Bio-inspired algorithms for tactile control of dexterous manipulation

Few years old children lift and manipulate unfamiliar objects more dexterously than today's robots. Thus, robotics researchers increasingly agree that ideas from biology can strongly benefit the design of autonomous robots. In this paper, bio-inspired algorithms for lifting unfamiliar objects w...

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Autor principal: Herrera, R.M
Formato: Acta de conferencia Capítulo de libro
Lenguaje:Inglés
Publicado: 2012
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100 1 |a Herrera, R.M. 
245 1 0 |a Bio-inspired algorithms for tactile control of dexterous manipulation 
260 |c 2012 
270 1 0 |m Herrera, R.M.; Department of Computer Science, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos AiresArgentina; email: rmatuk@dc.uba.ar 
506 |2 openaire  |e Política editorial 
504 |a Howe, R., Popp, N., Akella, P., Kao, I., Cutkosky, M., Grasping, manipulation and control with tactile sensing (1990) Proc. IEEE Int. Conf. Robotics and Automation, pp. 1258-1263 
504 |a Cutkosky, M., Hyde, J., Manipulation control with dynamic tactile sensing (1993) Proc. of the 6th International Symposium on Robotics Research 
504 |a Israelsson, A., (2002) Simulation of Responses in Afferents from the Glabrous Skin during Human Manipulation, , Master's thesis, Master thesis in Cognitive Science, Umeå University, Umeå, Sweden 
504 |a Johansson, R., Sensory and memory information in the control of dexterous manipulation (1996) Neural Bases of Motor Behaviour, pp. 205-260. , F. Lacquaniti and P. Viviani, Eds. Kluwer Academic Publishers 
504 |a Johansson, R., Sensory control of dexterous manipulation in humans (1996) Hand and Brain: The Neurophysiology and Psychology of Hand Movements, pp. 381-414. , A. Wing, P. Haggard, and J. Flanagan, Eds. Academic Press 
504 |a Gordon, A., Westling, G., Cole, K., Johansson, R., Memory representations underlying motor commands used during manipulation of common and novel objects (1993) Journal of Neurophysiology, 69, pp. 1789-1796 
504 |a Johansson, R., Westling, G., Programmed and triggered actions to rapid load changes during precision grip (1988) Exp Brain Res, 71, pp. 72-86 
504 |a Matuk Herrera, R., Leoni, F., Bio-inspired control of dexterous manipulation (2005) Lecture Notes in Artificial Intelligence, 3809, pp. 1319-1322 
504 |a Johansson, R., Westling, G., Signals in tactile afferents from the fingers eliciting adaptive motor responses during precision grip (1987) Exp Brain Res, 66, pp. 141-154 
504 |a Fagergren, A., Ekeberg, O., Forssberg, H., Control strategies correcting inaccurately programmed fingertip forces: Model predictions derived from human behavior (2003) Journal of Neurophysiology, 89 (6), pp. 2904-2916 
504 |a Johansson, R., Westling, G., Factors influencing the force control during precision grip (1984) Exp Brain Res, 53, pp. 277-284 
504 |a Westling, G., Johansson, R., Responses in glabrous skin mechanoreceptors during precision grip in humans (1987) Exp Brain Res, 66, pp. 128-140 
504 |a Matuk Herrera, R., A bio-inspired method for friction estimation (2008) Advances in Artificial Intelligence, 6th Mexican International Conference on Artificial Intelligence MICAI 2007, pp. 385-395. , IEEE CS Press 
504 |a Matuk Herrera, R., Multilayer perceptrons for bio-inspired friction estimation (2008) Lecture Notes in Artificial Intelligence, 5097, pp. 828-838 
504 |a Matuk Herrera, R., (2008) Dexterous Manipulation in Unknown Environments: A Bioinspired Model, , Ph.D. dissertation, Universidad de Buenos Aires, Argentina 
504 |a Matuk Herrera, R., A bio-inspired method for incipient slip detection (2007) Lecture Notes in Artificial Intelligence, 4830, pp. 347-356 
520 3 |a Few years old children lift and manipulate unfamiliar objects more dexterously than today's robots. Thus, robotics researchers increasingly agree that ideas from biology can strongly benefit the design of autonomous robots. In this paper, bio-inspired algorithms for lifting unfamiliar objects with grasp stability and human-like behavior are presented. In these algorithms, simulated human tactile afferent responses, drive the control of the grip and load forces, and signal important events in the lifting task. The presented model and algorithms follow closely the human behavior in a lifting task, as revealed by neurophysiological studies of human dexterous manipulation. © 2012 IEEE.  |l eng 
593 |a Department of Computer Science, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Argentina 
690 1 0 |a BIO-INSPIRED ALGORITHMS 
690 1 0 |a DEXTEROUS MANIPULATION 
690 1 0 |a HUMAN BEHAVIORS 
690 1 0 |a LOAD FORCES 
690 1 0 |a ALGORITHMS 
690 1 0 |a BEHAVIORAL RESEARCH 
711 2 |c Rome  |d 24 June 2012 through 27 June 2012  |g Código de la conferencia: 93171 
773 0 |d 2012  |h pp. 252-257  |p Proc. IEEE RAS EMBS Int. Conf. Biomed. Rob. Biomechatronics, BioRob  |n Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics  |x 21551774  |z 9781457711992  |t 2012 4th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2012 
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856 4 0 |u https://doi.org/10.1109/BioRob.2012.6290889  |y DOI 
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