One Model, Any Scenario: End-to-end Locomotion from Vision

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Introduces the low-level control capabilities of Skild Brain, enabling end-to-end locomotion driven entirely by online vision and proprioception. The single neural network directly outputs low-level motor commands from raw images and joint feedback, allowing robots to adapt dynamically to new terrain, climb stairs, and step over obstacles without prior planning or mapping. Demonstrates robustness, adaptability, and precise footwork in real-world scenarios, including carrying payloads.