Review of the Applications of Building Information Modelling in Robotics

Byers, Gareth, RazaviAlavi, SeyedReza and Kiavarz, H, (2022) Review of the Applications of Building Information Modelling in Robotics. In: 2022: The Digital Reality of Tomorrow. University of New Brunswick, Fredericton, Canada, pp. 1-10.

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Official URL: https://doi.org/10.57922/tcrc.624

Abstract

Adopting robots in the construction industry can address the main issues existing for a long time in this industry, i.e., low productivity, high safety incident and injury rates, and skilled labour shortage. Due to the advancements in artificial intelligence, sensing and computing technologies over the past few years, robot applications for automating manual and repetitive construction activities have been rising. Dynamics, uniqueness, and complexity of construction sites are the primary hindrances for adopting robots in the construction environment. Building Information Modeling (BIM) can assist robots to overcome these hindrances by providing geometric, topological, and semantic data about the construction and built environment in a digital format. Recent studies have attempted to exploit BIM data for enhancing robot navigation, planning robot tasks, and construction progress tracking. This study aims to report the state of the art in the emerging applications of BIM in robotics through systematically reviewing the literature and providing the trend of the studies for utilising BIM in promoting robot applications in the construction industry.

Item Type: Book Section
Additional Information: Transforming Construction with Reality Capture Technologies: The Digital Reality of Tomorrow, Fredericton, Canada: 23-26 Aug 2022
Uncontrolled Keywords: Building Information Modeling, Construction Automation, Robot, Construction Robotics, systematic literature review
Subjects: K900 Others in Architecture, Building and Planning
Department: Faculties > Engineering and Environment > Mechanical and Construction Engineering
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Depositing User: John Coen
Date Deposited: 10 Nov 2022 14:43
Last Modified: 10 Nov 2022 15:00
URI: https://nrl.northumbria.ac.uk/id/eprint/50612

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