A passivity criterion for N-port multilateral haptic systems
Bibliographic record
Abstract
This paper presents a criterion for passivity of n-port networks, which can be used to model multilateral systems involving haptic information sharing between a number of users. Such systems have recently found interesting applications in both cooperative haptic teleoperation and haptics-assisted training. The criterion presented in Theorem 1, which is necessary and sufficient for passivity of the n-port network, imposes 2n conditions on the immitance parameters of the network and on the residues of the immitance parameters at their imaginary-axis poles. It is shown that when n = 2, the proposed conditions reduce to the well-known Raisbeck's passivity criterion for two-port networks. Another special case for which the proposed criterion has been simplified corresponds to three-port networks. Finally, the passivity of a dual-user haptic system for control of a single teleoperated robot is investigated.
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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".