Bilateral Teleoperation Over Networks Based on Stochastic Switching Approach
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Bibliographic record
Abstract
In this paper, new control strategies based on linear matrix inequalities and Markov jump linear systems are proposed for bilateral teleoperation systems over networks with random time delays and packet losses. The characteristics of the network are thoroughly incorporated in the design and two cases are considered: where both communication directions behave identically and where they are independent. In both cases, the tracking error is shown to be bounded by the rate of change of the external forces acting on the teleoperation system. The theoretical results are verified with simulation results using experimentally collected network data to show the performance of the proposed scheme as well as how to fine-tune the controller gain to balance the tradeoff between force and position fidelity. Experimental teleoperation results are then presented that show the practical performance of the proposed control scheme.
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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 | 0.001 |
| 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