Blind bulldozing: multiple robot nest construction
Bibliographic record
Abstract
In this paper, we present a collective, or swarm construction algorithm to control robotic bulldozers in the creation of a work site. Predictions about robotic missions to the planet Mars have described such site preparation as essential to the success of later mission objectives, such as the construction of solar arrays, etc. This algorithm was based on a behaviour observed in a particular species of ant called "blind bulldozing". We developed a mathematical model of blind bulldozing using a unique approach based on Markov chains. Robot bulldozers were developed and used to test the algorithms in our laboratory. The team of robots was found to be successful at clearing an open area out of field of rocks. Our robots' behaviour also agreed with the predictions of our model. This work is significant because it demonstrated the viability of blind bulldozing and represents the first time, to our knowledge, that a multiple robot system has carried out a form of the general construction task outside of simulation.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".