Optimal Remote Center-of-Motion Location for Robotics-Assisted Minimally-Invasive Surgery
Why this work is in the frame
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Bibliographic record
Abstract
A novel technique is described for isotropy-based kinematic optimization of specific robot characteristics. The new technique has advantages over existing techniques when designing robotic systems for specific, unconventional tasks, and for constrained motion. In this paper, the technique is used to assist in the selection of a remote center-of-motion (RCM) location for a research testbed that is being developed at CSTAR to study robotics-assisted minimally-invasive surgery. The optimization technique allows isotropy to be considered with respect to the surgical tool tip while operating under the RCM constraint. Global isotropy over a minimally-invasive surgical workspace is evaluated for a set of candidate RCM locations, and an optimal RCM location with respect to isotropy is selected. The isotropy results are compared with experimental data for a number of candidate RCM locations. The experimental results confirm the usefulness of the optimization technique.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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