Intuitive Instruction of Robot Systems: Semantic Integration of Standardized Skill Interfaces

This work aims at facilitating the integration of industrial robots and other devices such as their gripper tools at small and medium-sized enterprises (SMEs). For this purpose, an intuitive user interface for the skill-based instruction of robot systems is combined with standardized opc UA-based sk...

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Bibliographic Details
Published in:IEEE International Conference on Industrial Informatics (INDIN) pp. 1 - 8
Main Authors: Ding, Junsheng, Kessler, Ingmar, Perzylo, Alexander, Knauer, Markus, Domel, Andreas, Willibald, Christoph, Riedell, Sebastian, Profanterl, Stefan, Brunner, Sebastian, Dunaev, Arsenii, Li, Le, Brucker, Manuel
Format: Conference Proceeding
Language:English
Published: IEEE 18.08.2024
Subjects:
Automation
Graphical user interfaces
Hardware
Intuitive Robot Programming
Packaging
Production systems
Robots
Semantic Process Models
Semantics
Service robots
Software
Standardization
Standardized Skill Interfaces
ISSN:2378-363X
Online Access:Get full text
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Summary:This work aims at facilitating the integration of industrial robots and other devices such as their gripper tools at small and medium-sized enterprises (SMEs). For this purpose, an intuitive user interface for the skill-based instruction of robot systems is combined with standardized opc UA-based skill interfaces that support various hardware and software resources from different manufacturers. Special emphasis is laid on supporting different user groups with varying levels of expertise. Production system engineers are provided with a detailed graphical user interface (GUI) for hierarchically defining new skills by combining preexisting ones. System operators receive a simplified view with limited complexity for process instruction and changing high-level task parameterizations. The skills and relevant semantic context knowledge about products, processes, and resources (PPR) are formally represented in OWL ontologies to enable hardware-agnostic process descriptions that can be deployed to different production environments, while automatically deriving parameterizations for skill invocations. The proposed concept has been qualitatively evaluated in two real-world robot workcells based on a smartphone accessory packaging use case.
ISSN:2378-363X
DOI:10.1109/INDIN58382.2024.10774421