HapticV1, PascalFrancis, Corpus, bibRecord, 000B09

MIMO output estimation with reduced multirate sampling for real-time haptic rendering

Identifieur interne : 000B09 ( PascalFrancis/Corpus ); précédent : 000B08; suivant : 000B10

MIMO output estimation with reduced multirate sampling for real-time haptic rendering

Auteurs : Kyungno Lee ; DOO YONG LEE

Source :

IEEE transactions on robotics [ 1552-3098 ] ; 2007.

RBID : Pascal:07-0451859

Descripteurs français

Pascal (Inist)
- Système MIMO, Identification système, Système multicadence, Echantillonnage, Temps réel, Sensibilité tactile, Grande déformation, Temps retard, Stabilité fréquence, Représentation graphique, Erreur sortie, Signal sortie, Modélisation, Méthode élément fini, Système masse ressort, Approche déterministe, Modèle entrée sortie, Méthode moindre carré, Estimation erreur, Erreur estimation, Méthode graphique, Convergence numérique.

English descriptors

KwdEn :
- Delay time, Deterministic approach, Error estimation, Estimation error, Finite element method, Frequency stability, Graphic method, Graphics, High strain, Input output model, Least squares method, MIMO system, Modeling, Multirate system, Numerical convergence, Output error, Output signal, Real time, Sampling, Spring mass system, System identification, Tactile sensitivity.

Abstract

This paper presents an output-estimation method with reduced multirate sampling for real-time multi-input-multi-output (MIMO) haptic rendering. Haptic systems employ physics-based deformation models such as finite-element models and mass-spring models. These physics-based deformation models for high fidelity have to deal with complex geometries, material properties, and realistic behavior of virtual objects. This incurs heavy computational burden and time delays so that the reflective force often cannot be computed at 1 kHz which is a safe frequency for stability of the haptic systems. Lower update rates of the haptic loop and the computational time delay also deteriorate the realism of the haptic system. This problem is resolved by the proposed MIMO output-estimation method. The haptic system is designed to have two sampling times, T and JT, for the haptic loop and the graphic loop, respectively. Dynamics of the physics-based deformation is captured in a discrete and deterministic input-output model. The MIMO output estimation method is developed drawing on a least-squares algorithm and an output-error estimation model. The P-matrix resetting algorithm is also designed to deal with the changing input-output relationship of the deformation model. The parameters of the discrete input-output model are adjusted online. Intersample outputs are computed from the estimated input-output model at a high rate, and traces the correct output computed from the deformation model. This method enables graphics rendering at a lower update rate, and haptic rendering at a higher update rate. Convergence of the proposed method is proved, and performance is demonstrated through simulation with both a linear tensor-mass and a linear mass-spring models.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

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C01	`01`		`ENG`	@0 This paper presents an output-estimation method with reduced multirate sampling for real-time multi-input-multi-output (MIMO) haptic rendering. Haptic systems employ physics-based deformation models such as finite-element models and mass-spring models. These physics-based deformation models for high fidelity have to deal with complex geometries, material properties, and realistic behavior of virtual objects. This incurs heavy computational burden and time delays so that the reflective force often cannot be computed at 1 kHz which is a safe frequency for stability of the haptic systems. Lower update rates of the haptic loop and the computational time delay also deteriorate the realism of the haptic system. This problem is resolved by the proposed MIMO output-estimation method. The haptic system is designed to have two sampling times, T and JT, for the haptic loop and the graphic loop, respectively. Dynamics of the physics-based deformation is captured in a discrete and deterministic input-output model. The MIMO output estimation method is developed drawing on a least-squares algorithm and an output-error estimation model. The P-matrix resetting algorithm is also designed to deal with the changing input-output relationship of the deformation model. The parameters of the discrete input-output model are adjusted online. Intersample outputs are computed from the estimated input-output model at a high rate, and traces the correct output computed from the deformation model. This method enables graphics rendering at a lower update rate, and haptic rendering at a higher update rate. Convergence of the proposed method is proved, and performance is demonstrated through simulation with both a linear tensor-mass and a linear mass-spring models.
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Format Inist (serveur)

