Szczegóły publikacji
Opis bibliograficzny
Evaluation of lidar odometry and mapping based on reference laser scanning / J. KOSZYK, P. Łabędź, K. GRZELKA, A. JASIŃSKA, K. PARGIEŁA, A. MALCZEWSKA, K. STRZĄBAŁA, M. MICHALCZAK, Ł. AMBROZIŃSKI // The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; ISSN 1682-1750. — 2023 — vol. 48-1/W3-2023, s. 79–84. — Bibliogr. s. 83–84, Abstr. — 2nd GEOBENCH Workshop on Evaluation and BENCHmarking of sensors, systems and GEOspatial data in photogrammetry and remote sensing : 23–24 October 2023, Krakow, Poland
Autorzy (9)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 149831 |
|---|---|
| Data dodania do BaDAP | 2023-11-28 |
| Tekst źródłowy | URL |
| DOI | 10.5194/isprs-archives-XLVIII-1-W3-2023-79-2023 |
| Rok publikacji | 2023 |
| Typ publikacji | referat w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Abstract
Simultaneous localization and mapping (SLAM) is essential for the robot to operate in an unknown, vast environment. LiDAR-based SLAM can be utilizable in environments where other sensors cannot deliver reliable measurements. Providing accurate map results requires particular attention due to deviations originating from the device. This study is aimed to assess LiDAR-based mapping quality in a vast environment. The measurements are conducted on a mobile platform. Accuracy of the map collected with the LeGO-LOAM method was performed by making a comparison to a map gathered with geodetic scanning using ICP. The results provided 60% of fitted points in a distance lower than 5 cm and 80% in a distance lower than 10 cm. The findings prove the mileage of the map created with this method for other tasks, including autonomous driving and semantic segmentation.