Exploring the use of tangible user interfaces for human-robot interaction
Why this work is in the frame
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Bibliographic record
Abstract
In this paper we suggest the use of tangible user interfaces (TUIs) for human-robot interaction (HRI) applications. We discuss the potential benefits of this approach while focusing on low-level of autonomy tasks. We present an experimental robotic interaction test bed to support our investigation. We use the test bed to explore two HRI-related task-sets: robotic navigation control and robotic posture control. We discuss the implementation of these two task-sets using an AIBO" robot dog. Both tasks were mapped to two different robotic control interfaces: keypad interface which resembles the interaction approach currently common in HRI, and a gesture input mechanism based on Nintendo Wii" game controllers. We discuss the interfaces implementation and conclude with a detailed user study for evaluating these different HRI techniques in the two robotic tasks-sets.
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 | 0.000 | 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 | 0.002 |
| 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