An Efficient Static Analysis of Continuum Robots
Bibliographic record
Abstract
An efficient yet accurate model of the continuum robot is the main component for its real-time control, simulation as well as localization. Previous models of the continuum robot, based on rod theory, suffer from high computational burden. The models also require a priori knowledge of the robot environment. This paper presents an efficient static model for the planar continuum robot that experiences external forces at the tip as a result of contact with its surroundings (measured by the built-in force sensors), thus no a priori information about the environment is required. The typical example of such robots is steerable catheters used in medical operations. The proposed approach involves discretizing the robot backbone curve to elastic arc elements. After deriving the equilibrium equations for the infinitesimal elements, a recursive algorithm with the time complexity of O(n) is proposed for realizing the shape of the robot as a result of the external force. Accuracy of the proposed method is evaluated both theoretically and experimentally for a case study, i.e., an intracardiac ablation catheter. Results validate the accuracy and time-efficiency of the proposed approach for real-time applications.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".