Kinetostatic Modeling of Tendon-Driven Parallel Continuum Robots
Bibliographic record
Abstract
Tendon-driven parallel continuum robots (PCR) consist of multiple individual continuous kinematic chains, that are actuated in bending utilizing tendons routed along their backbones. This work derives and proposes a Cosserat rod based kinetostatic modeling framework for such parallel structures that allows for efficiently solving the forward, inverse and velocity kinetostatic problems. Using this model, the kinematic properties such as reachable workspace, singularities, manipulability, and compliance of tendon-driven PCR are studied in detail. Experiments are conducted using a real robotic prototype to validate the derived modeling approach. Overall, a median pose accuracy of 4.9 mm, corresponding to 3.4% of the continuum robots' lengths, and 6.2$^\circ$is achieved. The median of the model's computation time results in 0.51 s on standard computing hardware. Fast computations of below 100 ms can be achieved, if an appropriate initial guess for solving the kinetostatic model is available, making the model suitable for a range of different applications including optimization or control.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".