2025/05/06 by Luis Miguel Vieira da Silva, Aljosha Köcher, da Silva, Luis Miguel Vieira +7 · 1 citation
Computer Science · #Artificial Intelligence (cs.AI) #E-Learning and Knowledge Management #FOS: Computer and information sciences #Open Education and E-Learning #Robotics (cs.RO) #Software Engineering (cs.SE)
paper · pdf · doi:10.48550/arxiv.2505.03295
openalex publication_date 2025/05/06 · openalex created_date 2025/10/16 · openalex updated_date 2026/07/29
Modern automation systems increasingly rely on modular architectures, with capabilities and skills as one solution approach. Capabilities define the functions of resources in a machine-readable form and skills provide the concrete implementations that realize those capabilities. However, the development of a skill implementation conforming to a corresponding capability remains a time-consuming and challenging task. In this paper, we present a method that treats capabilities as contracts for skill implementations and leverages large language models to generate executable code based on natural language user input. A key feature of our approach is the integration of existing software libraries and interface technologies, enabling the generation of skill implementations across different target languages. We introduce a framework that allows users to incorporate their own libraries and resource interfaces into the code generation process through a retrieval-augmented generation architecture. The proposed method is evaluated using an autonomous mobile robot controlled via Python and ROS 2, demonstrating the feasibility and flexibility of the approach.