A Python framework for robot skill development and automated generation of semantic descriptions
Publication date
2023-10-12
Document type
Konferenzbeitrag
Organisational unit
Conference
28th International Conference on Emerging Technologies and Factory Automation (ETFA 2023) ; Sinaia, Romania ; September 12–15, 2023
Publisher
IEEE
Book title
2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)
Part of the university bibliography
✅
Language
English
Keyword
dtec.bw
Abstract
Heterogeneous teams of autonomous robots offer a number of benefits for a variety of applications. But deploying such robots is a complex task that requires machine-interpretable descriptions in order to be flexible and adaptable. Formal descriptions in the form of ontologies are increasingly used to describe the functions of such autonomous robots in the form of capabilities and skills. However, these ontological descriptions and a corresponding invocation interface for skills need to be created, causing additional efforts for developers which are complex, time-consuming and error-prone. This contribution presents a Python framework that automates all these additional efforts. It supports a developer in implementing functionalities as skills by having them program only the skill behavior. The framework automatically takes care of generating a standardized state machine, an invocation interface and an ontological description. The presented framework can be used to implement arbitrary functionalities as skills using Python. This is demonstrated using two different evaluation case studies: a simplified behavior of a mobile robot as well as a machine learning algorithm used as an analytical skill for quality control. Both are integrated into an existing skill execution system and can interact with other skills based on their ontological description.
Version
Published version
Access right on openHSU
Metadata only access