Teaching distributed and heterogeneous robotic cells

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragen

Abstract

Teaching heterogeneous robotic cells is difficult and time-consuming. We present a context-aware robot teaching solution based on an open-source framework that decouples the task instruction from the task execution to simplify the teaching workflow significantly. To demonstrate the advantages of the solution, a human operator uses a VR headset and controllers to teach a virtual robot to perform a task, e.g., pick-and-place in a virtual world. The task is automatically adapted to different settings of operation cells and executed by physical robots located at different geographical locations.

Details

OriginalspracheEnglisch
Titel2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC)
Seiten1-2
ISBN (elektronisch)978-1-6654-3161-3
PublikationsstatusVeröffentlicht - 11 Jan. 2022
Peer-Review-StatusNein

Publikationsreihe

ReiheIEEE Consumer Communications and Networking Conference
ISSN2331-9852

Externe IDs

Scopus 85135730678
ORCID /0000-0001-7008-1537/work/142248642
ORCID /0000-0002-3513-6448/work/168720184

Schlagworte

Schlagwörter

  • distributed applications, model-based software engineering, robotics, virtual reality