| Autor: |
Manuel Sánchez, Jesús Morales, Jorge L. Martínez |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Machines, Vol 11, Iss 8, p 807 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2075-1702 |
| DOI: |
10.3390/machines11080807 |
| Popis: |
Moving on paths or trails present in natural environments makes autonomous navigation of unmanned ground vehicles (UGV) simpler and safer. In this sense, aerial photographs provide a lot of information of wide areas that can be employed to detect paths for UGV usage. This paper proposes the extraction of paths from a geo-referenced satellite image centered at the current UGV position. Its pixels are individually classified as being part of a path or not using a convolutional neural network (CNN) which has been trained using synthetic data. Then, successive distant waypoints inside the detected paths are generated to achieve a given goal. This processing has been successfully tested on the Andabata mobile robot, which follows the list of waypoints in a reactive way based on a three-dimensional (3D) light detection and ranging (LiDAR) sensor. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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