Accuracy/Stability Trade-Off and Hybrid Impedance and Admittance Control for Haptic Devices
Bibliographic record
Abstract
This paper investigates the use of Hybrid Impedance and Admittance controllers for navigating an accuracy/stability trade-off in haptic devices. Typically, sensitivity to modelling error in Impedance control (IC) and force sensor error in Admittance control (AC) is reduced by increasing the desired impedance parameters. This, however, couples the design of the interaction behaviour to the design of a stable and accurate control system. Instead, we propose that interpolating between IC and AC using methods like Unified Interaction Control can balance the relative sensitivities to modelling error and force sensor error, potentially improving stability in AC in the presence of force delays or improving accuracy in IC in the presence of parametric uncertainty and friction. This is particularly applicable when the haptic device has a high physical impedance (in terms of friction, gear reductions, etc), or when the desired impedance is lower than the physical impedance. Interpolation is demonstrated on a high impedance haptic device for the lower-limbs.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".