Path Planning with Modified RRT* Algorithm for Lung Biopsy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Path planning plays a central role in robot-assisted percutaneous insertion. The main challenge of path planning exists in the motion constraints inherited from the geometry and mechanics of the needle, and the complex anatomic environment of human body. In nonholonomic planning, the classic Rapidly-Exploring Random Trees (RRT) algorithm may fail to provide a continuous and obstacleavoidable path. To find a feasible path and minimize the damage on soft tissues based on a newly-introduced curvature-controllable steerable needle, we propose a method that utilizes RRT* and quadratic Bezier curve smoothing technique. RRT* with Bezier Curve Smoothing can generate a path composed of smooth piecewise planar curves with continuous connections. Comparisons are employed to show that our method generates shorter and less torturous paths with a higher success rate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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