COMBINING LIDAR SLAM AND DEEP LEARNING-BASED PEOPLE DETECTION FOR AUTONOMOUS INDOOR MAPPING IN A CROWDED ENVIRONMENT
| Autor: | D. Tiozzo Fasiolo, E. Maset, L. Scalera, S. O. Macaulay, A. Gasparetto, A. Fusiello |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B1-2022, Pp 447-452 (2022) |
| Druh dokumentu: | article |
| ISSN: | 1682-1750 2194-9034 |
| DOI: | 10.5194/isprs-archives-XLIII-B1-2022-447-2022 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
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