Tensionability Conditions of a Multi-Body System Driven by Cables
Bibliographic record
Abstract
Cable-driven mechanisms have been reported in the literature for the manipulation of a single rigid body. A cable-driven mechanism configured as a Completely Restrained Positioning Mechanism (CRPM) [6], requires a minimum of n+1 cables to maintain the tensionability of the manipulator (i.e. all cables can be made taut), where n is the dimension of the motion space (typically 3 in the planar and 6 in spatial manipulators). In this paper, the idea of cable-driven manipulators is extended to the manipulation of a multi-body system by cables. The first and most fundamental issue to be addressed is the required number of cables and the cable distribution over the links. This problem is thoroughly investigated in this paper. The major issue that differentiates between single rigid body and multi-body cable-driven systems is that in the multi-body systems, each link is subjected to not only the unilateral force of the cables, but also to the bilateral constraint forces and moments of the joints. This requires a new approach for the analysis of the tensionability. The proposed approach in this paper is based on the fundamental equilibrium equations. This will be shown to result that every subsystems of the cable-driven multi-body should satisfy the tensionability condition which also provides all the necessary conditions on the number of the cables attached to that sub-system. These necessary conditions will be then complied to provide the total sufficient number of the cables and their required distribution on the links.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.005 | 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".