EELS-DARTS: A Versatile Multibody Dynamics Simulator for Autonomous Snake-Like Robots
Bibliographic record
Abstract
EELS-DARTS is a first of its kind versatile multibody dynamics simulator designed for autonomy development and analysis of large-scale snake-like robots. A detailed description of the EELS-DARTS simulator design is presented. This includes the versatile underlying multibody representation used to model a variety of distinct snake robot configurations. A simple anisotropic friction model for describing screw-ice interaction is derived. Additional simulation components such as graphics, importable terrain, joint controllers, and perception are discussed. Methods for setting up and running simulations are discussed, including how the snake robot autonomy stack exchanges commands and information with the simulation via ROS. Multiple use cases are shown that represent how the simulation was used to aid and inform designs at distinct points in the robot life cycle. A validation analysis of the screw-ice contact model is performed for the surface mobility case. Lastly, an overview of simulation use throughout field test planning and operations during a recent trip to the Athabasca Glacier in Canada is discussed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".