This content will become publicly available on September 30, 2023
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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, notablymore »
The adoption of robotics into the construction industry has been much slower than in manufacturing and industrial sectors. Current shortfalls in skilled labor, productivity trends, and ongoing safety challenges point to the need for a drastic shift toward the adoption of robotics as a component of a shift toward industrialized construction. Despite this lag, the interest and development of robotic technology targeting construction has grown in recent years, ranging from the use of drones for tracking to use in offsite fabrication. However, the integration into fundamental site construction requires reconsideration of the information technology infrastructure needed to support detailed task execution information needs in the transition from craft labor to robotic operations. This research presents the identification and mapping of the IT System Architecture required to support BIM to Robotic Construction. Combining elements of the Building Information Modeling architecture and information exchanges with the needed construction task decomposition is required. These elements are mapped to the robotic system elements required 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.
Computer Vision-Based Geometry Mapping and Matching of Building Elements for Construction Robotic ApplicationsRobotic 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 initialmore »
Phosphorus availability and leaching losses in annual and perennial cropping systems in an upper US Midwest landscape
AbstractExcessive phosphorus (P) applications to croplands can contribute to eutrophication of surface waters through surface runoff and subsurface (leaching) losses. We analyzed leaching losses of total dissolved P (TDP) from no-till corn, hybrid poplar (Populus nigra X P. maximowiczii), switchgrass (Panicum virgatum), miscanthus (Miscanthus giganteus), native grasses, and restored prairie, all planted in 2008 on former cropland in Michigan, USA. All crops except corn (13 kg P ha−1 year−1) were grown without P fertilization. Biomass was harvested at the end of each growing season except for poplar. Soil water at 1.2 m depth was sampled weekly to biweekly for TDP determination during March–November 2009–2016 using tension lysimeters. Soil test P (0–25 cm depth) was measured every autumn. Soil water TDP concentrations were usually below levels where eutrophication of surface waters is frequently observed (> 0.02 mg L−1) but often higher than in deep groundwater or nearby streams and lakes. Rates of P leaching, estimated from measured concentrations and modeled drainage, did not differ statistically among cropping systems across years; 7-year cropping system means ranged from 0.035 to 0.072 kg P ha−1 year−1 with large interannual variation. Leached P was positively related to STP, which decreased over the 7 years in all systems. These results indicate that both P-fertilized and unfertilized cropping systems may
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This paper proposes a web-based platform that streamlines the data collection process for creating annotated material patches guided by BIM overlays.
Construction site images with BIM overlays are automatically generated after image-based 3D reconstruction. These images are deployed on a web-based platform for annotations.
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