A TD-Learning Based Bionic Cerebellar Model Controller For Humanoid Robots
Why this work is in the frame
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Bibliographic record
Abstract
The cerebellum is a crucial component of the human body that plays a vital role in human walking. To design a robot gait controller by referring the working mechanism of the cerebellum is one of the hotspots in the bionic control field. This paper designs a bionic cerebellar motion control model to control the slope gait of a humanoid robot. The cerebellum model refers to the connection method between neurons in a human cerebellum, and expresses from a bionic perspective how the neurons in the cerebellum process external information and generate control commands during walking. Inspired by how human walking is learned, this model employs reinforcement learning in the learning process of the bionic cerebellar model. A corresponding simulation environment is also designed to train and test the cerebellar control model's effectiveness when regulating a robot's slope walking stability. The simulation experimental results demonstrate that the cerebellum model can achieve stable control of the walking motion of the humanoid robot after training, verifying its effectiveness, and laying a foundation for further realization of human-like artificial intelligence.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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