ConSLAM: Construction Data Set for SLAM
| Autor: | Maciej Trzeciak, Kacper Pluta, Yasmin Fathy, Lucio Alcalde, Stanley Chee, Antony Bromley, Ioannis Brilakis, Pierre Alliez |
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| Přispěvatelé: | University of Cambridge [UK] (CAM), Geometric Modeling of 3D Environments (TITANE), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laing O'Rourke, Trzeciak, M [0000-0001-8188-487X], Fathy, Y [0000-0001-7398-5283], Brilakis, I [0000-0003-1829-2083], Alliez, P [0000-0002-6214-4005], Apollo - University of Cambridge Repository |
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Journal of Computing in Civil Engineering Journal of Computing in Civil Engineering, 2023, 37 (3), ⟨10.1061/JCCEE5.CPENG-5212⟩ |
| ISSN: | 0887-3801 |
| Popis: | International audience; This paper presents a dataset collected periodically on a construction site. The dataset aims to evaluate the performance of SLAM algorithms used by mobile scanners or autonomous robots. It includes ground-truth scans of a construction site collected using a terrestrial laser scanner along with five sequences of spatially registered and time-synchronized images, LiDAR scans and inertial data coming from our prototypical hand-held scanner. We also recover the ground-truth trajectory of the mobile scanner by registering the sequential LiDAR scans to the ground-truth scans and show how to use a popular software package to measure the accuracy of SLAM algorithms against our trajectory automatically. To the best of our knowledge, this is the first publicly accessible dataset consisting of periodically collected sequential data on a construction site. |
| Databáze: | OpenAIRE |
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