Embodied Reasoning

Embodied reasoning focuses on developing AI agents capable of understanding and interacting with the physical world by integrating perception, reasoning, and action. Current research emphasizes improving agents' ability to follow complex natural language instructions, often involving inferring human intentions and utilizing multi-modal data (e.g., vision and language) within online, real-time frameworks. This involves leveraging large language models, often in conjunction with novel architectures for efficient 3D perception and skill learning, to achieve robust and generalizable performance in tasks ranging from object manipulation to scene understanding. The advancements in this field are crucial for creating more capable and adaptable robots and AI systems for various real-world applications.