This research introduces a large language model (LLM) system that gives quadrupedal robots the ability to handle long-horizon tasks requiring both high-level reasoning and physical interactions.

• Combines LLMs for semantic understanding and task planning with locomotion/manipulation skills
• Creates a hybrid task planning approach for complex problem-solving
• Enables robots to perform long sequences of actions while understanding environmental context
• Demonstrates practical applications in engineering and factory settings

This breakthrough matters for engineering because it bridges the gap between AI reasoning and physical robotics capabilities, potentially revolutionizing industrial automation, security applications, and complex manufacturing processes.

Long-horizon Locomotion and Manipulation on a Quadrupedal Robot with Large Language Models