Design and Motion Principle Analysis of new parallel mechanisms with fewer active inputs than the degrees of freedom
Bibliographic record
Abstract
Abstract In this paper, two new parallel mechanisms (PMs) with fewer active inputs than the degrees of freedom (DOFs)are proposed: (i) an nSPS (n = 7, 8, 9) six‐DOF PM with n‐6 active inputs and six lockable joints. and (ii) a 3RPS‐SPS 3‐DOF PM with one active input and three lockable joints. Compared with the traditional PMs, the difference is that the proposed PMs can achieve the same mobility by using a minimal number of active joints. Moreover, the load‐carrying capacity is also improved compared with the original standard mechanisms, since the new PMs become statically redundant when all the branches are locked. For this purpose, a sequential motion control principle is introduced that requires both inverse and forward kinematics of PMs. Kinematic modeling, dimensional optimization, and structural design are carried out for the 7SPS and 3RPS‐SPS mechanisms, and the two prototypes are constructed for experimental validation. Both simulation and experiment results have shown that the proposed hybrid PM can achieve the original mobility while significantly reducing the number of actuators.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".