Scaling Behavior Foundation Model for Humanoid Robots
Humanoid control requires natural whole-body coordination, precise real-time responses to control signals, and robust generalization across diverse environmental contexts, making it a cornerstone for generalist embodied agents. Behavior Foundation Models (BFMs) have recently emerged as a promising solution to address these challenges by leveraging large-scale behavioral data to achieve superior expressiveness, versatility and generalization. However, despite growing interest in scaling BFMs to further improve their capabilities, it remains unclear how key factors, including the learning paradi
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- PossiblePossibly related (embedding) · 52%UK startup Humanoid launches reinforcement learning system to improve robot manipulation - Robotics & Automation News →
- PossiblePossibly related (embedding) · 51%Towards shared embodied intelligence in humanoid robots through optimization, development and testing of the human-aware ergoCub robot →
- PossiblePossibly related (embedding) · 49%Xiaomi Open-Sources Robotics-U0: A 38B-Parameter Embodied Generative Model That Unifies Four Robot Tasks - Pandaily →
- PossiblePossibly related (embedding) · 46%Building a Foundation Stack for General-Purpose Robots →
- FuzzyOverlapping authors or contributors · 62%bytedance/deer-flow →
“Shared author/contributor keys: wang”
- FuzzyOverlapping authors or contributors · 62%Zeyi-Lin/HivisionIDPhotos →
“Shared author/contributor keys: lin”
- FuzzyOverlapping authors or contributors · 62%rasbt/LLMs-from-scratch →
“Shared author/contributor keys: yin”
- FuzzyOverlapping authors or contributors · 62%sgl-project/sglang →
“Shared author/contributor keys: zhou”