60documents trouvés
Optimizing humanoid motions using recursive dynamics and lie groups
W.SULEIMAN, E.YOSHIDA, J.P.LAUMOND, A.MONIN
MRS, AIST, GEPETTO
Manifestation avec acte : 3rd International Conference on Information & Communication Technologies: from Theory to Applications (ICTTA'08), Damas (Syrie), 7-11 Avril 2008, 6p. , N° 08203
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Abstract
In this paper, we present a recursive method for the optimization of humanoid robot motions. The method is based on an efficient dynamics algorithm, which allows the calculation of the gradient function with respect to the control parameters analytically. The algorithm makes use of the theory of Lie groups and Lie algebra. The main objective of this method is to smooth the pre-calculated humanoid motions by minimizing the efforts, and at the same time improving the stability of the humanoid robot during the execution of the planned tasks. Experimental results using HRP-2 platform are provided to validate the proposed method.
GPS based land vehicle positionning using Gaussian sum filters
A.KIBANGOU, A.MONIN
MRS
Manifestation avec acte : 2008 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Las Vegas (USA), 30 Mars - 4 avril 2008, 4p. , N° 08438
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Mots-Clés / Keywords
GPS; Land vehicles; Nonlinear filtering; Jump processes;
New method for identifying a finite degree Volterra series
W.SULEIMAN, A.MONIN
MRS
Revue Scientifique : Automatica, Vol.44, N°2, pp.488-497, Février 2008 , N° 06475
Lien : http://hal.archives-ouvertes.fr/hal-00182924/fr/
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Abstract
In this paper, the identification of a class of nonlinear systems which admits inputoutput maps described by a finite degree Volterra series is considered. In actual fact, it appears that this class can model many important nonlinear multivariable processes not only in engineering, but also in biology, socio-economics, and ecology. To solve this identification problem, we propose a method based on local gradient search in a local parameterization of the state-space realization of finite degree Volterra series with infinite horizon. Using the local parameterization not only reduces the amount of the gradient calculations to the minimal value, but also overcomes the nonuniqueness problem of the optimal solution. Moreover, we propose a sequential projection method to provide an initial estimation of the parameters of finite degree Volterra series realization. This initial estimation is used to initialize the gradient search method.
Mots-Clés / Keywords
Identification; Non linear systems; Volterra series; Optimization; Subspace methods;
On Humanoid Motion Optimization
W.SULEIMAN, E.YOSHIDA, J.P.LAUMOND, A.MONIN
MRS, GEPETTO, AIST
Manifestation avec acte : IEEE-RAS International Conference on Humanoid Robots (Humanoids 07), Pittsburgh (USA), 29 Novembre - 1er décembre 2007, 8p. , N° 07395
Lien : http://hal.archives-ouvertes.fr/hal-00164004/fr/
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Abstract
In this paper, we present a recursive optimization method of humanoid motions. The method is based on an efficient dynamics algorithm, which allows the calculation of the gradient function with respect to the control parameters analytically. The algorithm makes use of the theory of Lie groups and Lie algebra. The main objective of this method is to smooth the pre-calculated humanoid motions by minimizing the efforts, and at the same time improving the stability of the humanoid robot during the execution of the planned tasks. Experimental results using HRP-2 platform are provided to validate the proposed method.
Mots-Clés / Keywords
Humanoid; Motion planning; Recursive dynamics; Optimization;
Identification of quadratic in-the-state system using nonlinear programming
W.SULEIMAN, A.MONIN
MRS
Manifestation avec acte : 15th Mediteterranean Conference on Control and Automation, Athène (France), 27-29 Juin 2007, 6p. , N° 07290
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110641Linear multivariable system identification: multi-experiments case
W.SULEIMAN, A.MONIN
MRS
Manifestation avec acte : Conference on Systems and Control (CSC 2007), Marrakech (Maroc), 16-18 Mai 2007, 6p. , N° 07087
Lien : http://hal.archives-ouvertes.fr/hal-00155852
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Abstract
In this paper, we propose a method for identifying the linear model of a system in the case of multiexperiments. The method is based on the minimization of output error cost function of all the input/output data sets simultaneously. The implementation of the proposed method is based on a local parameterization of the linear state space model in order to minimize the number of gradient search iterations. The optimization process is initialized by an extension of a classical subspace method. We show that, the estimated linear models provided by the proposed method are more accurate than that obtained by the actual methods of linear systems identification. Moreover, we figure out that, the method can handle the case of short multi-experiments by increasing the models vector of parameters to also include the initial conditions of the internal states
BiCamSLAM: two times mono is more than stereo
J.SOLA, A.MONIN, M.DEVY
MRS, RAP
Manifestation avec acte : 2007 IEEE International Conference on Robotics and Automation (ICRA'07), Rome (Italie), 10-14 Avril 2007, pp.4795-4800 , N° 06599
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110262Analyse de données GPS en vue de la modélisation des multitrajets
A.KIBANGOU, A.MONIN
MRS
Rapport de Contrat : Contrat EGNOS-BUS, Décembre 2006, 25p. , N° 06880
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108954Synthesizing and modeling human locomotion using system identification
W.SULEIMAN, A.MONIN, J.P.LAUMOND
MRS, RIA
Manifestation avec acte : 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'2006), Beijing (Chine), 9-12 Octobre 2006, pp.1972-1977 , N° 06103
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107968Identification of quadratic system by local gradient search
W.SULEIMAN, A.MONIN
MRS
Manifestation avec acte : 2006 IEEE International Conference on Control Applications, Munich (Allemagne), 4-6 Octobre 2006, pp.2565-2570 , N° 06104
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