A Framework for BIM-Driven Construction Robot Assembly: From Simulation to Real-World Implementation
The manufacturing industry has markedly enhanced production efficiency using digital twins and automation technologies, propelled by the advancements of Industry 4.0 and intelligent manufacturing. Nonetheless, the digitalization movement inside the construction sector is behind schedule. Construction robots encounter obstacles that include restricted functionality, inadequate environmental adaptability, and insufficient practical validation and integration with Building Information Modeling (BIM). This study presents a method utilizing BIM models to create robot simulation environment models and direct actual construction, with the objective of integrating design, simulation, and construction. Through the examination of the hierarchical structure and geometric data of Industry Foundation Classes (IFC) files, alongside the integration of material, density, and additional attributes from Revit project files, the BIM model is transformed into a Simulation Description Format (SDF) model suitable for the Gazebo simulation environment. The experiment validates the practicality of the technology through a case study involving a steel joint assembly task. The findings indicate that the mean grasping error of the robotic arm is between 2.55 and 2.6 mm, while the installation error varies from 3.6 to 3.73 mm. This research establishes a technical framework for the synergistic implementation of BIM and construction robotics, hence facilitating the automation enhancement of actual construction environments.
Authors
- Duo Zhang (ORCID: https://orcid.org/0000-0003-0361-4174)
- Shuai Li (ORCID: https://orcid.org/0000-0001-8316-5289)
- Tao Li (ORCID: https://orcid.org/0009-0006-6811-2182)
Institutions
- Chongqing University (CN)
Publication Details
- Published
- 2025-05-07
- DOI
- https://doi.org/10.1109/airc64931.2025.11077531
- Primary Topic
- Innovations in Concrete and Construction Materials
- Type
- article
- Field-Weighted Citation Impact
- 0.00