Framework demonstrates efficient point cloud registration in large-scale environments, suggesting time-saving potential.
This article presents a novel fully automatic indoor surveying (FAIS) framework for large-scale indoor environments using a Terrestrial Laser Scanning (TLS) hardware system. Traditional methods for indoor surveying are labor-intensive and time-consuming, as they rely on manually positioning scanners for data capture and placing markers for registration. What is more, positioning scanners manually may cause uneven scanning or rescanning, including unstructured areas specifically. To ensure full coverage of the scene, we precisely obtain the number and location of scan stations through the Signed Distance Function (SDF) based method. Meanwhile, we propose an efficient large-scale dense point cloud registration method without markers. The proposed framework is adapted to environments where the scanner operates on a flat surface, such as office spaces, theater stage spaces, urban areas, and some cultural heritage scenic areas. Experiments demonstrate that the proposed method decreases computation time and obtains a more complete point cloud.
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Li et al. (2025) studied this question.