Rapid dynamic target surface modeling for crane operation using hybrid LADAR system
Document Type
Conference Proceeding
Publication Date
1-1-2014
Abstract
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 recognize and track the dynamic objects quickly, such as a crane boom. The dynamic target object's point clouds were updated separately 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 converted rapidly 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 presented wirelessly to a remote crane operator. The field test results demonstrated that the proposed rapid dynamic target modeling method would improve the crane operation productivity and safety significantly by distinguishing a dynamic surface model being controlled by the operator from the point cloud of existing static environment in 3D views. © 2014 American Society of Civil Engineers.
Publication Source (Journal or Book title)
Construction Research Congress 2014: Construction in a Global Network - Proceedings of the 2014 Construction Research Congress
First Page
1053
Last Page
1062
Recommended Citation
Cho, Y., Wang, C., Gai, M., & Park, J. (2014). Rapid dynamic target surface modeling for crane operation using hybrid LADAR system. Construction Research Congress 2014: Construction in a Global Network - Proceedings of the 2014 Construction Research Congress, 1053-1062. https://doi.org/10.1061/9780784413517.0108