@article{Pan2025, 
author = {Xiao Pan and Tony T. Y. Yang and Ruiwu Liu and Yifei Xiao and Fan Xie},
title = {A computer vision and point cloud-based monitoring approach for automated construction tasks using full-scale robotized mobile cranes},
year = {2025},
journal = {Journal of Intelligent Construction},
volume = {3},
number = {2},
pages = {9180086},
keywords = {automated construction computer vision, image processing, object detection and tracking stereo vision, 3D point clouds},
url = {https://www.sciopen.com/article/10.26599/JIC.2025.9180086},
doi = {10.26599/JIC.2025.9180086},
abstract = {Recent years have witnessed rapid development and contemporary trends in smart construction research owing to advances in machine learning algorithms, modern sensory systems, and robotic technologies. In this paper, a novel economical computer vision (CV) and point cloud-based monitoring framework is proposed to assist in the lifting and relocation of construction sources via mobile cranes on site. The proposed framework incorporates a multicamera approach to achieve multiple goals, such as three-dimensional (3D) vision-based real-time reconstruction, 3D localization of construction resources, and safety monitoring. To demonstrate the effectiveness of the proposed framework, field experiments were conducted on a full-scale mobile crane. The results show that the proposed monitoring system achieves real-time performance, which can successfully recognize construction resources and guide the crane to initialize the lifting position and avoid potential moving workers during motion execution.}
}