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Record W1965260191 · doi:10.1109/tim.2010.2047589

Uniform Hardness Perception in 6-DOF Haptic Rendering

2010· article· en· W1965260191 on OpenAlexaff
Jilin Zhou, François Malric, Emil M. Petriu, Nicolas D. Georganas

Bibliographic record

VenueIEEE Transactions on Instrumentation and Measurement · 2010
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHaptic technologyRendering (computer graphics)PerceptionStiffnessCompensation (psychology)Computer scienceHaptic perceptionSimulationBall (mathematics)Tactile perceptionVirtual realityComputer visionArtificial intelligenceEngineeringMathematicsStructural engineeringPsychologyGeometry

Abstract

fetched live from OpenAlex

In this paper, we study the influence of a haptic interface's effective mass and viscous damping on the hardness perception of simulated virtual objects in six-degree-of-freedom (6-DOF) haptic rendering. It is found that induced forces from these physical parameters affect the perceived hardness nonuniformly as users tap virtual objects with different parts of the tool. Fundamentally, the distinct hardness perception is caused by the discrepancy between the user's holding point and the active end of the device. A stick-on-ball application was used for comparisons of three proposed compensation methods. A total of six stiffness intensities in the range of 0.1-0.6 N/m at a step of 0.1 were randomly presented to a total of ten test subjects. Experimental results show both the need for compensation and the effectiveness of the proposed methods.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.547
Threshold uncertainty score0.506

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 head0.027
GPT teacher head0.227
Teacher spread0.200 · 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 designBench or experimental
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

Citations8
Published2010
Admission routes1
Has abstractyes

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