Shared control architectures for haptic training: Performance and coupled stability analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A novel shared control architecture is presented for dual-user haptic training simulation systems for enhanced interaction between the users and between each user and the virtual environment. The coupled stability of the proposed control architecture against uncertainties in the environment and the user’s dynamics is investigated using the three-port master–slave network model of the dual-user haptic simulation system. For this purpose, Llewellyn’s unconditional stability criterion is applied to an equivalent two-port network model obtained from the corresponding three-port network, considering the environment as a load termination. The kinesthetic performance of the proposed architecture is numerically analyzed for transparency and evaluated against a benchmark control architecture under different operating conditions, such as various types of environments, users’ grasps, and levels of dominance of users over the task. An experimental user study is carried out to assess the effectiveness of the proposed architecture in terms of users’ perception of environment stiffness sensing, device agility, and haptic guidance reception.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 it