2026-05-30T08:02:04Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/296072026-02-03T12:14:17Zcom_10630_2254col_10630_37959

Automatic Generation of Labeled 3D Point Clouds of Natural Environments with Gazebo. Sánchez, Manuel Martínez-Rodríguez, Jorge Luis Morales-Rodríguez, Jesús Robles, Alfredo Moran Prados, Mariano Vehículos autodirigidos Aprendizaje automático (Inteligencia artificial) Progress in applying supervised learning for nat- ural scene classification is impeded by the lack of appropriate datasets for training. This paper describes the automatic generation of synthetic three-dimensional (3D) scans of natural environments with each point labelled individually with its element class. The developed software employs the robotic simulator Gazebo to obtain range and intensity measurements from a 3D laser rangefinder aboard a ground mobile robot. Precisely, the returned intensity values are used to annotate every 3D point within its corresponding class 100% error free. Several examples are provided to show the utility of the proposed approach. 2024-02-01T11:56:02Z 2024-02-01T11:56:02Z 2024-02-01T11:56:02Z 2019-05-27 conference output M. Sánchez, J. L. Martínez, J. Morales, A. Robles and M. Morán, "Automatic Generation of Labeled 3D Point Clouds of Natural Environments with Gazebo," 2019 IEEE International Conference on Mechatronics (ICM), Ilmenau, Germany, 2019, pp. 161-166, doi: 10.1109/ICMECH.2019.8722866. https://hdl.handle.net/10630/29607 10.1109/icmech.2019.8722866 eng 2019 IEEE International Conference on Mechatronics (ICM) Ilmenau (Alemania) 18-20 March 2019 http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional IEEE