Planning for terrestrial laser scanning in construction: A review

摘要

Terrestrial Laser Scanning (TLS) is an efficient and reliable method for collecting point clouds which have a range of applications in the Architecture, Engineering and Construction (AEC) domain. To ensure that the acquired point clouds are suitable to any given application, data collection must guarantee that all scanning targets are acquired with the specified data quality, and within time limits. Efficiency of data collection is important to reduce jobsite activity disruptions. Effective and efficient laser scanning data collection can be achieved through a prior planning optimisation process, which can be called Planning for Scanning (P4S). In the construction domain, the P4S problem has attracted increasing interest from the research community and a number of approaches have been proposed.This manuscript presents a systematic review of prior P4S works in the AEC domain and presents a categorisation of point cloud data quality criteria. The review starts with the identification and grouping in three categories of the point cloud data quality criteria that are commonly considered as constraints to the P4S problem. The three categories of data quality criteria include 1) completeness, 2) accuracy and spatial resolution, and 3) ?registrability?. The prior P4S works are then reviewed in a structured way by contrasting them in the way they formulate the P4S optimisation problem: the type of inputs they assume (model and possible scanning locations), the constraints they consider, and the algorithm they utilise to solve the optimisation problem. This work makes two contributions: (1) it identifies gaps in knowledge that require further research such as the need to establish a fully automated scan plan which provides the optimum coverage in construction domain specifically for indoor construction; and (2) it provides a framework ? principally a set of criteria ? for others to compare new P4S methods against the existing state of the art in the field. This will not only be valuable for young researchers who want to start research in solving the P4S problem, but also for the ones already working in the domain to rethink the problem from different perspectives.