mROBerTO: A modular millirobot for swarm-behavior studies
Bibliographic record
Abstract
Millirobots have increasingly become popular over the past several years, especially for swarm-behavior studies, allowing researchers to run experiments with a large number of units in limited workspaces. However, as these robots have become smaller in size, their sensory capabilities and battery life have been reduced. A number of these have also been customized, with few off-the shelf components, exhibiting integral (i.e., non-modular) designs. In response to the above concerns, this paper presents a novel open-source millirobot with a modular design based on the use of easily sourced elements and off-the-shelf components. The proposed milli-robot-Toronto (mROBerTO), is a 16×16 mm2robot with a variety of sensors (including proximity, IMU, compass, ambient light, and camera). mROBerTO is capable of formation control using an IR emitter and detector add-on. It can also communicate via Bluetooth Smart, ANT+, or both concurrently. It is equipped with an ARM processor for handling complex tasks and has a flash memory of 256 KB with over-the-air programming capability.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".