Trajectory-Attracted Tracking Control for Robotic Systems Based on an Admittance-Based Guiding Vector Field
Bibliographic record
Abstract
This article proposes a trajectory-attracted tracking control (TATC) scheme for robotic systems based on an admittance-based guiding vector field (AGVF). The AGVF is designed to be equipped with the admittance characteristic and convergence, which is used to deal with the time-varying contact force to achieve compliance and trajectory attraction, making human–robot interaction control possible within the framework of the guiding control methods. Also, the convergence and robustness of the AGVF are analyzed. Furthermore, the TATC is designed by using the guiding information of the AGVF, which is a trajectory-attracted scheme with compliance performance. The stability of the TATC scheme is analyzed by using the Lyapunov theorem. Finally, the effectiveness of the proposed method is validated through both simulation and experimental tests.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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".