GenAI for Robot System Engineering

While there are several approaches to use generative artificial intelligence (GenAI) for a simplified generation of robot programs, only limited knowledge exists on the use of GenAI for robot system configuration. However, to support non-experts in deploying robots, this initial setup of the system is crucial. Therefore, an agent-based tool is proposed, combining large language models (LLMs) with retrieval augmented generation (RAG), few-shot learning and a set of available actions to generate configuration files in a desired format based on user input. A key component of the approach is a feedback loop that provides error messages from the robot controller to the AI-agent that can be exploited in a subsequent trial. A prototypic implementation of the agent-based approach is used to demonstrate several use cases. Although evaluations and analysis with additional use cases is needed to gain scientific rigorous conclusions, it showcases high potential of such an approach for real-world applications, and problems and ideas for further developments can be identified.