Exploring the effect of robot hand configurations in directional gestures for human-robot interaction
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
In this work we explore the effectiveness of a three-fingered robotic gripper in accurately expressing directional instructions (move up, down, left, right) as gestures emulating human hand gestures. Such gestures can be necessary in noisy manufacturing environments where verbal communication is ineffective. Three studies are conducted. In Study 1 we explore hand configurations that human dyads use for nonverbal instruction (n = 17). In Study 2 we examine which hand-configurations from Study 1 are most accurately understood by observers (n = 140). In Study 3 we compare performance between a robot arm performing similar motions to those of human study participants using either an unposed or posed three-fingered robotic gripper (n =100) to observe the importance of the hand's pose. Recognition rates of directional gestures for both the human and the robot are examined. Results indicate that most gestures are better and more confidently recognized when displayed with the posed robot hand.
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 | 0.001 | 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 | 0.001 |
| 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