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The construction industry has undergone a technological shift. Technology advancements have made robots a topic of discussion in construction. One challenge to overcome is how the robot receives information from designed BIM models. This study describes the methods employed for parametric modeling and generating model content of wall systems in Autodesk Revit added with a Dynamo script. Coordinates are determined for components based on model geometry and dimensions. Once generated, components are placed with the required material based on wall parameters. This research develops a method to add components based on wall materials from a traditionally modeled BIM extracting information such as location, object identifier (ID), type, and orientation which is formatted to transfer to the robot based on the needs of the robotic system as a list of tasks in a comma-separated values (.CSV) file. This study details the development process and early implementation of the Dynamo script. 

Advances in construction robotics represent a potential shift in building design and construction. In general, construction robotics are usually deployed directly onto construction sites without systematically evaluating the design constructability for robotic applications. Literature on constructability suggest that ignoring it during design will cause rework, inefficiency, and higher cost. Although previous studies have widely discussed design constructability, they mainly focus on traditional human craft-based construction methods. Whereas a gap still exists in design constructability assessment for construction robotics. This paper presents an initial analytical framework for constructability assessment for construction robotics during the design phase. Specifically, we summarize factors that impact robotic constructability based on robotic features, design features, work constraints, and piloted an automated constructability checking system for robotics. Additionally, this study takes CANVAS, a drywall finishing robot, as case study to create a framework in simulation environment and the results demonstrate the potential value of the proposed framework. 

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 4 categories and 35 parameters with corresponding definitions, data types, examples, and references.