Detection and location of domestic waste for planning its collection using an autonomous robot
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http://hdl.handle.net/10045/123444
Título: | Detection and location of domestic waste for planning its collection using an autonomous robot |
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Autor/es: | Tornero, Pascual | Puente Méndez, Santiago T. | Gil, Pablo |
Grupo/s de investigación o GITE: | Automática, Robótica y Visión Artificial |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal | Universidad de Alicante. Instituto Universitario de Investigación Informática |
Palabras clave: | Detection and location objects | Domestic waste | Autonomous robot | Robot navigation | Deep learning |
Área/s de conocimiento: | Ingeniería de Sistemas y Automática |
Fecha de publicación: | 8-abr-2022 |
Editor: | IEEE |
Resumen: | This paper presents an approach of a detection and location system for waste recognition in outdoor environments that can be usable on an autonomous robot for garbage collection. It is composed of a camera and a LiDAR. For the detection task, some YOLO models were trained and tested for classification of waste by using a own dataset acquired from the camera. The image coordinates predicted by the best detector are used in order to compute the location relative to the camera. Then, we used the LiDAR to get a global waste location relative to the robot, transforming the coordinates of the center of each trash instance. Our detection approach was tested in outdoor environments obtaining a mAP@.5 around 0.99 and a mAP@.95 over 0.84, and an average time of detection less than 40 ms., being able to make it in real time. The location method was also tested in presence of objects at a maximum distance of 8 m., obtaining an average error smaller than 0.25 m. |
Descripción: | Paper submitted to the 8th International Conference on Control, Automation and Robotics (ICCAR), Xiamen, China, April 8-10, 2022. |
Patrocinador/es: | This research was funded by Spanish Government through the project RTI2018-094279-B-I00. Besides, computer facilities were provided by Valencian Government and FEDER through the IDIFEFER/2020/003. |
URI: | http://hdl.handle.net/10045/123444 |
ISBN: | 978-1-6654-8116-8 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/conferenceObject |
Derechos: | © The authors |
Revisión científica: | si |
Aparece en las colecciones: | INV - AUROVA - Comunicaciones a Congresos Internacionales |
Archivos en este ítem:
Archivo | Descripción | Tamaño | Formato | |
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SII_ICCAR_2022.pdf | Versión Preprint antes de publicación. | 65,18 MB | Adobe PDF | Abrir Vista previa |
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