NO :	PASCAL 07-0451859 INIST
ET :	MIMO output estimation with reduced multirate sampling for real-time haptic rendering
AU :	LEE (Kyungno); DOO YONG LEE
AF :	Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology/Daejeon 305-701/Corée, République de (1 aut., 2 aut.)
DT :	Publication en série; Niveau analytique
SO :	IEEE transactions on robotics ; ISSN 1552-3098; Etats-Unis; Da. 2007; Vol. 23; No. 3; Pp. 481-493; Bibl. 46 ref.
LA :	Anglais
EA :	This paper presents an output-estimation method with reduced multirate sampling for real-time multi-input-multi-output (MIMO) haptic rendering. Haptic systems employ physics-based deformation models such as finite-element models and mass-spring models. These physics-based deformation models for high fidelity have to deal with complex geometries, material properties, and realistic behavior of virtual objects. This incurs heavy computational burden and time delays so that the reflective force often cannot be computed at 1 kHz which is a safe frequency for stability of the haptic systems. Lower update rates of the haptic loop and the computational time delay also deteriorate the realism of the haptic system. This problem is resolved by the proposed MIMO output-estimation method. The haptic system is designed to have two sampling times, T and JT, for the haptic loop and the graphic loop, respectively. Dynamics of the physics-based deformation is captured in a discrete and deterministic input-output model. The MIMO output estimation method is developed drawing on a least-squares algorithm and an output-error estimation model. The P-matrix resetting algorithm is also designed to deal with the changing input-output relationship of the deformation model. The parameters of the discrete input-output model are adjusted online. Intersample outputs are computed from the estimated input-output model at a high rate, and traces the correct output computed from the deformation model. This method enables graphics rendering at a lower update rate, and haptic rendering at a higher update rate. Convergence of the proposed method is proved, and performance is demonstrated through simulation with both a linear tensor-mass and a linear mass-spring models.
CC :	001D02D05; 001D02D11
FD :	Système MIMO; Identification système; Système multicadence; Echantillonnage; Temps réel; Sensibilité tactile; Grande déformation; Temps retard; Stabilité fréquence; Représentation graphique; Erreur sortie; Signal sortie; Modélisation; Méthode élément fini; Système masse ressort; Approche déterministe; Modèle entrée sortie; Méthode moindre carré; Estimation erreur; Erreur estimation; Méthode graphique; Convergence numérique
ED :	MIMO system; System identification; Multirate system; Sampling; Real time; Tactile sensitivity; High strain; Delay time; Frequency stability; Graphics; Output error; Output signal; Modeling; Finite element method; Spring mass system; Deterministic approach; Input output model; Least squares method; Error estimation; Estimation error; Graphic method; Numerical convergence
SD :	Sistema MIMO; Identificación sistema; Sistema cadencia múltiple; Muestreo; Tiempo real; Sensibilidad tactil; Gran deformación; Tiempo retardo; Estabilidad frecuencia; Grafo (curva); Error salida; Señal salida; Modelización; Método elemento finito; Sistema masa muelle; Enfoque determinista; Modelo input-output; Método cuadrado menor; Estimación error; Error estimación; Método gráfico; Convergencia numérica
LO :	INIST-21023A.354000162960560080
ID :	07-0451859

