Stop-and-go mode: sensor manipulation as essential as sensor development in terrestrial laser scanning

Abstract

This study was dedicated to illustrating the significance of sensor manipulation in the case of terrestrial laser scanning, which is a field now in quick development. In fact, this quickness was mainly rooted in the emergence of new sensors with better performance, while the implications of sensor manipulation have not been fully recognized by the whole community. For this technical gap, the stop-and-go mapping mode can be reckoned as one of the potential solution plans. Stop-and-go was first proposed to handle the low efficiency of traditional static terrestrial laser scanning, and then, it was re-emphasized to improve the stability of sample collections for the state-of-the-art technology of mobile laser scanning. This work reviewed the previous efforts of trying the stop-and-go mode for improving the performance of static and mobile terrestrial laser scanning and generalized their principles respectively. This work also analyzed its advantages compared to the fully-static and fully-kinematic terrestrial laser scanning, and suggested the plans with more automatic measures for raising the efficacy of terrestrial laser scanning. Overall, this literature review indicated that the stop-and-go mapping mode as a case with generic sense can verify the presumption of sensor manipulation as essential as sensor development.

Figure 1.

(a) The schematic diagram of TLS-system-based stop-and-go mapping principle. (b) The workflow of georeferencing TLS-system-collected point clouds.

Figure 2.

(a) The schematic diagram of MLS-system-based stop-and-go mapping principle. (b) The workflow of georeferencing MLS-system-collected point clouds.

Figure 3.

(a) Illustration of lighting pole reconstruction based on the fully-kinematic MLS data; (b) The same lighting pole reconstruction based on the stop-and-go data mapped by the same MLS system; (c) Illustration of tree reconstruction based on the fully-kinematic MLS data; (d) The same tree reconstruction based on the stop-and-go data mapped by the same MLS system.