Work

Calibration Methods for Large-Scale and High-Precision Globalization of Local Point Cloud Data Based on iGPS

Year: 2024

Type: article

Abstract: The point cloud is one of the measurement results of local measurement and is widely used because of its high measurement accuracy, high data density, and low environmental impact. However, since point cloud data from a single measurement are generally small in spatial extent, it is necessary to accurately globalize the local point cloud to measure large components. In this paper, the method of using an iGPS (indoor Global Positioning System) as an external measurement device to realize high-accuracy globalization of local point cloud data is proposed. Two calibration models are also discussed for different application scenarios. Verification experiments prove that the average calibration errors of these two calibration models are 0.12 mm and 0.17 mm, respectively. The proposed method can maintain calibration precision in a large spatial range (about 10 m × 10 m × 5 m), which is of high value for engineering applications.

Source: Sensors

DOI: 10.3390/s24186114

Authors: Rui Han, Thomas Dunker, Erik Trostmann, Zhigang Xu

Institutions: Shenyang Institute of Automation, Chinese Academy of Sciences, Fraunhofer Institute for Factory Operation and Automation, University of Chinese Academy of Sciences

Language: English

Topic: 3D Surveying and Cultural Heritage

Subfield: Geology

Field: Earth and Planetary Sciences

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,955

Funder: European Regional Development Fund