Modeling Humans for Humanoid Robots - A Two-Level Learning Framework

Watch a Stanford University seminar exploring a two-level learning framework for humanoid robots presented by UC San Diego's Xiaolong Wang. Discover how Vision-Language-Action models trained on human video data enable navigation and manipulation skills, while teleoperation and motion imitation develop low-level robot control capabilities. Learn about the framework's approach to combining human behavioral modeling with robotic skills to create general-purpose humanoid robots capable of performing diverse daily tasks. Gain insights into the latest developments in robotics research focused on making humanoid robots operate more naturally and effectively across different environments and scenarios. Delve into both the high-level AI models that process visual and linguistic inputs and the practical implementation of robotic movement and control systems.