The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XL-1
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1, 287–291, 2014
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1, 287–291, 2014

  07 Nov 2014

07 Nov 2014

Registration of time of flight terrestrial laser scanner data for stop-and-go mode

H. Mohammed1, N. M. Alsubaie1, M. Elhabiby2, and N. El-sheimy1 H. Mohammed et al.
  • 1Department of Geomatics Engineering, University of Calgary, 2500 University Dr. NW, Calgary, AB T2N 1N4, Canada
  • 2Public Works Department, Ain Shams University, Cairo, Egypt

Keywords: Stop-and-Go, Time of Flight, Registration, Terrestrial Laser Scanner, Mobile Laser Scanning, Time of Flight

Abstract. Terrestrial Laser Scanners (TLS) are utilized through different data acquisition techniques such as Mobile Laser Scanning (MLS) and the output can be used in different applications such as 3D city modelling, cultural heritage documentations, oil and Gas as built, etc... In this research paper, we will investigate one of the modes of TLS on mobile mapping platform. Namely the Stop-and-Go (SAG) mode. Unlike the continuous mode, the Stop-and-Go mode does not require the use of IMU to estimate the TLS attitude and thus inturn it has an overall reduction in the system cost. Moreover, it decreases the time required for data processing in comparison with the continuous mode. For successful use of SAG mobile mapping in urban areas, it is preferred to use a long range time of flight laser scanner to cover long distances in each scan and minimize the registration error. The problem arise with Long range laser scanners is their low point cloud density. The low point cloud density affects the registration accuracy specially in monitoring applications. The point spacing between points is one of the issues facing the registration especially when the matching points are chosen manually.

Since most of TLS nowadays are equipped with camera on-board we can utilize the camera to get an initial estimate of the registration parameters based on image matching. After having an initial approximation of the registration parameters we feed those parameters to the Iterative Closest Point algorithm to obtain more accurate registration result.