A dual-user teleoperated system with Virtual Fixtures for robotic surgical training
Why this work is in the frame
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Bibliographic record
Abstract
This paper proposes a teleoperated dual-user system incorporating Virtual Fixtures (VFs) that allows concurrent performance of a robotic surgical task by an expert and a trainee. In order to guide the trainee through the procedure, an adaptive VF is created in the trainee's workspace according to the motion generated by the expert who is performing the surgery at the same time. The VF gets adaptively adjusted based on the level of expertise the trainee shows during the surgery. In addition, the trainee's level of expertise is used to adaptively adjust the dual-user dominance factor in an online fashion, which gives the trainee some authority over the task based on his/her skill level. To quantify the trainee's expertise level, a performance measure is proposed, based on the force generated by the VF. Three performance measures from the literature are also used. To satisfy the desired objectives of the proposed system, an impedance-based control methodology is adopted. Stability of the closed-loop system is investigated using the small-gain theorem. A sufficient stability condition is derived that guarantees stability in the presence of time-varying communication delay. Experimental results are given to validate the performance of the system.
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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 it