A Master‐Follower Teleoperation System for Robotic Catheterisation: Design, Characterisation and Tracking Control
Bibliographic record
Abstract
BACKGROUND: Over the past 2 decades, telerobotic systems with robot-mediated, minimally invasive techniques, have mitigated radiation exposure for medical staff and extended medical services to remote areas. To enhance these services, master-follower telerobotic systems should offer transparency, enabling surgeons and clinicians to feel force interactions similar to those the follower device experiences with patients' bodies. METHODS: We present a three-degree-of-freedom master-follower teleoperated system for robotic catheterisation. The follower device uses a grip-insert-release mechanism to prevent catheter buckling and torsion, mimicking real-world manual intervention. Performance is evaluated through open-loop path tracking on circular, infinity-like and spiral paths. RESULTS: Path tracking errors, mean Euclidean error (MEE) and mean absolute error (MAE), range from 0.64 to 1.53 cm (MEE) and 0.81-1.92 cm (MAE) for different paths. CONCLUSION: While the system meets precision and accuracy targets with an open-loop controller, closed-loop control is needed to address catheter hysteresis, dead zones and nonlinearities.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".