A High-Bandwidth Back-Drivable Hydrostatic Power Distribution System for Exoskeletons Based on Magnetorheological Clutches
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Exoskeletons are increasingly interesting for human assistance applications ranging from rehabilitation to force enhancement. However, today's exoskeletons are relatively slow and lack the mechanical transparency required to complete several daily tasks, mainly due to their bulky and non-back-drivable actuation mechanisms. To improve upon conventional exoskeleton designs, this letter presents a novel power-distribution system that combines magnetorheological (MR) clutches and low-friction hydrostatic transmissions using rolling diaphragms. In such a system, MR clutches are used to rapidly modulate the torque provided from a centralized power source and distribute it to each joint through a high-bandwidth, back-drivable, and low-inertia transmission. The main objective of this letter is to investigate the transparency performance of the MR-hydrostatic power distribution in terms of its force-bandwidth and back-drivability with the aim of being used in future exoskeletons. Experiments with a custom one degree-of-freedom haptic joint are supported by an analytical model that demonstrates the high bandwidth (>40 Hz) and good backdrivability (2-11% of peak force) of an MR-hydrostatic system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it