A Framework of Real2Sim Teleoperation System for Evaluating Surgical Robotic Tool Design
Bibliographic record
Abstract
During the process of designing a surgical robotic tool, a teleoperation system is necessary to evaluate the tool design in a simulated environment via virtual surgical tasks. It is possible to build such a system by involving a physical da Vinci Surgical System (dVSS) and using its master tool manipulator (MTM) to teleoperate the virtual robotic tool for evaluation. However, extensive testing and debugging require a more general and portable teleoperation system. In this work, we propose a general framework for establishing a real-to-sim teleoperation system. In the system, the real robot's Cartesian pose is first transformed, scaled, and mapped into the sim robot's coordinate system. Then, the resulting pose, as the desired pose of the sim robot, will proceed through a numerical inverse kinematics (IK) solver. The numerical IK solution is used to update the current joint configuration of the sim robot, which enables an independent and compact teleoperation system. Additionally, the numerical IK solution can be channeled to other simulation platforms for visualizing the sim robot with joint command control, where various virtual surgical tasks can be designed and conducted for further tool evaluation. Preliminary experiments were conducted to evaluate an established Omni-to-Unity teleoperation system, and the system's stability, accuracy, and usability were assessed and verified by the experimental results. The established teleoperation system can be used to streamline and facilitate robotic tool design and evaluation. Furthermore, the proposed real 2 sim framework can be easily adapted to a variety of application scenarios where both the real and sim robots can be specified by the user for different purposes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".