The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B1-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 181–187, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-181-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 181–187, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-181-2022
 
30 May 2022
30 May 2022

THE USE OF A WIDE FOV LASER SCANNING SYSTEM AND A SLAM ALGORITHM FOR MOBILE APPLICATIONS

L. F. Castanheiro1, A. M. G. Tommaselli1, M. V. Machado1, G. H. Santos1, I. S. Norberto1, and T. T. Reis2 L. F. Castanheiro et al.
  • 1Department of Cartography, São Paulo State University (UNESP) at Presidente Prudente, São Paulo 19060-900, Brazil
  • 2T2R Soluções at Presidente Prudente, São Paulo, 19050-310, Brazil

Keywords: laser point cloud, wide-angle laser, multi-beam laser, mobile mapping, SLAM, backpack mobile system

Abstract. This paper presents the assessment of a wide-angle laser scanner and a simultaneous localisation and mapping (SLAM) algorithm to estimate the trajectory and generate a 3D map of the environment. A backpack platform composed of an OS0-128 Ouster (FoV 90° × 360°) laser scanner was used to acquire laser data in an area with urban and forest features. Web SLAM, an online SLAM algorithm implemented by Ouster, Inc., was used to estimate the trajectory and generate a 3D map in a local reference system. Then, the 3D point clouds were transformed into the ground coordinate system with a rigid body transformation. Three datasets were used: (I) the entire trajectory consisting of forwarding and backwards paths, (II) only forward path, and (III) only backward path. Visual analysis showed a double mapping error in the point cloud of dataset I. Therefore, the point cloud registration was performed only for datasets II and III, achieving a centimetric accuracy, which is compatible with the OS0-128 laser scanner accuracy (∼5cm).