ATLAS: A NOVEL KINEMATIC ARCHITECTURE FOR SIX DOF MOTION PLATFORMS
Bibliographic record
Abstract
Conventional training simulators commonly use the hexapod configuration to provide motion cues. While widely used, studies have shown that hexapods are incapable of producing the range of motion required to achieve high fidelity simulation required in many applications. This paper presents an overview of the Atlas platform: a novel six DOF motion platform architecture. Orienting is decoupled from positioning, and unlimited rotations are possible about every axis of the mechanism. The decoupling is accomplished by fixing a three DOF spherical orienting device, called the Atlas sphere, on a gantry with three linear axes. The key to the design is three omni-directional wheels in an equilateral arrangement, which impart angular motions to a sphere, thereby providing rotational actuation. The omni-wheels and their castor rollers provide virtually friction-free motion parallel to each omni-wheel rotation axis creating the possibility for unconstrained rotational motion. Since the Atlas sphere rests on these omni-wheels, there are no joints or levers constraining its motion, allowing full 360° motion about all axes. The motivation, architecture, and potential applications for this motion platform are described.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".