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1. Validation of a Construction Robotics Schema for Site Operation Planning

   https://doi.org/10.1061/9780784485262.066  

   Li, Fangxiao; Wang, Ziyi; Hu, Yuqing; Leicht, Robert M (March 2024, American Society of Civil Engineers)

   This paper presents a construction robot schema (CRS) for construction planners to facilitate decision-making and project planning in operating robotics. CRS is a database schema structure that was developed in our previous study, which can facilitate collecting and exchanging data of various construction robots based on the data requirements of the construction domain. We validated the applicability of the schema by the simulation of robotic construction operations. In addition, we conducted interviews with experts from the construction industry to validate the information in CRS. As a result, the schema was validated with minor revisions to some parameters. The characteristics of CRS compared to other types of robot schema are that its development and application are based on the perspective of the construction domain and are designed to cover different construction robots broadly. The conclusions highlight the contributions of the data schema use and applicability for the construction industry. 

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2. Application of Graph Convolutional Networks to Classification of Building Code Requirements

   https://doi.org/10.1061/9780784485262.085  

   Yang, Fan; Zhang, Jiansong (March 2024, American Society of Civil Engineers)

   A building must meet various requirements during the design and construction process to ensure the benefits of stakeholders and well-being of construction workers and occupants. These requirements may come from different functional areas such as structure, electricity, and fire protection, and focus on different building materials, such as concrete, steel, and glass. They may overlap or even conflict with each other. In order to identify the sources and focus of building code requirements and further clarify the relationships between them, this paper presents some recent results on using graphic convolutional networks (GCN) to classify building code requirements. One hundred building code provisions were randomly selected from the International Building Code 2015 and labeled into six categories manually, and a cutting-edge GCN model was trained to classify them. Experimental results showed an average precision of 91.67% and an average recall of 94.44% when 10% of the data was used for testing, which is comparable to the 84.30% precision and 97.30% recall of the state-of-the-art machine learning-based approaches applied on construction document classification. The effect of the size of training data on testing accuracy was also discussed in this paper. 

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3. A Systematic Review of Virtual Reality Interfaces for Controlling and Interacting with Robots

   https://doi.org/10.3390/app10249051  

   Wonsick, Murphy; Padir, Taskin (December 2020, Applied Sciences)

   null (Ed.)

   There is a significant amount of synergy between virtual reality (VR) and the field of robotics. However, it has only been in approximately the past five years that commercial immersive VR devices have been available to developers. This new availability has led to a rapid increase in research using VR devices in the field of robotics, especially in the development of VR interfaces for operating robots. In this paper, we present a systematic review on VR interfaces for robot operation that utilize commercially available immersive VR devices. A total of 41 papers published between 2016–2020 were collected for review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Papers are discussed and categorized into five categories: (1) Visualization, which focuses on displaying data or information to operators; (2) Robot Control and Planning, which focuses on connecting human input or movement to robot movement; (3) Interaction, which focuses on the development of new interaction techniques and/or identifying best interaction practices; (4) Usability, which focuses on user experiences of VR interfaces; and (5) Infrastructure, which focuses on system architectures or software to support connecting VR and robots for interface development. Additionally, we provide future directions to continue development in VR interfaces for operating robots. 

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4. Ecological diversity methods improve quantitative examination of student language in short constructed responses in STEM

   https://doi.org/10.3389/feduc.2023.989836  

   Shiroda, Megan; Fleming, Michael P.; Haudek, Kevin C. (February 2023, Frontiers in Education)

   We novelly applied established ecology methods to quantify and compare language diversity within a corpus of short written student texts. Constructed responses (CRs) are a common form of assessment but are difficult to evaluate using traditional methods of lexical diversity due to text length restrictions. Herein, we examined the utility of ecological diversity measures and ordination techniques to quantify differences in short texts by applying these methods in parallel to traditional text analysis methods to a corpus of previously studied college student CRs. The CRs were collected at two time points (Timing), from three types of higher-ed institutions (Type), and across three levels of student understanding (Thinking). Using previous work, we were able to predict that we would observe the most difference based on Thinking, then Timing and did not expect differences based on Type allowing us to test the utility of these methods for categorical examination of the corpus. We found that the ecological diversity metrics that compare CRs to each other (Whittaker’s beta, species turnover, and Bray–Curtis Dissimilarity) were informative and correlated well with our predicted differences among categories and other text analysis methods. Other ecological measures, including Shannon’s and Simpson’s diversity, measure the diversity of language within a single CR. Additionally, ordination provided meaningful visual representations of the corpus by reducing complex word frequency matrices to two-dimensional graphs. Using the ordination graphs, we were able to observe patterns in the CR corpus that further supported our predictions for the data set. This work establishes novel approaches to measuring language diversity within short texts that can be used to examine differences in student language and possible associations with categorical data. 

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5. Proposing a Computational Modeling Framework for Generating Masonry Wall Units, Enhancing the Information Within a BIM

   https://doi.org/10.1007/s43069-024-00332-w  

   McClymonds, Austin D; Asadi, Somayeh; Leicht, Robert M (June 2024, Operations Research Forum)

   In recent decades, the construction industry has undergone a technological shift incorporating innovative technologies, such as robotics. However, information requirements must be met to integrate robotics further. Currently, building information models (BIM) contain substantial project information that can be leveraged for robots to create construction tasks, but for some building systems, the level of development (LOD) is inadequate to support these new requirements. Therefore, this study proposes a framework to increase the LOD of building systems by considering location information (X, Y, Z), orientation, material type, and component I.D. The computational modeler, Dynamo, is leveraged to increase the model’s LOD, extract information, and facilitate robotic task execution in the future. A case study is presented for multiple masonry room configurations developed in Autodesk Revit, where masonry units are generated and placed into design locations based on the geometry of the wall system. The case study used concrete masonry units (CMU) and standard brick. The number of partial-sized and full-sized blocks for each configuration was recorded, along with the computational time required to generate the units. It was observed that room configurations with more openings had longer computational times when compared to rooms constructed from the same material. After running the script, the model is reviewed to ensure accuracy and prevent overlaps or gaps in the model. The workflow provides insight into the methods used to interpret model geometry and extract information. 

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