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Record W2018754103 · doi:10.1115/detc2011-48551

Dynamics of Multibody Haptic Systems

2011· article· en· W2018754103 on OpenAlexaff
Sara Shayan Amin, Jo ́zsef Ko ̈vecses

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsMcGill University
Fundersnot available
KeywordsHaptic technologyComputer scienceDiscretizationInterface (matter)Stability (learning theory)WorkspaceSimulationNonlinear systemFour-bar linkagePantographControl theory (sociology)Control engineeringMotion (physics)EngineeringArtificial intelligenceRobotMechanical engineeringMathematics

Abstract

fetched live from OpenAlex

An essential requirement in haptics is accuracy and transparency of the haptic interface. Haptic devices are usually lightweight robotic systems with which a human operator interacts. In the current literature, dynamic analyses of haptic devices are limited to single degree-of-freedom (DoF) point mass models. In this paper, experimental and simulation studies are conducted to investigate the effects of mechanical design parameters on the performance of such devices. For this purpose two commonly used haptic devices were considered: a two-DoF PANTOGRAPH and a three-DoF PHANToM. The results show that dynamic coupling between the rendered (controlled) and free directions of motion can influence the desired performance. An alternative formulation is outlined in which dynamic behavior of a haptic interface is modeled as a multibody system. The dynamic equations are separated to two sets of equations associated with the rendered and admissible motions. Effects of time delay and discretization stemming from digital realization of the virtual environment can be analyzed using the rendered dynamic equations, while the equations associated with the admissible motions can serve as a basis for performance measure. This formulation can be efficiently used for the complex nonlinear dynamics and stability analyses of haptic interfaces and can provide essential details on the performance of these devices. Stability analysis of a two-DoF five-bar linkage is presented as an example using the proposed formulation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.200
Teacher spread0.180 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2011
Admission routes1
Has abstractyes

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