| Journal: | Acta scientiarum. Agronomy |
| Database: | PERIÓDICA |
| System number: | 000460089 |
| ISSN: | 1679-9275 |
| Authors: | Guzmán, Leonardo Enrique Solaque1 Acevedo, Marianne Lorena Romero1 Guevara, Adriana Riveros1 |
| Institutions: | 1Universidad Militar Nueva Granada, Bogotá. Colombia |
| Year: | 2019 |
| Volumen: | 41 |
| Country: | Brasil |
| Language: | Inglés |
| Document type: | Artículo |
| Approach: | Experimental, aplicado |
| English abstract | The recent exploration of autonomous robotics tasks in agro-industry has permitted the integration of theories of artificial vision and mobile robotics with tasks in precision agriculture. Artificial vision allows for the classification of weeds and crops from images of plantations. With 3D-image processing systems, the location of the weeds is determined, and then the movement of the tool responsible for eradication is proposed. This article presents the solution for finding weeds within a crop field using classifiers and the integration of a 3D-vision system that builds a point cloud featuring the plants to safeguard, the weeds and the free space using Zed technology. With this information, search techniques such as A* (A star) and RRT (Rapidly exploring Random Tree) are used to determine the trajectory that the weed-removal tool must follow. The last feature is an integral part of an XYZ-positioning system, and this is part of a mobile robot dedicated to precision agriculture tasks |
| Disciplines: | Agrociencias, Ciencias de la computación |
| Keyword: | Malezas, Inteligencia artificial, Robótica, Robots móviles, Agricultura de precisión |
| Keyword: | Weeds, Artificial intelligence, Robotics, Mobile robot, Precision agriculture |
| Full text: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
