Design and Modelling of SCARA Robot Variant
Bibliographic record
Abstract
Abstract The SCARA robot has been extensively used for industrial applications. The motivation behind this research is to propose a SCARA variant as an alternative, with the popularity and applications of a SCARA robot. The main objective is to relocate the vertical prismatic joint and study the computational dynamics of the SCARA variant and the performances. The SCARA variant has been analyzed for the forward and inverse kinematics based on the transformation matrix method. The dynamic model for the SCARA variant has been developed by using the Lagrangian method. The dynamic model is compared to the standard SCARA, it has been found that the dynamic models are very similar apart from the mass inertia and Coriolis matrices having terms in columns 2 & 3 exchanged. In this paper, linear and nonlinear trajectories, such as straight line, ellipse, and circular trajectories have been selected in the simulation study. Consistent results for torque requirements have been observed with the linear trajectory having the least values, followed by ellipse, and the circular trajectory.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".