Experimental Evaluation of Two Bilateral Control Schemes Applied to a Tele-Operated Hydraulic Actuator
Bibliographic record
Abstract
Providing force feedback along with other sensory information can greatly increase task quality, productivity, and safety during teleoperation of hydraulic manipulators. However, as compared to the class of electrically-actuated robots, research on application of bilateral control schemes applied to the class of hydraulic manipulators is sparse. In this paper, we present experimental results of implementing two bilateral control scheme, previously developed for electrically-actuated manipulators, to a hydraulic actuator having additional nonlinear dynamics. The two schemes chosen are ‘force reflection’ and ‘position error’. The performance of each scheme is evaluated in terms of position tracking, force tracking, and fidelity of perceived stiffness by the human operator. The results reveal specific features of each scheme paving the road for future research in this direction in terms of designing appropriate bilateral control schemes for hydraulic manipulators.
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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) | 0.000 | 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) | 0.001 | 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".