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Building "RoboAvatar": Industry Foundation Classes–Based Digital Representation of Robots in the Built Environment.

Authors :
Chen, Junjie
Lu, Weisheng
Pan, Yipeng
Fu, Yonglin
Source :
Journal of Computing in Civil Engineering. Jul2024, Vol. 38 Issue 4, p1-17. 17p.
Publication Year :
2024

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08873801
Volume :
38
Issue :
4
Database :
Academic Search Index
Journal :
Journal of Computing in Civil Engineering
Publication Type :
Academic Journal
Accession number :
177251889
Full Text :
https://doi.org/10.1061/JCCEE5.CPENG-5723