New XY-Theta Positioning Table with Partially Decoupled Parallel Kinematics
Bibliographic record
Abstract
Parallel robots provide an efficient solution in a world demanding better positioning accuracy. These robots are preferred over their serial counterparts because each leg helps support the platform, thus reducing the need to add means for extra support. The problem with parallel robots though is that most are coupled and difficult to control. In this paper, new parallel robot architecture has been proposed that can deliver accurate movements in addition to being partially decoupled and fast. This is a significant technological advantage over current designs because a decoupled robot is simpler to control as each actuator is independent. Furthermore, its displacement resolution is less variable throughout the workspace. To achieve the decoupled state, this parallel robot took the novel approach of having mixed legs. By comparing this robot to existing commercial devices through kinematic, singularity, workspace, velocity and dexterity analysis, this paper would like to show that this new design should be looked into further to create a precision positioning table that is parallel, decoupled, and highly accurate
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".