A Highly-Geared Haptic Actuator using 3D Printed Magnetorheological Clutches
Bibliographic record
Abstract
<title>Abstract</title> Advanced robotic systems such as humanoid robots need actuators with high torque density but yet, with good haptic abilities, in order to interact transparently with people. Combining these two requirements presents an important challenge for conventional gearmotors due to a gearing design conflict where gearing increases torque density but only at the cost of reduced haptic performance. Recent research suggests that magnetorheological (MR) actuators have the potential to greatly reduce the gearing design conflict by introducing a small fluidic clutch between the “gear” and the “motor” which allows maintaining excellent haptic performance at high gearing. Fully extracting the benefits of MR actuators requires pushing gearing ratios above 100:1 in combination with miniature low friction and inertia clutches which presents serious manufacturing challenges. This paper presents a manufacturing solution for such miniature, low friction and inertia, 3D printed MR clutch design and integration in an actuator with 120:1 gearing ratio. An extensive experimental characterisation is conducted on a fully-functional actuator showing excellent backdrivability and frequency response even with such high gearing levels thus opening the door to a future generation of torque-dense, but yet haptic robot actuators.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".