Contact parameter identification for robotic systems
Why this work is in the frame
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Bibliographic record
Abstract
This paper reviews and compares three impedance control algorithms with respect to identificatio n of environment stiffness and damping during robot constrained motion. Estimates of these parameters, also referred to as contact parameters, are valuable for force-tracking and stability of impedance force controllers. Our primary interest in identifying these parameters stems from their use as inputs to dynamics simulation software with contact dynamics capability. The algorithms considered in this work include: an indirect adaptive controller with modifications to identify environment damping, an MR AC controller and a recursive least-squares estimation technique. A benchmark test was performed using both numerical simulation and experimentation. Our results indicate that the indirect adaptive controller has the best combination of performance and ease of use. In addition, the effect of persistently exciting signals is discussed.
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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