Build‐A‐Robot: Using virtual reality to visualize the Denavit–Hartenberg parameters
Bibliographic record
Abstract
ABSTRACT Virtual reality‐based educational tools allow students to visualize and interact with three‐dimensional objects in ways that cannot be achieved using traditional teaching methods. This type of educational tool is especially relevant to mechanically‐complex courses, such as those pertaining to robotics and mechatronics. Build‐A‐Robot is such a tool, created using the Virtual Reality Modeling Language (VRML), MATLAB, and the Simulink 3D Animation Toolbox, to study the forward kinematics of serial robot arms according to the Denavit–Hartenberg convention. This tool is described, and the power of using MATLAB to directly manipulate VRML geometric dimensions is explored. The potential of this tool is evidenced by student survey responses and examination results. © 2015 Wiley Periodicals, Inc. Comput Appl Eng Educ 23:846–853, 2015; View this article online at wileyonlinelibrary.com/journal/cae ; DOI 10.1002/cae.21656
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".