Investigation of human-robot interaction stability using Lyapunov theory
Bibliographic record
Abstract
For human-robot cooperation in the context of human-augmentation tasks, the stability of the control model is of great concern due to the risk for the human safety represented by a powerful robot. This paper investigates stability conditions for impedance control in this cooperative context and where touch is used as the sense of interaction. The proposed analysis takes into account human arm and robot physical characteristics, which are first investigated. Then, a global system model including noise filtering and impedance control is defined in a state-space representation. From this representation, a Lyapunov function candidate has been successfully discovered. In addition to providing conclusions on the global asymptotic stability of the system, the relative simplicity of the resulting equation allows the derivation of general expressions for the critical values of impedance parameters. Such knowledge is of great interest in the context of design of new adaptive control laws or simply to serve as design guidelines for conventional impedance control. The accuracy of these results were verified in a user study involving 7 human subjects and a 3-dof parallel robot. In this experiment, the real effective stability frontier was defined for each subject and compared with values predicted using the Lyapunov function.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".