Multilateral haptic system stability analysis: The effect of activity or passivity of terminations via a series-shunt approach
Bibliographic record
Abstract
Haptic teleoperation and haptic interaction systems can be modeled as multi-port networks. In this context, bilateral or trilateral haptic systems stability has been analyzed in the literature by using their two-port or three-port network models. Traditionally, such stability criteria assume that operators and environments (collectively, terminations) of the multilateral haptic systemare passive but otherwise arbitrary. However, recent research has shown that such an assumption can be inaccurate or too conservative as far as the human operator in a robotic system is concerned. In order not to jeopardize the haptic system stability when a termination is active or sacrifice system performance when a termination is strictly passive, we need a stability analysis approach that can take into account the degree of passivity (or lack thereof) of each termination. In response to this need, we have developed an approach based on series-shunt decomposition of the termination impedance model. Experimental validation of the theoretical stability criteria are performed involving active operators and environment for both bilateral and trilateral teleoperation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".