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Record W1972332889 · doi:10.1177/0278364905057856

Local Model of Interaction for Haptic Manipulation of Rigid Virtual Worlds

2005· article· en· W1972332889 on OpenAlexaff
Daniela Constantinescu, Septimiu E. Salcudean, Elizabeth A. Croft

Bibliographic record

VenueThe International Journal of Robotics Research · 2005
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsUniversity of British ColumbiaUniversity of Victoria
Fundersnot available
KeywordsHaptic technologyComputer scienceVirtual machineContact forceKinesthetic learningHuman–computer interactionRigid bodySimulationPhysics

Abstract

fetched live from OpenAlex

In this paper we propose a local model of rigid body interaction that provides users with convincing kinesthetic feedback while they manipulate a virtual tool within a rigid multibody virtual world. The virtual tool can be a rigid object or a linkage. The local model can interface a haptic device to any virtual environment simulation that provides the contact position, the contact normal direction, and the penetration depth of the virtual tool into the virtual world at the virtual tool contacts. The local model includes a proxy of the virtual tool that embeds an approximation of its geometry and of its dynamics, and that eliminates force discontinuities at model updates via proxy deformation. In addition, the model includes active and predicted virtual tool contacts. Predicted contacts are used to maintain force continuity and to better constrain users to tight virtual spaces. Experiments performed within a planar virtual world demonstrate that, compared to prior local models of rigid body interaction, the proposed model enables users to feel stiffer contacts and improves users' perception of free space in locally cluttered virtual environments.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.882
Threshold uncertainty score0.181

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.122
GPT teacher head0.379
Teacher spread0.257 · 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

Citations17
Published2005
Admission routes1
Has abstractyes

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