Artículo

Matuk Herrera, R. "Multilayer perceptrons for bio-inspired friction estimation" (2008) 9th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2008. 5097 LNAI:828-838
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Abstract:

Few years old children lift and manipulate unfamiliar objects more dexterously than today's robots. Therefore, it has arisen an interest at the artificial intelligence community to look for inspiration on neurophysiological studies to design better models for the robots. The estimation of the friction coefficient of the object's material is a crucial information in a human dexterous manipulation. Humans estimate the friction coefficient based on the responses of their tactile mechanoreceptors. In this paper, finite element analysis was used to model a finger and an object. Simulated human afferent responses were then obtained for different friction coefficients. Multiple multilayer perceptrons that received as input simulated human afferent responses, and gave as output an estimation of the friction coefficient, were trained and tested. A performance analysis was carried out to verify the influence of the following factors: number of hidden neurons, compression ratio of the input pattern, partitions of the input pattern. © 2008 Springer-Verlag Berlin Heidelberg.

Registro:

Documento: Artículo
Título:Multilayer perceptrons for bio-inspired friction estimation
Autor:Matuk Herrera, R.
Ciudad:Zakopane
Filiación:Department of Computer Science, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Argentina
Palabras clave:Artificial intelligence; Bionics; Compression ratio (machinery); Cybernetics; Electric loads; Estimation; Finite element method; Machine design; Multilayers; Neural networks; Pattern recognition systems; Robotics; Soft computing; Tribology; Bio-inspired; Compression ratios; Dexterous manipulation; Finite element analysis; Friction co-efficient; Friction estimation; Hidden neurons; Input patterns; Intelligence communities; International conferences; Mechanoreceptors; Multi-layer perceptrons; Performance analyses; Friction
Año:2008
Volumen:5097 LNAI
Página de inicio:828
Página de fin:838
DOI: http://dx.doi.org/10.1007/978-3-540-69731-2_79
Título revista:9th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2008
Título revista abreviado:Lect. Notes Comput. Sci.
ISSN:03029743
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v5097LNAI_n_p828_MatukHerrera

Referencias:

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  • 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
  • Matuk Herrera, R., A bio-inspired method for friction estimation (2007) Proc. of MICAI, , IEEE CS Press, Los Alamitos
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Citas:

---------- APA ----------
(2008) . Multilayer perceptrons for bio-inspired friction estimation. 9th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2008, 5097 LNAI, 828-838.
http://dx.doi.org/10.1007/978-3-540-69731-2_79
---------- CHICAGO ----------
Matuk Herrera, R. "Multilayer perceptrons for bio-inspired friction estimation" . 9th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2008 5097 LNAI (2008) : 828-838.
http://dx.doi.org/10.1007/978-3-540-69731-2_79
---------- MLA ----------
Matuk Herrera, R. "Multilayer perceptrons for bio-inspired friction estimation" . 9th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2008, vol. 5097 LNAI, 2008, pp. 828-838.
http://dx.doi.org/10.1007/978-3-540-69731-2_79
---------- VANCOUVER ----------
Matuk Herrera, R. Multilayer perceptrons for bio-inspired friction estimation. Lect. Notes Comput. Sci. 2008;5097 LNAI:828-838.
http://dx.doi.org/10.1007/978-3-540-69731-2_79