A Framework for Steering Dynamic Robotic Locomotion Systems
Why this work is in the frame
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Bibliographic record
Abstract
We seek to formulate control and motion planning algorithms for a class of dynamic robotic locomotion systems. We consider mechanical systems that involve some type of interaction with the environment and have dynamics that possess rotational and translational symmetries. Research in non-holonomic systems and geometric mechanics has led to a single, simplified framework that describes this class of systems. In this paper, we explore a hybrid systems approach to generating motion plans for systems of this type. We perform a dynamic analysis of the system to find a small set of periodic control inputs for momentum generation in desired directions. We then find a simplified, kinematic model which captures the fundamental nature of the locomotion system and we use this abstract model for motion planning. This approach is inherently modular, since broad classes of locomotion systems can be described by the same kinematic approximation. In this paper, we describe the application of such an approach to two examples: the snakeboard robot and an eel-like, underwater robot.
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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 | 0.002 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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