Adaptive Haptic Control for Telerobotics Transitioning Between Free, Soft, and Hard Environments
Bibliographic record
Abstract
This paper presents an adaptive haptic control for a one degree-of-freedom master-slave teleoperated device. The aim is to reduce excessive collision forces that occur when there are significant time delays in master-slave communication. The control design also allows the operator to move the slave in free space and in a soft medium. Previous approaches to haptic teleoperation typically design for either movement in a medium or constrained contact with a solid surface; then, it is up to the operator to avoid collisions or precisely anticipate collisions. The proposed control runs on the slave side inner loop, with no time delay, and tracks commanded forces from the outer loop. A Lyapunov-stable backstepping-with-tuning-functions design provides a way to ensure smooth forces are applied that guarantee stability in the presence of unmodeled environmental stiffness and viscosity. Experiments using a Phantom hand controller interacting with simulated environment show that collision forces are substantially reduced compared to two other control methods. In collision-free operation, the performance is comparable to other methods.
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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 | 0.000 | 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 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".