CaRC Lab
Computing and Robotic Construction Lab
Vision
Automation, digitalization, and robotics technologies are the key success factor for the fourth construction industry revolution (i.e. Construction 4.0), which can potentially enhance the efficiency, productivity, accuracy, and safety of the construction industry and address the complex problems surrounding our cities, environment, and the planet. The Computing and Robotic Construction (CaRC) Lab, led by Dr. Bo Xiao, is based in the Department of Civil, Environmental, and Geospatial Engineering at Michigan Technological University (MTU). The CaRC Lab has been and will continue to advance the digital transformation of the construction industry by adopting automated technologies (e.g., artificial intelligence (AI), robotics, and digital twinning).
News
22 December 2023
Dr. Xiao has won the 2023 Best Paper Award from the ASCE Journal of Construction Engineering and Management (IF=5.1) for his paper entitled "Deep Learning Image Captioning in Construction Management: A Feasibility Study". This paper was selected from over 200 journal papers published from July 2022 to June 2023 on the journal. More information is available here!
5 July 2023
Dr. Xiao will join the Michigan Technological University in August 2023. Positions of Ph.D. students and student research assistants are available in the CaRC Lab. Please read this link if you are interested to join!
Research in CaRC Lab
The research interests in CaRC Lab include:
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Computer vision-based site monitoring
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Construction robotics
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Natural language processing
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Blockchain-enabled contract management
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Cybersecurity in construction
Monitoring construction sites is the fundamental step for productivity analysis, safety control, and site planning. CaRC Lab adopts deep learning methods for monitoring construction machines and workforce
In almost all construction projects, engineers need to write daily reports for documentation, which is a time-consuming and labour-intensive process. CaRC Lab have integrated ChatGPT and computer vision to automatically generate daily reports from construction videos
Alberta Construction Image Dataset (ACID), developed by Dr. Bo Xiao in his Ph.D. study, is a public image dataset of construction machines for training deep learning algorithms for construction applications. ACID has been adopted by over 400 research groups in the world
Monitoring construction sites is the fundamental step for productivity analysis, safety control, and site planning. CaRC Lab adopts deep learning methods for monitoring construction machines and workforce
More details about our research can be found here or in our publication list