Links to Exploration step

Pascal:07-0451859

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<front><div type="abstract" xml:lang="en">This paper presents an output-estimation method with reduced multirate sampling for real-time multi-input-multi-output (MIMO) haptic rendering. Haptic systems employ physics-based deformation models such as finite-element models and mass-spring models. These physics-based deformation models for high fidelity have to deal with complex geometries, material properties, and realistic behavior of virtual objects. This incurs heavy computational burden and time delays so that the reflective force often cannot be computed at 1 kHz which is a safe frequency for stability of the haptic systems. Lower update rates of the haptic loop and the computational time delay also deteriorate the realism of the haptic system. This problem is resolved by the proposed MIMO output-estimation method. The haptic system is designed to have two sampling times, T and JT, for the haptic loop and the graphic loop, respectively. Dynamics of the physics-based deformation is captured in a discrete and deterministic input-output model. The MIMO output estimation method is developed drawing on a least-squares algorithm and an output-error estimation model. The P-matrix resetting algorithm is also designed to deal with the changing input-output relationship of the deformation model. The parameters of the discrete input-output model are adjusted online. Intersample outputs are computed from the estimated input-output model at a high rate, and traces the correct output computed from the deformation model. This method enables graphics rendering at a lower update rate, and haptic rendering at a higher update rate. Convergence of the proposed method is proved, and performance is demonstrated through simulation with both a linear tensor-mass and a linear mass-spring models.</div>
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<fC01 i1="01" l="ENG"><s0>This paper presents an output-estimation method with reduced multirate sampling for real-time multi-input-multi-output (MIMO) haptic rendering. Haptic systems employ physics-based deformation models such as finite-element models and mass-spring models. These physics-based deformation models for high fidelity have to deal with complex geometries, material properties, and realistic behavior of virtual objects. This incurs heavy computational burden and time delays so that the reflective force often cannot be computed at 1 kHz which is a safe frequency for stability of the haptic systems. Lower update rates of the haptic loop and the computational time delay also deteriorate the realism of the haptic system. This problem is resolved by the proposed MIMO output-estimation method. The haptic system is designed to have two sampling times, T and JT, for the haptic loop and the graphic loop, respectively. Dynamics of the physics-based deformation is captured in a discrete and deterministic input-output model. The MIMO output estimation method is developed drawing on a least-squares algorithm and an output-error estimation model. The P-matrix resetting algorithm is also designed to deal with the changing input-output relationship of the deformation model. The parameters of the discrete input-output model are adjusted online. Intersample outputs are computed from the estimated input-output model at a high rate, and traces the correct output computed from the deformation model. This method enables graphics rendering at a lower update rate, and haptic rendering at a higher update rate. Convergence of the proposed method is proved, and performance is demonstrated through simulation with both a linear tensor-mass and a linear mass-spring models.</s0>
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<s5>09</s5>
</fC03>
<fC03 i1="05" i2="X" l="FRE"><s0>Temps réel</s0>
<s5>10</s5>
</fC03>
<fC03 i1="05" i2="X" l="ENG"><s0>Real time</s0>
<s5>10</s5>
</fC03>
