Embodied Control

Embodied control focuses on enabling robots to effectively interact with their physical environment through integrated perception, planning, and action. Current research emphasizes developing robust and efficient control strategies, often leveraging large language models (LLMs) to translate high-level instructions into low-level control commands, and exploring biologically-inspired neural network architectures for improved data efficiency and transferability. These advancements are significant for improving robot dexterity, adaptability, and safety in diverse applications, ranging from mobile manipulation to human-robot collaboration.