Implementation of Oil-Based Hydraulic Artificial Muscles in a Bio-Inspired Configuration
Bibliographic record
Abstract
The hydraulic artificial muscles (HAMs) have been studied recently due to the high power/weight ratio, inherent safety and their human-like characteristics which provide a great potential in biomedical applications like exoskeleton robots and artificial limbs. In this paper, a new oil-based hydraulic artificial muscle (OHAM) with a bio-inspired configuration is presented. The common parts in traditional pneumatic artificial muscles (PAMs) like compressors, pumps and tanks are replaced with linear actuator and cylinders which makes the platform of the OHAM more compact. Moreover, a phenomenological model is used for the dynamic modeling of the OHAM in the static and dynamic states. Then, a new program in LabVIEW software is developed for the signal processing of the system which helps applicants visualize every aspect of the experimental tests, including hardware configuration, data measurement, and troubleshooting. Additionally, characteristics of the OHAM are determined by the implementation of experimental tests for a single artificial muscle. Finally, the bio-inspired configuration is implemented in order to demonstrate the usefulness of the hardware and software of OHAMs in an opposing pair configuration.
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.
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) | 0.000 | 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 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".