Teaching distributed and heterogeneous robotic cells
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed
Contributors
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
Original language | English |
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Title of host publication | 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC) |
Pages | 1-2 |
ISBN (electronic) | 978-1-6654-3161-3 |
Publication status | Published - 11 Jan 2022 |
Peer-reviewed | No |
Publication series
Series | IEEE Consumer Communications and Networking Conference |
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ISSN | 2331-9852 |
External IDs
Scopus | 85135730678 |
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ORCID | /0000-0001-7008-1537/work/142248642 |
ORCID | /0000-0002-3513-6448/work/168720184 |
Keywords
ASJC Scopus subject areas
Keywords
- distributed applications, model-based software engineering, robotics, virtual reality