Control design and experiments for enhanced detection of stiffness variation in soft-tissue telemanipulation
Bibliographic record
Abstract
The performance index in teleoperation, transparency, is often defined as linear scaling of force and position between the master/operator and slave/environment. Motivated by applications involving soft tissue manipulation such as robotic surgery, the transparency objective is generalized to include monotonic nonlinear mappings between the master/slave position and force signals. To demonstrate the utility of such performance index, an enhanced sensitivity non-linear force mapping design is proposed that can improve stiffness discrimination in telemanipulation tasks. The mapping design is validated using adaptive psychophysics perception experiments. Lyapunov-based adaptive motion/force controllers are presented that can guarantee the convergence of position and force tracking errors in the presence of dynamic uncertainty. Given a priori known bounds on the unknown operator/environment parameters, the robust stability of the proposed teleoperation system is analyzed using an off-axis circle criterion and the Nyquist envelope of interval plant systems. Experimental results with a two-axis teleoperation setup are provided.
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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".