Mobility and singularity analyses of a symmetric multi-loop mechanism for space applications
Bibliographic record
Abstract
A symmetric, double-tripod multi-loop mechanism (DTMLM), for aerospace applications, is the subject of this paper. Its mobility and singularity are analyzed, while introducing a novel tool, the cell-division method for singularity analysis, applicable to multi-loop mechanisms. The key principle of this method lies in replacing the singularity analysis of the original multi-loop mechanism with: (1) that of an equivalent simpler parallel mechanism; (2) the constraint analysis between loops; and (3) the singularity analysis of simpler kinematic subchains. Then, the mechanism is transformed into a simpler, equivalent parallel mechanism with three identical kinematic subchains. Its mobility and singularity are analyzed based on screw algebra, which leads to a key conclusion about the geometric properties of this mechanism. Results show that: (a) the DTMLM has three degrees of freedom (dof), i.e., two rotational dof around two intersecting axes lying in the middle plane of the mechanism, and one translational dof along the normal to the said plane (2R1T); and (b) the singularities of the 3-RSR parallel mechanism are avoided in the DTMLM by means of prismatic joints, singularities in the DTMLM occurring on the boundary of its workspace. Thus, the DTMLM has a 2R1T mobility everywhere within its workspace. When a set of multi-loop mechanisms of this kind are stacked as modules to assemble a multi-stage manipulator for space applications, the modules can be designed so that, under paradigm operations, all individual loops operate within their workspace, safe from singularities.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".