Interpolating across the impedance/admittance spectrum with Unified Interaction Control
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
Abstract Impedance Control (IC) and Admittance control (AC) are two control methods for robot-environment interaction which have opposing performance and stability characteristics. Previous research has proposed that the two controllers define a spectrum of controllers. This paper quantifies the IC/AC spectrum as a trade-off between the suppression of force sensor error and modelling error. Unified Interaction Control (UIC) is introduced, which can interpolate across this spectrum of controllers by using a periodic state-reset and an inner-loop gain weighting parameter. The UIC is verified through simulation, experiment, and an eigenvalue analysis. Interpolating across the spectrum allows one to choose an ideal controller given the nature of the robot and environment. This is demonstrated in two case studies: adapting the level of interpolation to optimize performance with a changing environment, and using a static level of interpolation to mitigate the worst-case effects in both IC and AC.
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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