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, 447–452, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-447-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 447–452, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-447-2022
 
30 May 2022
30 May 2022

COMBINING LIDAR SLAM AND DEEP LEARNING-BASED PEOPLE DETECTION FOR AUTONOMOUS INDOOR MAPPING IN A CROWDED ENVIRONMENT

D. Tiozzo Fasiolo, E. Maset, L. Scalera, S. O. Macaulay, A. Gasparetto, and A. Fusiello D. Tiozzo Fasiolo et al.
  • Polytechnic Department of Engineering and Architecture (DPIA), University of Udine, Udine, Italy

Keywords: Mobile Robotics, Laser Scanning, Simultaneous Localization and Mapping, People Detection, Deep Learning, Indoor Mapping

Abstract. In this paper, we present a mapping system based on an autonomous mobile robot equipped with a LiDAR device and a camera, that can deal with the presence of people. Thanks to a deep learning approach, the position of humans is identified and a new surveying path is planned that brings the robot to scan occluded areas, so as to obtain a complete point cloud of the environment. Experimental results are performed with a wheeled mobile robot in different crowded scenarios, showing the applicability of the proposed approach to perform an autonomous survey avoiding occlusions and automatically removing from the map noisy and spurious objects caused by people presence.