华人团队之光！CoRL2025最佳论文（北京通用人工智能研究院&宇树等）

Core Insights - The article highlights significant advancements in the field of robotics and autonomous driving, particularly from the CoRL 2025 conference held in Seoul, South Korea, where notable research papers were awarded for their contributions to the field [2][10]. Research Highlights - The Best Paper award was given to a collaborative research effort from the Beijing Academy of Artificial Intelligence, Yushu Technology, and Beijing University of Posts and Telecommunications for their work titled "Learning a Unified Policy for Position and Force Control in Legged Loco-Manipulation," focusing on a hybrid force/position control model [2][10]. - The Best Student Paper award went to a team from the University of California, Berkeley for their paper "Visual Imitation Enables Contextual Humanoid Control," which addresses motion control across embodied agents [5][10]. Finalist Overview - Several finalist papers were recognized, including: - "LocoFormer: Generalist Locomotion via Long-context Adaptation," which involves motion control for embodied agents [10]. - "Fabrica: Dual-Arm Assembly of General Multi-Part Objects via Integrated Planning and Learning," focusing on dual-arm planning and control strategies [10]. - "DexUMI: Using Human Hand as the Universal Manipulation Interface for Dexterous Manipulation," which explores human-robot interaction and data collection [10]. - "The Sound of Learning Simulation: Multimodal Sim-to-Real Robot Policies with Generative Audio," which combines generative models with multimodal approaches [10]. - "Pi 0.5: a Vision-Language-Action Model with Open-World Generalization," which presents a foundational model for vision-language-action tasks [10]. - "Steering Your Diffusion Policy with Latent Space Reinforcement Learning," which integrates generative models with reinforcement learning [10]. Community Engagement - The article mentions the establishment of nearly 100 technical discussion groups related to various aspects of autonomous driving, including large models, end-to-end systems, and multi-modal perception [12][14]. - A community of approximately 4,000 members has been formed, with over 300 autonomous driving companies and research institutions participating, covering more than 30 learning pathways in autonomous driving technology [14].