Development of whole-body humanoid “pneumat-BS” with pneumatic musculoskeletal system
Bibliographic record
Abstract
Unwanted conflicts are inevitable between collaborating agents that share spaces and resources. Motivated by the use of nonverbal communications as a conflict resolution mechanism by humans, this study investigates the communicative capabilities reflected in the trajectory characteristics of hesitation gestures during human-robot collaboration. Hesitation gestures and non-hesitation human arm motions were recorded from a series of reach-and-retract tasks and embodied on a 6-DOF robot arm. A total of 86 survey respondents watched and scored recordings of these motions according to whether they recognized hesitation gestures as exhibited by both the human and the robot. Using the survey's statistical evidence indicating that hesitation trajectories embodied in an articulated robot arm can be recognized by human observers, we identified trajectory characteristics of hesitation gestures. The contribution of our work is an empirically grounded robot trajectory specification that provides communicative cues for conflict resolution during collaborative reaching scenarios.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".