Network traffic reduction in six degree-of-freedom haptic, telementoring systems
Bibliographic record
Abstract
This paper introduces a haptic data reduction and transmission technique to reduce the packet rate in six degree-of-freedom (6-DoF) haptic-enabled telementoring systems. The presented method relies on the limitations of human haptic perception (i.e. the Just Noticeable Differences) with respect to a user's hand position and orientation in order to reduce the number of packets transmitted without compromising transparency. A haptic prediction model is exploited to further reduce the amount of haptic packets transmitted, and to improve the reconstruction of data samples on the receiver side. Several distance metrics are also discussed to evaluate the acuity of human haptic perception when data reduction is performed in 6-DoF settings. Psychophysical experiments validate the effectiveness of the suggested algorithm as great haptic data reduction is achieved (up to 96%), while preserving the overall quality of the telementoring environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".