TY - GEN
T1 - A schema for robotics operations in construction
AU - Li, Fangxiao
AU - Hu, Yuqing
AU - Leicht, Robert M.
N1 - Publisher Copyright:
© International Conference on Computing in Civil Engineering 2023.All rights reserved.
PY - 2024
Y1 - 2024
N2 - This study gathered data into a construction robot schema (CRS) with an initial data structure that can be used to collect and exchange various construction robots' information based on the data requirements of construction planners for robotics operations. To develop the CRS, the study conducted a systematic literature review using the Web of Science database to filter and identify relevant papers which were published from 2018 to 2022. Based on 279 eligible papers, the study identified significant information which involved data requirements of the construction domain on robotics using Nvivo software. To structure the information, the study summarized the information into parameters then categorized, defined, matched data types, and exemplified for these parameters. All the parameters were grouped into four categories, including ontological properties, operational requirements, activity, and safety. As a result, CRS supports data structure, including four categories and 35 parameters with corresponding definitions, data types, examples, and references.
AB - This study gathered data into a construction robot schema (CRS) with an initial data structure that can be used to collect and exchange various construction robots' information based on the data requirements of construction planners for robotics operations. To develop the CRS, the study conducted a systematic literature review using the Web of Science database to filter and identify relevant papers which were published from 2018 to 2022. Based on 279 eligible papers, the study identified significant information which involved data requirements of the construction domain on robotics using Nvivo software. To structure the information, the study summarized the information into parameters then categorized, defined, matched data types, and exemplified for these parameters. All the parameters were grouped into four categories, including ontological properties, operational requirements, activity, and safety. As a result, CRS supports data structure, including four categories and 35 parameters with corresponding definitions, data types, examples, and references.
UR - http://www.scopus.com/inward/record.url?scp=85184287078&partnerID=8YFLogxK
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U2 - 10.1061/9780784485224.089
DO - 10.1061/9780784485224.089
M3 - Conference contribution
AN - SCOPUS:85184287078
T3 - Computing in Civil Engineering 2023: Data, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2023
SP - 739
EP - 746
BT - Computing in Civil Engineering 2023
A2 - Turkan, Yelda
A2 - Louis, Joseph
A2 - Leite, Fernanda
A2 - Ergan, Semiha
PB - American Society of Civil Engineers (ASCE)
T2 - ASCE International Conference on Computing in Civil Engineering 2023: Data, Sensing, and Analytics, i3CE 2023
Y2 - 25 June 2023 through 28 June 2023
ER -