Generative control for a physical embodiment.
Adapting pretrained motion structure to the joint topology, observations, and control cycle of the Unitree G1.
Explore the workResearch
Explore the problems, methods, and validation boundaries behind our work.
Adapting pretrained motion structure to the joint topology, observations, and control cycle of the Unitree G1.
Explore the workTesting what survives a change in simulator, operating conditions, and inference runtime.
Explore the workA quantitative research stack that shaped our approach to uncertainty, reward design, and honest evaluation.
Explore the workEvaluation philosophy
A model’s output is only meaningful within the conditions used to train, test, and execute it.
Compare additional complexity against simpler alternatives.
Distinguish prediction, decision, execution, and integration errors.
Challenge behavior under noise, uncertainty, and distribution shift.
Connect observations, outputs, commands, and measured responses.
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