Realization of Efficient Rotational Springs and Series Elastic Actuators Using DC Motors
Bibliographic record
Abstract
In this paper, a review of adjustable rotational springs is presented along with their application in robotic systems. To this end, the process of implementing an adjustable rotational spring using DC motors and their limitations is presented. Additionally, Series Elastic Actuators (SEAs) as one of the important applications of an adjustable spring are investigated. A review of motor parameters and their effect on achievable stiffness values is presented using available DC motors in the market. Finally, Simulations and comparative studies are presented using MATLAB/Simulink to show that correct selection of the series spring plays a significant role in achieving an efficient SEA with a relatively good stiffness tunability. To this end, a comprehensive parametric sweep study is conducted over different parameters such as amplitude of the rotational deflection, angular velocity, inertia of the rotor, and gearbox ratio of the motor. The findings of this study, facilitates the road for a systematical development of SEAs for various robotic applications.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".