CAREER: Hybrid 3D Unstructured Workspace Modeling: A Critical Component in Developing an Automated Construction Site

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The objective of this Faculty Early Career Development (CAREER) program award is to create an innovative 3D workspace visualization method, which will enable automated construction equipment to safely and efficiently handle construction materials for robotic field erection and connection. Robotic construction material handling requires both rapid visualization of the workspace and highly accurate position data for safe and secure physical contact between a target object and a robot. These are difficult to achieve with current sensor technologies. To meet this challenge, a target-focused range data collection and modeling method will be researched through a hybrid approach that integrates a light-weight 3D laser scanner with secondary and tertiary sensory devices such as a laser rangefinder and an infrared camera. A hybrid system mountable on a robot or piece of equipment will significantly reduce data collection time while enhancing data accuracy. Automatic target detection and model-based fitting and matching algorithms will be developed for various shapes of construction material components. The hybrid approach will be tested using real-world robotic test beds, including a multi-joint arm robot at the University of Nebraska-Lincoln and a bolting robot and a robot crane located within Korea University's automated building construction system. If successful, the results of this research will enhance the development of more intelligent and automated construction job sites and manufacturing processes by providing a fully sensed, monitored environment for materials, equipment, and operators. This research will also positively impact the environment by reducing the enormous amount of construction waste, which will greatly benefit the construction industry and society in general. Finally, this project has strong educational plans that will nurture tomorrow's leaders in engineering and science, promote lifelong learning for industrial practitioners, and broaden participation of underrepresented groups in research.