A Vision-Driven Collaborative Robotic Grasping System Tele-Operated by Surface Electromyography
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Título: | A Vision-Driven Collaborative Robotic Grasping System Tele-Operated by Surface Electromyography |
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Autor/es: | Úbeda, Andrés | Zapata-Impata, Brayan S. | Puente Méndez, Santiago T. | Gil, Pablo | Candelas-Herías, Francisco A. | Torres, Fernando |
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: | Surface electromyography | Computer vision | Grasping | Assistive robotics |
Área/s de conocimiento: | Ingeniería de Sistemas y Automática |
Fecha de publicación: | 20-jul-2018 |
Editor: | MDPI |
Cita bibliográfica: | Úbeda A, Zapata-Impata BS, Puente ST, Gil P, Candelas F, Torres F. A Vision-Driven Collaborative Robotic Grasping System Tele-Operated by Surface Electromyography. Sensors. 2018; 18(7):2366. doi:10.3390/s18072366 |
Resumen: | This paper presents a system that combines computer vision and surface electromyography techniques to perform grasping tasks with a robotic hand. In order to achieve a reliable grasping action, the vision-driven system is used to compute pre-grasping poses of the robotic system based on the analysis of tridimensional object features. Then, the human operator can correct the pre-grasping pose of the robot using surface electromyographic signals from the forearm during wrist flexion and extension. Weak wrist flexions and extensions allow a fine adjustment of the robotic system to grasp the object and finally, when the operator considers that the grasping position is optimal, a strong flexion is performed to initiate the grasping of the object. The system has been tested with several subjects to check its performance showing a grasping accuracy of around 95% of the attempted grasps which increases in more than a 13% the grasping accuracy of previous experiments in which electromyographic control was not implemented. |
Patrocinador/es: | This work was funded by the Spanish Government’s Ministry of Economy, Industry and Competitiveness through the DPI2015-68087-R, by the European Commission’s and FEDER funds through the COMMANDIA (SOE2/P1/F0638) action supported by Interreg-V Sudoe and by University of Alicante through project GRE16-20, Control Platform for a Robotic Hand based on Electromyographic Signals. |
URI: | http://hdl.handle.net/10045/77711 |
ISSN: | 1424-8220 |
DOI: | 10.3390/s18072366 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.3390/s18072366 |
Aparece en las colecciones: | INV - AUROVA - Artículos de Revistas INV - HURO - Artículos de Revistas |
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