Teaching distributed and heterogeneous robotic cells
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen
Beitragende
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
Originalsprache | Englisch |
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Titel | 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC) |
Seiten | 1-2 |
ISBN (elektronisch) | 978-1-6654-3161-3 |
Publikationsstatus | Veröffentlicht - 11 Jan. 2022 |
Peer-Review-Status | Nein |
Publikationsreihe
Reihe | IEEE Consumer Communications and Networking Conference |
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ISSN | 2331-9852 |
Externe IDs
Scopus | 85135730678 |
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ORCID | /0000-0001-7008-1537/work/142248642 |
ORCID | /0000-0002-3513-6448/work/168720184 |
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- distributed applications, model-based software engineering, robotics, virtual reality