Passive Multirate Wave Communications for Haptic Interaction in Slow Virtual Environments
Bibliographic record
Abstract
Haptic interaction in slow virtual environments (VEs) can become unstable due to the phase lag introduced in the control loop by the slow update rate of the VE. Increasing the physical damping and/or limiting the contact stiffness rendered to users can mitigate the destabilizing effect of the low VE update rate. However, large physical damping and compliant virtual contacts decrease the sense of presence in VEs, especially during interaction with rigid virtual objects. To increase the maximum virtual contact stiffness that can be rendered to users without increasing the interface damping, this paper proposes a control strategy based on multirate wave communications between a haptic interface and a VE updated at a slow and fixed rate. The multirate wave communications are shown to be guaranteed passive only if the decrease of the wave sampling rate at the connection between the haptic interface and the VE does not cause aliasing. Therefore, an antialiasing low-pass filter is placed before the wave rate drop in the communications. The passivity condition is verified analytically and numerically for multirate haptic interaction in VEs with various contact stiffnesses and update rates. The transparency of haptic interaction in slow VEs to which users connect via passive multirate wave communications is investigated analytically in the frequency domain. Experiments validate that passive multirate wave communications can render stiffer contact in slow VEs than conventional direct coupling, and illustrate the destabilizing effect of the aliasing caused by the sampling rate drop in the communications.
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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".