3D model-based terrestrial laser scanning (TLS) observation network planning for large-scale building facades

Abstract

Planning a terrestrial laser scanning (TLS) observation network is vital for capturing large-scale building facade point clouds with high time efficiency and high quality. However, existing planning methods are susceptible to low reliability, computational burden and lack of robust registrability assessment solutions, especially for a large-scale task. Therefore, this paper proposes a 3D model-based TLS observation network planning method for large-scale building facades. Firstly, a simple 3D model is quickly obtained by low-cost unmanned aerial vehicle (UAV) photogrammetry. Secondly, a fast scanning simulation of TLS candidate scan positions is performed. Finally, the TLS network is generated by a weighted greedy algorithm and a registration assessment method. Comprehensive experiments based on simulation and real scanning were conducted for validating the proposed method. Results demonstrated that the planned TLS network was efficient in various complex scenes. Moreover, the proposed method outperformed the 2D model-based method in terms of reliability.