<fC03 i1="05" i2="X" l="SPA"><s0>Tiempo real</s0>
<s5>10</s5>
</fC03>
<fC03 i1="06" i2="X" l="FRE"><s0>Sensibilité tactile</s0>
<s5>18</s5>
</fC03>
<fC03 i1="06" i2="X" l="ENG"><s0>Tactile sensitivity</s0>
<s5>18</s5>
</fC03>
<fC03 i1="06" i2="X" l="SPA"><s0>Sensibilidad tactil</s0>
<s5>18</s5>
</fC03>
<fC03 i1="07" i2="X" l="FRE"><s0>Grande déformation</s0>
<s5>19</s5>
</fC03>
<fC03 i1="07" i2="X" l="ENG"><s0>High strain</s0>
<s5>19</s5>
</fC03>
<fC03 i1="07" i2="X" l="SPA"><s0>Gran deformación</s0>
<s5>19</s5>
</fC03>
<fC03 i1="08" i2="X" l="FRE"><s0>Temps retard</s0>
<s5>20</s5>
</fC03>
<fC03 i1="08" i2="X" l="ENG"><s0>Delay time</s0>
<s5>20</s5>
</fC03>
<fC03 i1="08" i2="X" l="SPA"><s0>Tiempo retardo</s0>
<s5>20</s5>
</fC03>
<fC03 i1="09" i2="X" l="FRE"><s0>Stabilité fréquence</s0>
<s5>21</s5>
</fC03>
<fC03 i1="09" i2="X" l="ENG"><s0>Frequency stability</s0>
<s5>21</s5>
</fC03>
<fC03 i1="09" i2="X" l="SPA"><s0>Estabilidad frecuencia</s0>
<s5>21</s5>
</fC03>
<fC03 i1="10" i2="X" l="FRE"><s0>Représentation graphique</s0>
<s5>22</s5>
</fC03>
<fC03 i1="10" i2="X" l="ENG"><s0>Graphics</s0>
<s5>22</s5>
</fC03>
<fC03 i1="10" i2="X" l="SPA"><s0>Grafo (curva)</s0>
<s5>22</s5>
</fC03>
<fC03 i1="11" i2="X" l="FRE"><s0>Erreur sortie</s0>
<s5>23</s5>
</fC03>
<fC03 i1="11" i2="X" l="ENG"><s0>Output error</s0>
<s5>23</s5>
</fC03>
<fC03 i1="11" i2="X" l="SPA"><s0>Error salida</s0>
<s5>23</s5>
</fC03>
<fC03 i1="12" i2="X" l="FRE"><s0>Signal sortie</s0>
<s5>28</s5>
</fC03>
<fC03 i1="12" i2="X" l="ENG"><s0>Output signal</s0>
<s5>28</s5>
</fC03>
<fC03 i1="12" i2="X" l="SPA"><s0>Señal salida</s0>
<s5>28</s5>
</fC03>
<fC03 i1="13" i2="X" l="FRE"><s0>Modélisation</s0>
<s5>29</s5>
</fC03>
<fC03 i1="13" i2="X" l="ENG"><s0>Modeling</s0>
<s5>29</s5>
</fC03>
<fC03 i1="13" i2="X" l="SPA"><s0>Modelización</s0>
<s5>29</s5>
</fC03>
<fC03 i1="14" i2="X" l="FRE"><s0>Méthode élément fini</s0>
<s5>30</s5>
</fC03>
<fC03 i1="14" i2="X" l="ENG"><s0>Finite element method</s0>
<s5>30</s5>
</fC03>
<fC03 i1="14" i2="X" l="SPA"><s0>Método elemento finito</s0>
<s5>30</s5>
</fC03>
<fC03 i1="15" i2="X" l="FRE"><s0>Système masse ressort</s0>
<s5>31</s5>
</fC03>
<fC03 i1="15" i2="X" l="ENG"><s0>Spring mass system</s0>
<s5>31</s5>
</fC03>
<fC03 i1="15" i2="X" l="SPA"><s0>Sistema masa muelle</s0>
<s5>31</s5>
</fC03>
<fC03 i1="16" i2="X" l="FRE"><s0>Approche déterministe</s0>
<s5>32</s5>
</fC03>
<fC03 i1="16" i2="X" l="ENG"><s0>Deterministic approach</s0>
<s5>32</s5>
</fC03>
<fC03 i1="16" i2="X" l="SPA"><s0>Enfoque determinista</s0>
<s5>32</s5>
</fC03>
<fC03 i1="17" i2="X" l="FRE"><s0>Modèle entrée sortie</s0>
<s5>33</s5>
</fC03>
<fC03 i1="17" i2="X" l="ENG"><s0>Input output model</s0>
<s5>33</s5>
</fC03>
<fC03 i1="17" i2="X" l="SPA"><s0>Modelo input-output</s0>
<s5>33</s5>
</fC03>
<fC03 i1="18" i2="X" l="FRE"><s0>Méthode moindre carré</s0>
<s5>34</s5>
</fC03>
<fC03 i1="18" i2="X" l="ENG"><s0>Least squares method</s0>
<s5>34</s5>
</fC03>
<fC03 i1="18" i2="X" l="SPA"><s0>Método cuadrado menor</s0>
<s5>34</s5>
</fC03>
<fC03 i1="19" i2="X" l="FRE"><s0>Estimation erreur</s0>
<s5>35</s5>
</fC03>
<fC03 i1="19" i2="X" l="ENG"><s0>Error estimation</s0>
<s5>35</s5>
</fC03>
<fC03 i1="19" i2="X" l="SPA"><s0>Estimación error</s0>
<s5>35</s5>
</fC03>
<fC03 i1="20" i2="X" l="FRE"><s0>Erreur estimation</s0>
<s5>36</s5>
</fC03>
<fC03 i1="20" i2="X" l="ENG"><s0>Estimation error</s0>
<s5>36</s5>
</fC03>
<fC03 i1="20" i2="X" l="SPA"><s0>Error estimación</s0>
<s5>36</s5>
</fC03>
<fC03 i1="21" i2="X" l="FRE"><s0>Méthode graphique</s0>
<s5>37</s5>
</fC03>
<fC03 i1="21" i2="X" l="ENG"><s0>Graphic method</s0>
<s5>37</s5>
</fC03>
<fC03 i1="21" i2="X" l="SPA"><s0>Método gráfico</s0>
<s5>37</s5>
</fC03>
<fC03 i1="22" i2="X" l="FRE"><s0>Convergence numérique</s0>
<s5>38</s5>
</fC03>
<fC03 i1="22" i2="X" l="ENG"><s0>Numerical convergence</s0>
<s5>38</s5>
</fC03>
<fC03 i1="22" i2="X" l="SPA"><s0>Convergencia numérica</s0>
<s5>38</s5>
</fC03>
<fN21><s1>295</s1>
</fN21>
