Semi-Autonomous Surgical Robot Control for Beating-Heart Surgery
Bibliographic record
Abstract
In this paper, a semi-autonomous robot control system is developed for 3D robotic tracking of the complex physiological organ motion introduced by respiration and heartbeat in cardiac surgery. The same control system enables the surgeon's hand to perceive the non-oscillatory portion of the surgical robot-heart tissue interaction force. The semi-autonomous surgical system includes a slave surgical robot which can compensate for the physiological organ motion automatically and a master robot (user interface) which is manipulated by the surgeon to provide task commands to the surgical robot. The proposed impedance control method for the surgical robot only needs the frequency range of the physiological motion to synchronize the surgical instrument with the organ motion automatically. Another reference impedance model for the master robot is designed to provide non-oscillatory force feedback to the surgeon. A usability study emulating the motion requirements of tissue ablation is carried out. Experimental results are presented to show the effectiveness of the proposed method by comparing the results to the manual compensation method.
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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 | 0.000 |
| 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) | 0.001 | 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".