SwarmFidget: Exploring Programmable Actuated Fidgeting with Swarm Robots
Bibliographic record
Abstract
Fidgeting is a common behavior that one tends to engage in during periods of inattention or mind wandering. Although attempts were undertaken to enhance fidget devices with advanced technology, such as sensors and displays, no works exist that explored fidgeting with actuated devices. To fill this gap, we introduce the concept of programmable actuated fidgeting and the design space for SwarmFidget. Programmable actuated fidgeting is a type of fidgeting that involves devices integrated with actuators, sensors, and computing to enable a dynamic and customizable interactive fidgeting experience. SwarmFidget is an instance of a platform where tabletop swarm robots are used to facilitate programmable actuated fidgeting. To engage with actuated fidgets, users can input commands through various modalities such as touch or gesture, and the actuators in the fidgeting device will respond in a programmable manner to provide haptic, visual, or audio feedback.
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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 | 0.000 | 0.001 |
| 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) | 0.004 | 0.001 |
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".