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Your search keyword '"Laboratoire d'Electronique, d'Informatique et d'Image UMR CNRS 6306 ( Le2i )"' showing total 4 results
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4 results on '"Laboratoire d'Electronique, d'Informatique et d'Image UMR CNRS 6306 ( Le2i )"'

1. Predictive Control Based on Nonlinear Observer for Muscular Force and Fatigue Model

Author

Toufik Bakir, Sami Othman, B. Bonnard, Laboratoire d'Electronique, d'Informatique et d'Image UMR CNRS 6306 ( Le2i ), Université de Technologie de Belfort-Montbeliard ( UTBM ) -Centre National de la Recherche Scientifique ( CNRS ) -École Nationale Supérieure d'Arts et Métiers ( ENSAM ) -Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Mathematics for Control, Transport and Applications ( McTAO ), Inria Sophia Antipolis - Méditerranée ( CRISAM ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ), Institut de Mathématiques de Bourgogne [Dijon] ( IMB ), Université de Bourgogne ( UB ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire d'automatique et de génie des procédés ( LAGEP ), Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-École Supérieure Chimie Physique Électronique de Lyon-Centre National de la Recherche Scientifique ( CNRS ), Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] (Le2i), Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Mathematics for Control, Transport and Applications (McTAO), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institut de Mathématiques de Bourgogne [Dijon] (IMB), Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université de Bourgogne (UB), Laboratoire d'automatique et de génie des procédés (LAGEP), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École Supérieure Chimie Physique Électronique de Lyon-Centre National de la Recherche Scientifique (CNRS), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Centre National de la Recherche Scientifique (CNRS), Université de Bourgogne (UB)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS), and Université de Lyon-Université de Lyon-École Supérieure de Chimie Physique Électronique de Lyon (CPE)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0209 industrial biotechnology, [SDV.BIO]Life Sciences [q-bio]/Biotechnology, 02 engineering and technology, [SPI.AUTO]Engineering Sciences [physics]/Automatic, [SPI]Engineering Sciences [physics], 03 medical and health sciences, 020901 industrial engineering & automation, 0302 clinical medicine, Control theory, [ SPI.AUTO ] Engineering Sciences [physics]/Automatic, [ SPI ] Engineering Sciences [physics], Muscular force, Functional electrical stimulation, Predictive control, Reinforcement, Simulation, Functional Electrical Stimulation, [ SDV.BIO ] Life Sciences [q-bio]/Biotechnology, Nonlinear observer, Numerical models, Model predictive control, Observateur nonlinéaire, Stimulation électrique fonctionnelle, Commande prédictive, Psychology, 030217 neurology & neurosurgery
Abstract

International audience; The Functional Electrical Stimulation (FES) is used in the case of neurological disorders (paralyzed muscles) or the muscle reinforcement (sportsmen). A recent model was proposed coupling a force model and a fatigue model. Based on the specific structure of the model, we present a predictive control scheme using online estimation of the fatigue variables with a nonlinear observer. It is numerically tested in a preliminary study.

Published
2018
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2. Evolutionary algorithm for positioning cameras networks mounted on UAV

Author

David Fofi, Olivier Morel, David Strubel, Naufal M. Saad, Laboratoire d'Electronique, d'Informatique et d'Image UMR CNRS 6306 ( Le2i ), Université de Technologie de Belfort-Montbeliard ( UTBM ) -Centre National de la Recherche Scientifique ( CNRS ) -École Nationale Supérieure d'Arts et Métiers ( ENSAM ) -Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] (Le2i), Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)

Subjects
Optimization, Coverage, [ INFO ] Computer Science [cs], Application, Computer science, UAV, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Evolutionary algorithm, 02 engineering and technology, indoor environment, genetic algorithms, Set (abstract data type), 0203 mechanical engineering, mobile robots, Position (vector), cameras, Robot sensing systems, [ INFO.INFO-TI ] Computer Science [cs]/Image Processing, Algorithm design and analysis, 0202 electrical engineering, electronic engineering, information engineering, [INFO]Computer Science [cs], Computer vision, particle swarm optimisation, [ INFO.INFO-DS ] Computer Science [cs]/Data Structures and Algorithms [cs.DS], Genetic Algorithm, evolutionary algorithm, cameras networks positioning, particle swarm optimization, business.industry, GA, PSO, Shape, Particle swarm optimization, Biological cells, 020206 networking & telecommunications, 020302 automobile design & engineering, Outdoor area, robot vision, Cost function, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Satellite, Algorithm design, Artificial intelligence, unmanned aerial vehicles, autonomous aerial vehicles, business, Mosaic, satellite images
Abstract

International audience; This paper aims to optimize the coverage of a given area from a set of views to allow a complete mosaicing. Among the investigated methods to find the best camera positions, two of them are studied, namely the Particle Swarm Optimization (PSO) and the Genetic Algorithms (GA). After having performed experiments to compare the algorithms, the hybridization of GA and PSO is investigated. To validate the proposed method, it is simulated area of irregular shapes with the cameras mounted on a Unmanned Aerial Vehicles (UAVs). V-REP is used to simulate the UAVs in an indoor environment and satellite images are used for a large outdoor area. The simulation validates the efficiency of the proposed method to find the optimal position of cameras. Then by using the images acquired it is possible to monitor the area and to compute a full mosaic of it.

