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1. System Architecture for supporting BIM to Robotic Construction Integration

   McClymonds, A.; Leicht, R.; Asadi, S. (May 2021, Proceedings Canadian Society for Civil Engineering)

   The adoption of robotics into the construction industry has been progressing slower than in the manufacturing and industrial sectors. Current shortfalls in skilled labor, productivity trends, and ongoing safety challenges point to the need for a drastic shift toward adopting robotics. Addressing these shortfalls would be a necessary component of the shift toward industrializing the construction industry. Despite this lag in technology adoption, the interest and development of robotic technology targeting the construction industry has grown in recent years and is ranging from the use of drones for tracking to advances in offsite fabrication. However, the integration into fundamental site construction necessitates reconsidering the information technology infrastructure needed to support detailed task execution information needs in the change from craft labor to robotic operations. This research presents the identification and mapping of the Information Technology (IT) system architecture required to support building information modeling (BIM) to robotic construction. Combining elements of BIM architecture and information exchanges with the needed construction task decomposition is required. These elements are mapped to the robotic system elements vital for mobile robotic operations. In addition to defining the functions and integration required to support the BIM to robotic Construction Workflow, shortcomings in existing infrastructure, notably regarding the ability to decompose construction fabrication and assembly means and methods, are defined. 

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2. Automated Constructability Assessment for Robotics in Construction: Case Study of CANVAS

   https://doi.org/10.1061/9780784485262.070  

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

   Advances in robotics represent a potential shift in the construction industry. Construction planning is planned based on craft work; it is necessary to emphasize external factors such as construction robotics. Improving constructability can enhance design-phase construction opportunities, thereby expanding the potential scope of robot operations. However, robotics are often neglected concerning constructability. Previous studies on constructability concentrated on human-based construction methods; hence, gaps remain in assessing constructability for robotics. To minimize the barriers in robotic construction, this paper presents a method for using a rule-based framework for robotic constructability assessment checks with the help of BIM. Focusing on CANVAS—a drywall finishing robot—this paper applies a BIM-based object-oriented model integrating with ROS to utilize constructability reasoning about robotic operations. A model of rule-checking for robotics in the case study is demonstrated and tested. The availability of design information in the model containing robotics is discussed, showing the need for assessing robotics-related constructability information to support an automated review of robotic constructability assessment. This paper applies a case study to validate use of the framework for robotic constructability assessment in the design phase, leading to an automated constructability assessment of construction robotics. 

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3. Utilizing Parametric Computational Modeling to Generate Masonry Wall System to Facilitate Robotic Task Creation

   https://doi.org/10.1061/9780784485262.097  

   McClymonds, Austin D; Asadi, Somayeh; Leicht, Robert M (March 2024, American Society of Civil Engineers)

   Building information modeling (BIM) technology in construction has become increasingly prevalent in recent years, and integrating robotics is seen as a natural step to improve efficiency. To increase the level of development (LOD) of a BIM model to support a construction robot, parametric modeling can be used to create highly detailed models by supplementing and defining the geometric and physical properties of the construction elements, such as the components’ size, shape, and material parameters, which are used as inputs for designing robotic tasks. Component information and data are stored as extractable parameters within the BIM model, allowing a robot to perform highly precise and repeatable tasks. This study develops a framework for implementing computational parametric modeling for masonry wall systems with Dynamo. This study tested six wall configurations constructed of 8″ × 8″ × 16″ concrete masonry units (CMUs). Dynamo successfully interpreted most wall geometries placing full-sized CMUs into the correct design locations. Errors occurred when placing partial-sized CMUs, typically at wall intersections, revealing a need for future refinement. The study shows the careful planning and considerations needed to implement computational modeling to generate model content for creating robotic tasks. 

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4. Information Exchange for Supporting BIM to Robotic Construction

   https://doi.org/9780784483961  

   McClymonds, Austin; Asadi, Somayeh; Wagner, Alan; Leicht, Robert (September 2022, ASCE Construction Research Congress)

   In the past, the construction industry has been slow to adopt new technology. There has been a rapid expansion of technologies, often referred to as Industry 4.0, to aid in the use of automation. One challenge paralleling these new technologies is implementing how a robot interprets design information, specifically information from a Building Information Model (BIM). This paper presents a method for identifying and transforming information from BIM to support robotic material placement on the construction site. This research will include a review of what information can be directly extracted from the model and what must be supplemented to the model for the robot to perform defined tasks within a construction site. The construction sites’ dynamic nature poses multiple challenges that must be addressed for the information extracted from a model to be used by a robot in daily construction operations. This research also identifies barriers and limitations based upon current practice, such as different levels of development or model content as well as needed precision within the information provided for a mobile robot to complete a defined task. 

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5. Computer Vision-Based Geometry Mapping and Matching of Building Elements for Construction Robotic Applications

   https://doi.org/10.1061/9780784483961.057  

   Lacny, Christopher; Zhang, Jiansong (March 2022, Construction Research Congress 2022)

   Robotic automation of construction tasks is a growing area of research. For robots to successfully operate in a construction environment, sensing technology must be developed which allows for accurate detection of site geometry in a wide range of conditions. Much of the existing body of research on computer vision systems for construction automation focuses on pick-and-place operations such as stacking blocks or placing masonry elements. Very little research has focused on framing and related tasks. The research presented here aims to address this gap by designing and implementing computer vision algorithms for detection and measurement of building framing elements and testing those algorithms using realistic framing structures. These algorithms allow for a stationary RGB-D camera to accurately detect, identify, and measure the geometry of framing elements in a construction environment and match the detected geometry to provided building information modeling (BIM) data. The algorithms reduce identified framing elements to a simplified 3D geometric model, which allows for robust and accurate measurement and comparison with BIM data. This data can then be used to direct operations of construction robotic systems or other machines/equipment. The proposed algorithms were tested in a laboratory setting using an Intel RealSense D455 RGB-D camera, and initial results indicate that the system is capable of measuring the geometry of timber-frame structures with accuracy on the order of a few centimeters. 

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