Abstract
In order to assist crane operators in rapidly perceiving 3D working environments at dynamic construction sites, an automated rapid 3D workspace modeling method is proposed in this paper. A custom-designed laser scanner system was utilized to collect point cloud data; multiple video camera arrays were used to quickly recognize and track the dynamic objects such as a crane boom. The dynamic target object’s point clouds were separately updated by a smart scan method. At the same time, the point cloud data of previously scanned static work environments were merged to the dynamic scan data. The raw point cloud from extracted target areas was rapidly converted into a 3D surface model using the convex hull algorithm after a process of downsizing the raw data to increase the data processing speed. The performance of the proposed method was tested at a steel frame building construction site. Both the generated dynamic target’s surface models and the point cloud of static surroundings were wirelessly presented to a remote crane operator. The field test results demonstrated that the proposed rapid dynamic target modeling method would significantly improve the crane operation productivity and safety by distinguishing a dynamic surface model being controlled by the operator from the point cloud of existing static environment in 3D views.
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