Bibliographic record
Abstract
An essential requirement in haptics is accuracy and transparency of the haptic interface. Haptic devices are usually lightweight robotic systems with which a human operator interacts. In the current literature, dynamic analyses of haptic devices are limited to single degree-of-freedom (DoF) point mass models. In this paper, experimental and simulation studies are conducted to investigate the effects of mechanical design parameters on the performance of such devices. For this purpose two commonly used haptic devices were considered: a two-DoF PANTOGRAPH and a three-DoF PHANToM. The results show that dynamic coupling between the rendered (controlled) and free directions of motion can influence the desired performance. An alternative formulation is outlined in which dynamic behavior of a haptic interface is modeled as a multibody system. The dynamic equations are separated to two sets of equations associated with the rendered and admissible motions. Effects of time delay and discretization stemming from digital realization of the virtual environment can be analyzed using the rendered dynamic equations, while the equations associated with the admissible motions can serve as a basis for performance measure. This formulation can be efficiently used for the complex nonlinear dynamics and stability analyses of haptic interfaces and can provide essential details on the performance of these devices. Stability analysis of a two-DoF five-bar linkage is presented as an example using the proposed formulation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".