The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLII-2/W17
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W17, 149–156, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W17-149-2019
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W17, 149–156, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W17-149-2019

  29 Nov 2019

29 Nov 2019

INTEGRATING A LOW-COST MEMS IMU INTO A LASER-BASED SLAM FOR INDOOR MOBILE MAPPING

S. Karam, V. Lehtola, and G. Vosselman S. Karam et al.
  • Dept. of Earth Observation Science, Faculty ITC, University of Twente, 7514 AE Enschede, The Netherlands

Keywords: indoor mapping, mobile laser scanning, SLAM, IMU, integration, point clouds, 2D laser scanner

Abstract. Indoor mapping techniques are highly important in many applications, such as human navigation and indoor modelling. As satellite positioning systems do not work in indoor applications, several alternative navigational sensors and methods have been used to provide accurate indoor positioning for mapping purposes, such as inertial measurement units (IMUs) and simultaneous localisation and mapping algorithms (SLAM). In this paper, we investigate the benefits that the integration of a low-cost microelectromechanical system (MEMS) IMU can bring to a feature-based SLAM algorithm. Specifically, we utilize IMU data to predict the pose of our backpack indoor mobile mapping system to improve the SLAM algorithm. The experimental results show that using the proposed IMU integration method leads into a more robust data association between the measured points and the model planes. Notably, the number of points that are assigned to the model planes is increased, and the root mean square error (RMSE) of the residuals, i.e. distances between these measured points and the model planes, is decreased significantly from 1.8 cm to 1.3 cm.