Robot-assisted lung motion compensation during needle insertion
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, a robotic solution is proposed to deal with the challenges caused by lung motion during needle insertion. To accomplish this goal, a macro-micro robotic tool is designed to compensate for tissue motion using the macro part, while performing the needle insertion independently with the micro part. The main application of this work is for robotics-assisted lung tumor biopsy, where the combined motions of respiration and heartbeat may compromise success. An impedance-based controller keeps the macro reference coordinate in contact with the moving soft tissue using measurements from small pressure sensors mounted at the tip of the macro shaft. The micro part, mounted at the end of the macro robot, manipulates the needle in the harmonized reference coordinate system. Preoperative identification of ex vivo soft tissue is performed to estimate the dynamic behavior of the tissue. The controller is then synthesized based on the identified model. The effects of identification error and high frequency uncertainty are addressed in the control design. A prototype was built to evaluate the proposed approach using: 1) two Mitsubishi PA-10 robots, one for manipulating the macro part and the other for mimicking tissue motion, 2) one motorized linear stage to handle the micro part, and 3) a Phantom Omni haptic device for remote manipulation. Experimental results demonstrate the performance of the motion compensation 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