Compensating device inertia for 6-DOF haptic rendering
Bibliographic record
Abstract
In this paper, the importance of the user's primary holding pivot point on the end effector of a haptic interface is discussed. Both theoretical analysis and experimental results demonstrate that this holding pivot point is critical for the correct perception of the haptic properties assigned to the virtual objects. We also study the physical inertia effects of the end effector on the non-uniform stiffness perception of simulated virtual objects. To the best of our knowledge, no such combined consideration of holding pivot point and device structure related inertia has so far been made for works in 6-DOF haptic rendering. We have instrumented the end effector of a haptic interface with a membrane potentiometer to measure the user's primary holding pivot point in real-time. Accordingly, a preliminary adaptive feedback method is developed to render the appropriate forces/torques to compensate for the effects of the end effector's inertia on the haptic stiffness perception.
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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".