An LLM-based approach for enabling seamless Human-Robot collaboration in assembly
Christos Gkournelos, Christos Konstantinou, Sotiris Makris
Abstract
The complexity in the collaboration between humans and robots in smart manufacturing remains a significant challenge. This paper introduces an LLM-based manufacturing execution system enhancing Human-Robot Collaboration (HRC) in smart manufacturing. By leveraging Large Language Models (LLMs), the system provides a natural language interface for operators, integrates with Digital Twins for real-time data, and employs behavior-based control for robots. This integration facilitates intuitive interactions and rapid system programming, addressing communication complexities in HRC. The effectiveness of this approach is validated through two HRC assembly case studies, demonstrating significant improvements in collaboration and efficiency.