Depth-based Visual Predictive Control of Tendon-Driven Continuum Robots
Why this work is in the frame
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Bibliographic record
Abstract
Image-based visual servoing (IBVS) scheme has become popular due to its advantages such as robustness to camera calibration errors and enabling direct control over the image features. However, in IBVS approaches several issues such as image singularities, and camera retreat problems must be addressed. Also, they lack a mechanism for enforcing constraints into control formulation. This paper presents a novel depth-based visual predictive control (DVPC) method to overcome several shortcomings of the previous IBVS methods. In particular, the proposed approach enables constraints enforcement and addresses one of the critical issues of the IBVS method, namely camera retreat problem. Furthermore, the proposed approach is applied for the control of continuum robots (CR). Simulation results are presented to verify the efficiency and functionality of the proposed approach.
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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