<fN44 i1="01"><s1>OTO</s1>
</fN44>
<fN82><s1>OTO</s1>
</fN82>
</pA>
</standard>
<server><NO>PASCAL 07-0451859 INIST</NO>
<ET>MIMO output estimation with reduced multirate sampling for real-time haptic rendering</ET>
<AU>LEE (Kyungno); DOO YONG LEE</AU>
<AF>Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology/Daejeon 305-701/Corée, République de (1 aut., 2 aut.)</AF>
<DT>Publication en série; Niveau analytique</DT>
<SO>IEEE transactions on robotics ; ISSN 1552-3098; Etats-Unis; Da. 2007; Vol. 23; No. 3; Pp. 481-493; Bibl. 46 ref.</SO>
<LA>Anglais</LA>
<EA>This paper presents an output-estimation method with reduced multirate sampling for real-time multi-input-multi-output (MIMO) haptic rendering. Haptic systems employ physics-based deformation models such as finite-element models and mass-spring models. These physics-based deformation models for high fidelity have to deal with complex geometries, material properties, and realistic behavior of virtual objects. This incurs heavy computational burden and time delays so that the reflective force often cannot be computed at 1 kHz which is a safe frequency for stability of the haptic systems. Lower update rates of the haptic loop and the computational time delay also deteriorate the realism of the haptic system. This problem is resolved by the proposed MIMO output-estimation method. The haptic system is designed to have two sampling times, T and JT, for the haptic loop and the graphic loop, respectively. Dynamics of the physics-based deformation is captured in a discrete and deterministic input-output model. The MIMO output estimation method is developed drawing on a least-squares algorithm and an output-error estimation model. The P-matrix resetting algorithm is also designed to deal with the changing input-output relationship of the deformation model. The parameters of the discrete input-output model are adjusted online. Intersample outputs are computed from the estimated input-output model at a high rate, and traces the correct output computed from the deformation model. This method enables graphics rendering at a lower update rate, and haptic rendering at a higher update rate. Convergence of the proposed method is proved, and performance is demonstrated through simulation with both a linear tensor-mass and a linear mass-spring models.</EA>
<CC>001D02D05; 001D02D11</CC>
<FD>Système MIMO; Identification système; Système multicadence; Echantillonnage; Temps réel; Sensibilité tactile; Grande déformation; Temps retard; Stabilité fréquence; Représentation graphique; Erreur sortie; Signal sortie; Modélisation; Méthode élément fini; Système masse ressort; Approche déterministe; Modèle entrée sortie; Méthode moindre carré; Estimation erreur; Erreur estimation; Méthode graphique; Convergence numérique</FD>
<ED>MIMO system; System identification; Multirate system; Sampling; Real time; Tactile sensitivity; High strain; Delay time; Frequency stability; Graphics; Output error; Output signal; Modeling; Finite element method; Spring mass system; Deterministic approach; Input output model; Least squares method; Error estimation; Estimation error; Graphic method; Numerical convergence</ED>
<SD>Sistema MIMO; Identificación sistema; Sistema cadencia múltiple; Muestreo; Tiempo real; Sensibilidad tactil; Gran deformación; Tiempo retardo; Estabilidad frecuencia; Grafo (curva); Error salida; Señal salida; Modelización; Método elemento finito; Sistema masa muelle; Enfoque determinista; Modelo input-output; Método cuadrado menor; Estimación error; Error estimación; Método gráfico; Convergencia numérica</SD>
<LO>INIST-21023A.354000162960560080</LO>
<ID>07-0451859</ID>
</server>
</inist>
</record>

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MIMO output estimation with reduced multirate sampling for real-time haptic rendering

MIMO output estimation with reduced multirate sampling for real-time haptic rendering

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