Domain-Specific Fine-Tuning of Large Language Models for Interactive Robot Programming
This addresses the challenge of robot programming being limited to experts in industrial settings, but it appears incremental as it focuses on fine-tuning existing models.
The paper tackles the problem of making industrial robot programming accessible to non-experts by developing a natural language-based assistant, and it investigates strategies for domain-specific fine-tuning of large language models with limited data and compute.
Industrial robots are applied in a widening range of industries, but robot programming mostly remains a task limited to programming experts. We propose a natural language-based assistant for programming of advanced, industrial robotic applications and investigate strategies for domain-specific fine-tuning of foundation models with limited data and compute.