ChameleonControl: Teleoperating Real Human Surrogates through Mixed Reality Gestural Guidance for Remote Hands-on Classrooms
Bibliographic record
Abstract
We present ChameleonControl, a real-human teleoperation system for scalable remote instruction in hands-on classrooms. In contrast to existing video or AR/VR-based remote hands-on education, ChameleonControl uses a real human as a surrogate of a remote instructor. Building on existing human-based telepresence approaches, we contribute a novel method to teleoperate a human surrogate through synchronized mixed reality hand gestural navigation and verbal communication. By overlaying the remote instructor’s virtual hands in the local user’s MR view, the remote instructor can guide and control the local user as if they were physically present. This allows the local user/surrogate to synchronize their hand movements and gestures with the remote instructor, effectively teleoperating a real human. We deploy and evaluate our system in classrooms of physiotherapy training, as well as other application domains such as mechanical assembly, sign language and cooking lessons. The study results confirm that our approach can increase engagement and the sense of co-presence, showing potential for the future of remote hands-on classrooms.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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 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".