Adaptive nonlinear teleoperation control in multi-master/multi-slave environments
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Bibliographic record
Abstract
An adaptive nonlinear control framework for multi-master/multi-slave teleoperation is proposed. A fully connected communication architecture is considered, which allows for transmission of position and force information between all master and slave robots. The operators are presented with a virtual intervening tool in order to collaboratively interact with the task environment. Models of operators, master and slave robots, tool, and environment are incorporated in the design. The performance and stability of cooperative teleoperation are guaranteed under dynamic interactions between slave robots and in the presence of model uncertainty. The robustness of the control system with respect to communication latency is also analyzed. Experimental studies demonstrate that the proposed approach is highly effective in all phases of a teleoperation task, i.e. in free motion and in contact with both flexible and rigid environments
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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 | 0.001 |
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