An Atlas-Based Approach to Planar Variable-Structure Cable-Driven Parallel Robot Configuration-Space Representation
Bibliographic record
Abstract
Variable-structure cable-driven parallel robots (VSCR) are a new class of cable robots that are able to cover nonconvex installation spaces by permitting collisions between cables and fixed objects in the environment. In this article, we show how the configuration space of a general planar VSCR can be represented as an organized set of partially overlapping regions of constant structure. The benefit of this representation, which we refer to as the “structure atlas,” is that it allows any techniques from the established cable-driven parallel robot literature to be applied locally, greatly simplifying the modeling complexity associated with VSCRs. A complete method for how such a representation can be constructed is provided, which includes identifying the set of reachable kinematic structures for a given VSCR and the area where each structure is active. We then give specific examples of how this new representation can be used for performing VSCR workspace analysis and directly solving the VSCR inverse kinematics problem. Our results are demonstrated with the aid of simulated and experimental results.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".