Mixed Autonomous/Teleoperation Control of Asymmetric Robotic Systems
Bibliographic record
Abstract
This paper presents a unified framework for system design and control in human-in-the-loop asymmetric robotic systems. It introduces a highly general teleoperation system configuration involving any number of operators, haptic interfaces, and robots with possibly different degrees of mobility. The proposed framework allows for mixed teleoperation/autonomous control of user-defined subtasks by establishing position/force tracking as well as kinematic constraints among relevant teleoperation control frames. The control strategy is hierarchical comprising of a high-level teleoperation coordinating controller and low-level joint velocity controllers. The approach utilizes idempotent, generalized pseudoinverse and weighting matrices in order to achieve new performance objectives that are defined for such asymmetric semi-autonomous teleoperation systems. Three layers of velocity-based autonomous control at different priority levels with respect to human teleoperation are integrated into the framework. A detailed analysis of system performance and stability is presented. Experimental results with a single-master/dual-slave system configuration demonstrate an application of the proposed system design and control strategy.
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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".