Automated Robot Skill Parameterization Based On Task Specifications

Sebastian Kurscheid, Ruediger Daub

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

High-mix, low-volume manufacturing still relies on manual labor despite the potential for automation. This is due to the high cost of robot programming, which is required on a frequent basis. Skill-based frameworks for robot programming have reduced the expertise level and effort required for automation to meet the demands of high-mix, low-volume manufacturing. In these frameworks, the capabilities of robots are encapsulated in skills. By parameterizing these robot skills, they are adapted to new variants or products. This paper presents a concept for automating the parameterization process based on task specifications to reduce worker efforts by combining natural language processing and knowledge models.

Original languageEnglish
Title of host publication2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation, ETFA 2024
EditorsTullio Facchinetti, Angelo Cenedese, Lucia Lo Bello, Stefano Vitturi, Thilo Sauter, Federico Tramarin
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350361230
DOIs
StatePublished - 2024
Event29th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2024 - Padova, Italy
Duration: 10 Sep 202413 Sep 2024

Publication series

NameIEEE International Conference on Emerging Technologies and Factory Automation, ETFA
ISSN (Print)1946-0740
ISSN (Electronic)1946-0759

Conference

Conference29th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2024
Country/TerritoryItaly
CityPadova
Period10/09/2413/09/24

Keywords

  • industrial robots
  • information extraction
  • knowledge modeling
  • manufacturing
  • skill parameterization
  • skill-based programming

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