Analysis of kinematic characteristics of 2-P(RPS + UPS) parallel mechanism with six degrees of freedom
Bibliographic record
Abstract
At present, there is an increasing demand for the workspace required for the assembly of components, and a parallel mechanism with a large workspace is urgently needed to make up for it. Therefore, in this paper, a 2-P(RPS + UPS) parallel mechanism (where S, P, R, and U represent spherical, prismatic, revolute, and universal joints) with four branched chains and six degrees of freedom is proposed and its kinematic characteristics are analyzed. First, the speed of the 2-P(RPS + UPS) parallel mechanism is numerically derived and verified by simulation using ADAMS software. Then, the motion decoupling characteristics of the mechanism are analyzed from the expression of the speed and position relationship between the input and output of the mechanism. To minimize the force on each branch in the workspace, scale optimization of the 2-P(RPS + UPS) mechanism and the Stewart mechanism is performed. Further, analysis of the dexterity, singularity, and workspace of the 2-P(RPS + UPS) mechanism is conducted, and the performance of the mechanism is compared with that of the Stewart mechanism. The proposed parallel mechanism has fewer branches, a simple kinematic model, strong motion decoupling, a high bearing capacity, a large workspace, and a low initial position height. Moreover, it can be conveniently transported and stored. Therefore, it has good application prospects in assembly and posture adjustment scenes requiring large workspaces.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".