Manipulación visual-táctil para la recogida de residuos domésticos en exteriores
[EN] This work presents a perception system applied to robotic manipulation, that is able to assist in navegation, household waste classification and collection in outdoor environments. This system is made up of optical tactile sensors, RGBD cameras and a LiDAR. These sensors are integrated on a mob...
| Autores: | , , , |
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| Formato: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Recursos: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | español |
| OAI Identifier: | oai:riunet.upv.es:10251/192800 |
| Acesso em linha: | https://riunet.upv.es/handle/10251/192800 |
| Access Level: | acceso abierto |
| Palavra-chave: | Visual detection Object recognition Object location Tactile perception Robotic manipulation Detección visual Reconocimiento de objetos Localización de objetos Percepción táctil Manipulación robótica |
| Resumo: | [EN] This work presents a perception system applied to robotic manipulation, that is able to assist in navegation, household waste classification and collection in outdoor environments. This system is made up of optical tactile sensors, RGBD cameras and a LiDAR. These sensors are integrated on a mobile platform with a robot manipulator and a robotic gripper. Our system is divided in three software modules, two of them are vision-based and the last one is tactile-based. The vision-based modules use CNNs to localize and recognize solid household waste, together with the grasping points estimation. The tactile-based module, which also uses CNNs and image processing, adjusts the gripper opening to control the grasping from touch data. Our proposal achieves localization errors around 6 %, a recognition accuracy of 98% and ensures the grasping stability the 91% of the attempts. The sum of runtimes of the three modules is less than 750 ms. |
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