JRM Vol.36 No.2 pp. 294-308
doi: 10.20965/jrm.2024.p0294


Dynamic Visualization of Construction Sites with Machine-Borne Sensors Toward Automated Earth Moving

Ryo Nakamura* ORCID Icon, Masato Domae*, Takaaki Morimoto**, Takeya Izumikawa**, and Hiromitsu Fujii* ORCID Icon

*Chiba Institute of Technology
2-17-1 Tsudanuma, Narashino, Chiba 275-0016, Japan

**Sumitomo Construction Machinery Co., Ltd.
731-1 Naganumahara-cho, Inage-ku, Chiba, Chiba 263-0001, Japan

October 9, 2023
February 21, 2024
April 20, 2024
ICT construction, unmanned operation, hydraulic excavator, LiDAR, sensor fusion

The digitization of the construction site environment has progressed rapidly. In this study, the operations of hydraulic excavators—which are machines widely used in the construction industry—were advanced to enable automation and unmanned operation. To achieve this, it is necessary to determine the environment of the machines at the sites, and a real-time measurement and visualization methodology that can be installed at common construction sites is required. In this study, we propose a measurement system for reconstructing a wide range of surrounding environments using machine-borne sensors mounted on a hydraulic excavator. The proposed system measures the entire surrounding environment using a sensor unit composed of a laser imaging detection and ranging (LiDAR) and a wide-angle camera. Furthermore, methods of time-series integration for wide-range and dynamic measurements during work for occlusion-robust visualization are proposed. In an experiment using actual machines on an earth-moving site, we validated the performance of our proposed system by quantitative evaluation and confirmed that the system provides an effective solution for the digitization of construction sites.

Non-occluded measurement with machine-borne sensors

Non-occluded measurement with machine-borne sensors

Cite this article as:
R. Nakamura, M. Domae, T. Morimoto, T. Izumikawa, and H. Fujii, “Dynamic Visualization of Construction Sites with Machine-Borne Sensors Toward Automated Earth Moving,” J. Robot. Mechatron., Vol.36 No.2, pp. 294-308, 2024.
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Last updated on May. 19, 2024