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Record W2049695895 · doi:10.1108/01439910210425487

Haptic interaction with virtual objects: the technology and some applications

2002· article· en· W2049695895 on OpenAlex
Lennart Thurfjell, John P. McLaughlin, Johan Mattsson, Piet Lammertse

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIndustrial Robot the international journal of robotics research and application · 2002
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsReach Technologies (Canada)
Fundersnot available
KeywordsHaptic technologyComputer scienceStereotaxyHuman–computer interactionRendering (computer graphics)Computer graphics (images)Computer graphicsVirtual realityArtificial intelligence

Abstract

fetched live from OpenAlex

Haptics is an emerging technology that allows touch‐enabled interaction with virtual objects. Analogous to the use of computer graphics for rendering of a three‐dimensional (3D) scene to give the user a visual description of the scene, it is possible to use computer haptics to let the user touch objects in the 3D scene. This is normally accomplished by having the haptics engine sending either force vectors or positional information to a haptics device, a robotic arm, that the user manipulates. The purpose of this paper is to give an overview of this technology, describe haptic devices and haptic application programming interfaces. We will also illustrate the use of haptics technology by describing a few industrial and medical applications.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.721
Threshold uncertainty score0.276

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 integrity0.0000.001
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 head0.069
GPT teacher head0.307
Teacher spread0.238 · 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