars represented by the Unified Robot Description Format. Experiments demonstrated the effectiveness of Building RoboAvatar in representing robot information needed for the built environment, which encompasses the “whole-part” robot structure and properties in terms of productivity, capability, etc. The RoboIFCTrans can accurately generate IFC representations of diverse robots (TurtleBot, UR-5, Diablo) within 41.9 s. Practical implications of the IFC-based Building RoboAvatars were illustrated by two use cases. The research contributes to building a “Tower of Babel” between the construction and robotics communities. The source code is made publicly open, in the hope of encouraging future research to explore more exciting opportunities (e.g., robot-oriented design, digital twin) enabled by the Building RoboAvatar.
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Data Availability Statement
Select data and codes generated during the study are available from the corresponding author by request, which include the URDF and IFC files of the tested robots and the source code of the RoboIFCTrans.
Acknowledgments
This research is jointly supported by the HKU Teaching Development Grant and Seed Fund for Basic Research.
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Information & Authors
Information
Published In
Journal of Computing in Civil Engineering
Volume 38 • Issue 4 • July 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Sep 16, 2023
Accepted: Jan 2, 2024
Published online: Mar 27, 2024
Published in print: Jul 1, 2024
Discussion open until: Aug 27, 2024
ASCE Technical Topics:
- Architectural engineering
- Automation and robotics
- Building design
- Building information modeling
- Building management
- Buildings
- Construction engineering
- Construction industry
- Construction management
- Design (by type)
- Engineering fundamentals
- Foundation construction
- Foundations
- Geotechnical engineering
- Structural engineering
- Structures (by type)
- Systems engineering
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