Direct impulse-based rendering in force feedback haptics
Bibliographic record
Abstract
In certain haptic applications, producing a sharp feeling of impact is important for high-fidelity force feedback rendering of virtual objects. This paper studies the direct impulse-based rendering paradigm to achieve this goal. Three main challenges are identified and some solutions are proposed. The first one is the energy deviation due to the sampled-data settings. Since the deviation tends to have a dissipative nature, it is called unsolicited dissipation and is suggested to be countered by applying a larger adaptive coefficient of restitution based on energy monitoring. The second challenge is the actuation limits which can be met by distributing the impulse into a sequence of force commands over successive intervals. The third is rendering resting contacts which is proposed to be done using a hybrid penalty-impulse-based technique. This paper develops a systematic way for collecting all the required mathematical formulations, analysis of the aforementioned issues and implementation of the solutions within a unified control-oriented framework entitled the generalized contact controller (GCC). Our initial simulation and experimental results show the promising aspects of the direct impulse-based rendering and the GCC framework for generating a sharper unfiltered feeling of impact at relatively low sampling rates compared to virtual coupling-based indirect 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 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".