Style by demonstration for interactive robot motion
Bibliographic record
Abstract
As robots continue to enter people's everyday spaces, we argue that it will be increasingly important to consider the robots' movement style as an integral component of their interaction design. That is, aspects of the robot's movement which are not directly related to a task at hand (e.g., pick up a ball) can have a strong impact on how people perceive that action (e.g., aggressively or hesitantly). We call these elements the movement style. We believe that perceptions of this kind of style will be highly dependent on the culture, group, or individual, and so people will need to have the ability to customize their robot. Therefore, in this work we use Style by Demonstration, a style focus on the more-traditional programming by demonstration technique, and present the Puppet Dancer system, an interface for constructing paired and interactive robotic dances. In this paper we detail the Puppet Dancer interface and interaction design, explain our new algorithms for teaching dance by demonstration, and present the results from a formal qualitative study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".