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Open AccessArticle

Intelligent Multimodal Framework for Human Assistive Robotics Based on Computer Vision Algorithms

1
Institute for Research and Innovation in Bioengineering, Universitat Politècnica de València, 46022 Valencia, Spain
2
Biomedical Neuroengineering Group, Universidad Miguel Hernández de Elche, 03202 Elche, Spain
*
Authors to whom correspondence should be addressed.
Sensors 2018, 18(8), 2408; https://doi.org/10.3390/s18082408
Received: 4 July 2018 / Revised: 18 July 2018 / Accepted: 23 July 2018 / Published: 24 July 2018
(This article belongs to the Special Issue Assistance Robotics and Biosensors)
Assistive technologies help all persons with disabilities to improve their accessibility in all aspects of their life. The AIDE European project contributes to the improvement of current assistive technologies by developing and testing a modular and adaptive multimodal interface customizable to the individual needs of people with disabilities. This paper describes the computer vision algorithms part of the multimodal interface developed inside the AIDE European project. The main contribution of this computer vision part is the integration with the robotic system and with the other sensory systems (electrooculography (EOG) and electroencephalography (EEG)). The technical achievements solved herein are the algorithm for the selection of objects using the gaze, and especially the state-of-the-art algorithm for the efficient detection and pose estimation of textureless objects. These algorithms were tested in real conditions, and were thoroughly evaluated both qualitatively and quantitatively. The experimental results of the object selection algorithm were excellent (object selection over 90%) in less than 12 s. The detection and pose estimation algorithms evaluated using the LINEMOD database were similar to the state-of-the-art method, and were the most computationally efficient. View Full-Text
Keywords: 3D object detection and pose estimation; assistive robotics; eye-tracking; human–computer interface 3D object detection and pose estimation; assistive robotics; eye-tracking; human–computer interface
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Ivorra, E.; Ortega, M.; Catalán, J.M.; Ezquerro, S.; Lledó, L.D.; Garcia-Aracil, N.; Alcañiz, M. Intelligent Multimodal Framework for Human Assistive Robotics Based on Computer Vision Algorithms. Sensors 2018, 18, 2408.

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