Published
2017
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3. Mechanism of Integrating Force and Vibrotactile Cues for 3D User Interaction within Virtual Environments

Author

Frédéric Merienne, Yaoping Hu, Aida Erfanian, Stanley Tarng, Jeremy Plouzeau, University of Calgary, Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] (Le2i), Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Electronique, d'Informatique et d'Image UMR CNRS 6306 ( Le2i ), and Université de Technologie de Belfort-Montbeliard ( UTBM ) -Centre National de la Recherche Scientifique ( CNRS ) -École Nationale Supérieure d'Arts et Métiers ( ENSAM ) -Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement

Subjects
3D interaction, Computer science, InformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g.,HCI), Synthèse d'image et réalité virtuelle [Informatique], Haptics, Virtual reality, 050105 experimental psychology, Task (project management), 03 medical and health sciences, 0302 clinical medicine, [ INFO.INFO-HC ] Computer Science [cs]/Human-Computer Interaction [cs.HC], Human–computer interaction, 0501 psychology and cognitive sciences, Computer vision, [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], Sensory cue, Haptic technology, Mechanism (biology), business.industry, 05 social sciences, 3D user interaction, [ INFO.INFO-GR ] Computer Science [cs]/Graphics [cs.GR], [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Interface homme-machine [Informatique], Artificial intelligence, business, 030217 neurology & neurosurgery
Abstract

International audience; Proper integration of sensory cues facilitates 3D user interaction within virtual environments (VEs). Studies showed that the integration of visual and haptic cues follows maximum likelihood estimation (MLE). Little effort focuses however on the mechanism of integrating force and vibrotactile cues. We thus investigated MLE's suitability for integrating these cues. Within a VE, human users undertook 3D interaction of navigating a flying drone along a high-voltage transmission line for inspection. The users received individual force or vibrotactile cues, and their combinations in collocated and dislocated settings. The users' task performance including completion time and accuracy was assessed under each individual cue and setting. The presence of the vibrotactile cue promoted a better performance than the force cue alone. This agreed with the applicability of tactile cues for sensing 3D surfaces, herein setting a baseline for using MLE. The task performance under the collocated setting indicated a degree of combining the individual cues. In contrast, the performance under the dislocated setting was alike under the individual vibrotactile cue. These observations imply a possible role of MLE in integrating force and vibrotactile cues for 3D user interaction within VEs.

Published
2017
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4. Force and vibrotactile integration for 3D user interaction within virtual environments

Author

Yaoping Hu, Stanley Tarng, Jeremy Plouzeau, Frederic Merriene, Aida Erfanian, University of Calgary, Laboratoire d'Electronique, d'Informatique et d'Image UMR CNRS 6306 ( Le2i ), Université de Technologie de Belfort-Montbeliard ( UTBM ) -Centre National de la Recherche Scientifique ( CNRS ) -École Nationale Supérieure d'Arts et Métiers ( ENSAM ) -Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] (Le2i), Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)

Subjects
Computer science, InformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g.,HCI), Synthèse d'image et réalité virtuelle [Informatique], Maximum likelihood, Stereoscopy, 050105 experimental psychology, law.invention, Task (project management), Sensory integration, 03 medical and health sciences, 0302 clinical medicine, [ INFO.INFO-HC ] Computer Science [cs]/Human-Computer Interaction [cs.HC], law, Human–computer interaction, 0501 psychology and cognitive sciences, Computer vision, [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], Sensory cue, Haptic technology, Modality (human–computer interaction), 3D user interaction, User performance, business.industry, 05 social sciences, [ INFO.INFO-GR ] Computer Science [cs]/Graphics [cs.GR], Maximum likelihood estimation, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Interface homme-machine [Informatique], Artificial intelligence, Completion time, business, 030217 neurology & neurosurgery, Force and vibrotactile cues
Abstract

International audience; Proper integration of sensory cues facilitates 3D user interaction within virtual environments (VEs). Studies on multi-sensory integration of visual and haptic cues revealed that the integration follows maximum likelihood estimation (MLE). Little effort focuses however on integrating force and vibrotactile cues - two sub-categorical cues of the haptic modality. Hence, this paper presents an investigation on MLE's suitability for integrating these sub-categorical cues. Within a stereoscopic VE, human users performed a 3D interactive task of navigating a flying drone along a high-voltage transmission line in an inaccessible region and identifying defects on the line. The users had to identify defects via individual force or vibrotactile cues, and their combinations in co-located and dislocated settings. The co-located setting provided both cues on the right hand of the users; whereas the dislocated setting delivered the force and vibrotactile cues on the right hand and forearm of the users, respectively. Task performance of the users, such as completion time and accuracy, was assessed under each cue and setting. The presence of the vibrotactile cue promoted a better performance than the force cue alone. This was in agreement with the role of tactile cues in sensing surface properties, herein setting a baseline for using MLE. The task performance under the co-located setting indicated certain degrees of combining those under the individual cues. In contrast, the performance under the dislocated setting was alike that under the individual vibrotactile cue. These observations imply an inconclusiveness of MLE to integrate both cues in a co-located setting for 3D user interaction.

Published
2017
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