Domestic waste detection and grasping points for robotic picking up
| Autor: | Gea, Víctor de, Puente Méndez, Santiago T., Gil, Pablo |
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| Přispěvatelé: | Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal, Universidad de Alicante. Instituto Universitario de Investigación Informática, Automática, Robótica y Visión Artificial |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Computer Science - Machine Learning Domestic waste Computer Vision and Pattern Recognition (cs.CV) Computer Science - Computer Vision and Pattern Recognition Robotic Grasping Deep learning Machine Learning (cs.LG) 3D Points Grasping Geograsp Computer Science - Robotics Object Detection Mask-RCNN Robotics (cs.RO) Ingeniería de Sistemas y Automática |
| Zdroj: | RUA. Repositorio Institucional de la Universidad de Alicante Universidad de Alicante (UA) |
| Popis: | This paper presents an AI system applied to location and robotic grasping. Experimental setup is based on a parameter study to train a deep-learning network based on Mask-RCNN to perform waste location in indoor and outdoor environment, using five different classes and generating a new waste dataset. Initially the AI system obtain the RGBD data of the environment, followed by the detection of objects using the neural network. Later, the 3D object shape is computed using the network result and the depth channel. Finally, the shape is used to compute grasping for a robot arm with a two-finger gripper. The objective is to classify the waste in groups to improve a recycling strategy. Comment: 2 pages, 3 figures, accepted as poster for presentation in ICRA 2021 Workshop: Emerging paradigms for robotic manipulation: from the lab to the productive world |
| Databáze: | OpenAIRE |
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