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Enregistrement W6995689697

Passive Multirate Wave Variables Control for Haptic Applications

2014· dissertation· en· W6995689697 sur OpenAlexfundno aff

Notice bibliographique

RevueUVic’s Research and Learning Repository (University of Victoria) · 2014
Typedissertation
Langueen
DomaineEngineering
ThématiqueTeleoperation and Haptic Systems
Établissements canadiensnon disponible
Organismes subventionnairesNatural Sciences and Engineering Research Council of Canada
Mots-clésTeleoperationFilter (signal processing)Object (grammar)Work (physics)Stability (learning theory)Transmission (telecommunications)
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

A haptic system is a robotic computer interface which aims to provide tactile feedback for human operators when they manipulate virtual environments (VEs) or remote environments (REs). The tactile feedback is emulated by applying forces, vibrations, or motions to the human users through a haptic device/interface, e.g. a robot arm.
\n Transparency and stability are two important criteria for designing a haptic system. Transparency is related to the realism of user's touch sensation and stability guarantees the safety of the user while interacting with VEs/REs. Because of the nature of the human tactile sensory system, a transparent haptic system demands an update rate greater than 500 Hz, i.e. most commercial haptic devices work at 1 KHz. On the other hand, many haptic applications are multirate systems. The multirate property of a haptic system is due to either the slow update rate of the VE or the impairments of computer networks such as limited transmission bandwidth or packet loss.
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\n Wave transformation is wildly used in teleoperation to cope with both constant and varying time delays. This work aims to use wave transformation to tackle the challenges imposed by multirate property of a haptic system. First, passive multirate wave variables control (PMWVC) is introduced. PMWVC guarantees the passivity of the communication channels through which the fast haptic device is connected to the slow VE/RE. It is shown that to maintain the passivity of the system, aliasing should be avoided in the communication channels, i.e. by using anti-aliasing filters.
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\nNext, PMWVC strategy is applied to two different applications: i) multiuser cooperative haptics and ii) haptic interaction with an unknown VE.
\nIn the first application, two users at two different locations manipulate a common virtual object simulated on a central server. The users are connected to the central server through a LAN network. The second application is a single user application in which PMWVC is used to connect the haptic device to an unknown slowly updated VE. Since in this application the VE is unknown, the computational delay of the VE significantly affects the stability of the overall system. To tackle this problem, a nonlinear algorithm based on passivity analysis is proposed. In both examples, numerical and experimental results validating the analytical results are provided. The results show that by using PMWVC, it is possible to significantly improve the performance of a multirate haptic system in terms of transparency and stability.
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\nThe second half of this work is devoted to improving the performance of PMWVC in all frequency ranges. In order to study the performance of PMWVC, lifting is used to convert the multirate haptic system to a unirate system. By using this technique, it is shown that velocity estimation plays a critical role in a haptic application with PMWVC, especially in high frequencies. Considering this fact, a method for designing a passive velocity filter in wave domain is proposed. 
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\nFinally, a filter bank structure is introduced which enables utilizing a local model in conjunction with PMWVC. In this structure, the outgoing signal sent to the VE is split into two frequency ranges. Low frequency content of the signal is fed to the original VE and high frequency content of the signal is sent to the local model. By using lifting the performance of the proposed structure is studied. The results show that the proposed method improves the transparency of the system in all frequency ranges and unlike utilizing a local model in power domain, it does not impose any restriction on the stability of the system.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,651
Score d'incertitude au seuil0,904

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,017
Tête enseignante GPT0,247
Écart entre enseignants0,229 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2014
Routes d'admission1
Résumé présentoui

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