Touch-based admittance control of a robotic arm using neural learning of an artificial skin
| Autor: | Philippe Gaussier, Artem Melnyk, Ganna Pugach, Alexandre Pitti, O.I. Tolochko |
|---|---|
| Přispěvatelé: | Equipes Traitement de l'Information et Systèmes (ETIS - UMR 8051), Ecole Nationale Supérieure de l'Electronique et de ses Applications (ENSEA)-Centre National de la Recherche Scientifique (CNRS)-CY Cergy Paris Université (CY), National Technical University of Donetsk (DONTU), CY Cergy Paris Université (CY)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de l'Electronique et de ses Applications (ENSEA), Neurocybernétique, CY Cergy Paris Université (CY)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de l'Electronique et de ses Applications (ENSEA)-CY Cergy Paris Université (CY)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de l'Electronique et de ses Applications (ENSEA), National Technical University 'Kharkiv Polytechnic Institute' (NTUKPI), Neurocybernetics, Pitti, Alexandre |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Engineering Robot kinematics Admittance business.industry [INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO] 02 engineering and technology Degrees of freedom (mechanics) [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE] 020901 industrial engineering & automation [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Receptive field Touch Perception 0202 electrical engineering electronic engineering information engineering Torque [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO] 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Robotic arm Humanoid robot Simulation ComputingMilieux_MISCELLANEOUS |
| Zdroj: | Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on, Oct 2016, Daejeon, South Korea. pp.3374-33803374-3380, ⟨10.1109/IROS.2016.7759519⟩ IROS IROS, Oct 2016, Daejon, South Korea HAL |
| DOI: | 10.1109/IROS.2016.7759519⟩ |
| Popis: | International audience; Touch perception is an important sense to model in humanoid robots to interact physically and socially with humans. We present a neural controller that can adapt the compliance of the robot arm in four directions using as input the tactile information from an artificial skin and as output the estimated torque for admittance control-loop reference. This adaption is done in a self-organized fashion with a neural system that learns first the topology of the tactile map when we touch it and associates a torque vector to move the arm in the corresponding direction. The artificial skin is based on a large area piezoresistive tactile device (ungridded) that changes its electrical properties in the presence of the contact. Our results show the self-calibration of a robotic arm (2 degrees of freedom) controlled in the four directions and derived combination vectors, by the soft touch on all the tactile surface, even when the torque is not detectable (force applied near the joint). The neural system associates each tactile receptive field with one direction and the correct force. We show that the tactile-motor learning gives better interactive experiments than the admittance control of the robotic arm only. Our method can be used in the future for humanoid adaptive interaction with a human partner. |
| Databáze: | OpenAIRE |
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