Efficient Reconfiguration for Lattice-Based Modular Robots
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Bibliographic record
Abstract
Abstract — Modular robots consist of many small units that attach together and can perform local motions. By combining these motions, we can achieve a reconfiguration of the global shape. The term modular comes from the idea of grouping together a fixed number of units into a module, which behaves as a larger individual component. Recently, a fair amount of research has focused on Crystalline robots, whose units (and modules) fit on a cubic lattice. When the proper module size is formed, these robots can reconfigure in linear time within a rather physically restrictive model, or in O(log n) time in a more unrestricted theoretical model. In this paper, we show that the results for Crystalline robots also apply to two other modular robots: M-TRAN and Molecube. The common requirement, for each robot type, is that a fixed number of units combine to create modules of specified shapes. In this way, we are able to simulate the actions of Crystalline modules. Previous reconfiguration bounds thus transfer automatically, as long as the robots are composed of the module shapes that we specify. Index Terms — self-reconfiguring modular robots, cubical units, lattice reconfiguration. I.
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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 | 0.000 | 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 | 0.000 | 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