Automatically Annotated Dataset of a Ground Mobile Robot in Natural Environments via Gazebo Simulations
This paper presents a new synthetic dataset obtained from Gazebo simulations of an Unmanned Ground Vehicle (UGV) moving on different natural environments. To this end, a Husky mobile robot equipped with a tridimensional (3D) Light Detection and Ranging (LiDAR) sensor, a stereo camera, a Global Navig...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/15/5599 |
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| author | Manuel Sánchez Jesús Morales Jorge L. Martínez J. J. Fernández-Lozano Alfonso García-Cerezo |
| author_facet | Manuel Sánchez Jesús Morales Jorge L. Martínez J. J. Fernández-Lozano Alfonso García-Cerezo |
| author_sort | Manuel Sánchez |
| collection | DOAJ |
| description | This paper presents a new synthetic dataset obtained from Gazebo simulations of an Unmanned Ground Vehicle (UGV) moving on different natural environments. To this end, a Husky mobile robot equipped with a tridimensional (3D) Light Detection and Ranging (LiDAR) sensor, a stereo camera, a Global Navigation Satellite System (GNSS) receiver, an Inertial Measurement Unit (IMU) and wheel tachometers has followed several paths using the Robot Operating System (ROS). Both points from LiDAR scans and pixels from camera images, have been automatically labeled into their corresponding object class. For this purpose, unique reflectivity values and flat colors have been assigned to each object present in the modeled environments. As a result, a public dataset, which also includes 3D pose ground-truth, is provided as ROS bag files and as human-readable data. Potential applications include supervised learning and benchmarking for UGV navigation on natural environments. Moreover, to allow researchers to easily modify the dataset or to directly use the simulations, the required code has also been released. |
| first_indexed | 2024-03-09T10:05:32Z |
| format | Article |
| id | doaj.art-7acee4c47b244e2c8314222666b0a679 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T10:05:32Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-7acee4c47b244e2c8314222666b0a6792023-12-01T23:09:29ZengMDPI AGSensors1424-82202022-07-012215559910.3390/s22155599Automatically Annotated Dataset of a Ground Mobile Robot in Natural Environments via Gazebo SimulationsManuel Sánchez0Jesús Morales1Jorge L. Martínez2J. J. Fernández-Lozano3Alfonso García-Cerezo4Robotics and Mechatronics Lab, Andalucía Tech, Universidad de Málaga, 29071 Málaga, SpainRobotics and Mechatronics Lab, Andalucía Tech, Universidad de Málaga, 29071 Málaga, SpainRobotics and Mechatronics Lab, Andalucía Tech, Universidad de Málaga, 29071 Málaga, SpainRobotics and Mechatronics Lab, Andalucía Tech, Universidad de Málaga, 29071 Málaga, SpainRobotics and Mechatronics Lab, Andalucía Tech, Universidad de Málaga, 29071 Málaga, SpainThis paper presents a new synthetic dataset obtained from Gazebo simulations of an Unmanned Ground Vehicle (UGV) moving on different natural environments. To this end, a Husky mobile robot equipped with a tridimensional (3D) Light Detection and Ranging (LiDAR) sensor, a stereo camera, a Global Navigation Satellite System (GNSS) receiver, an Inertial Measurement Unit (IMU) and wheel tachometers has followed several paths using the Robot Operating System (ROS). Both points from LiDAR scans and pixels from camera images, have been automatically labeled into their corresponding object class. For this purpose, unique reflectivity values and flat colors have been assigned to each object present in the modeled environments. As a result, a public dataset, which also includes 3D pose ground-truth, is provided as ROS bag files and as human-readable data. Potential applications include supervised learning and benchmarking for UGV navigation on natural environments. Moreover, to allow researchers to easily modify the dataset or to directly use the simulations, the required code has also been released.https://www.mdpi.com/1424-8220/22/15/5599synthetic datasetGazebo simulatorUGV navigationnatural environmentsautomatic data labeling3D LiDAR |
| spellingShingle | Manuel Sánchez Jesús Morales Jorge L. Martínez J. J. Fernández-Lozano Alfonso García-Cerezo Automatically Annotated Dataset of a Ground Mobile Robot in Natural Environments via Gazebo Simulations Sensors synthetic dataset Gazebo simulator UGV navigation natural environments automatic data labeling 3D LiDAR |
| title | Automatically Annotated Dataset of a Ground Mobile Robot in Natural Environments via Gazebo Simulations |
| title_full | Automatically Annotated Dataset of a Ground Mobile Robot in Natural Environments via Gazebo Simulations |
| title_fullStr | Automatically Annotated Dataset of a Ground Mobile Robot in Natural Environments via Gazebo Simulations |
| title_full_unstemmed | Automatically Annotated Dataset of a Ground Mobile Robot in Natural Environments via Gazebo Simulations |
| title_short | Automatically Annotated Dataset of a Ground Mobile Robot in Natural Environments via Gazebo Simulations |
| title_sort | automatically annotated dataset of a ground mobile robot in natural environments via gazebo simulations |
| topic | synthetic dataset Gazebo simulator UGV navigation natural environments automatic data labeling 3D LiDAR |
| url | https://www.mdpi.com/1424-8220/22/15/5599 |
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