Adaptive force-motion control of coordinated robots interacting with geometrically unknown environments
Why this work is in the frame
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Bibliographic record
Abstract
Most studies on adaptive coordination of multi-robot systems assume exact knowledge of system kinematics and deal with dynamic uncertainties. However, many industrial applications involve tasks in which a multi-robot system interacts with geometrically unknown environments. In this paper we consider a multi-robot system grasping a rigid object which is in contact with a frictionless surface with unknown geometry. The proposed adaptive hybrid force-motion controller guarantees asymptotic tracking of desired motion and force trajectories while ensuring exact identification of tangential and normal directions to the constraining surface without persistency of excitation condition. The control signal is smooth and no projection is used in parameter update law. A simulation example is presented to illustrate the results.
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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