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Safe Navigation of Networked Robots Under Localization Uncertainty Using Robust Control Barrier Functions
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson Research, Sweden.ORCID iD: 0000-0002-3922-5288
Ericsson Research, Sweden.
Ericsson Research, Sweden.
Ericsson Research, Sweden.
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2023 (English)In: 2023 62nd IEEE Conference on Decision and Control, CDC 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023, p. 6064-6071Conference paper, Published paper (Refereed)
Abstract [en]

5G networks have the potential to provide external sensor data and offload computations for future industrial mobile robots. To enable these benefits while maintaining safety, we propose a modular architecture, including an onboard safety filter for the velocity control loop. The safety filter leverages robust control barrier functions to guarantee safety from collisions under bounded localization uncertainty. Initial experiments are performed to quantify the localization uncertainty and generate suitable bounds for the safety filter. We then derive the safety filter, and analyze its conservatism numerically. Finally, the method is demonstrated in experiments using an ABB Mobile YuMi® Research Platform robot.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2023. p. 6064-6071
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-343720DOI: 10.1109/CDC49753.2023.10383973Scopus ID: 2-s2.0-85184831809OAI: oai:DiVA.org:kth-343720DiVA, id: diva2:1839915
Conference
62nd IEEE Conference on Decision and Control, CDC 2023, Dec 13 2023 - Dec 15 2023, Singapore
Note

Part of ISBN: 979-8-3503-0124-3

QC 20240228

Available from: 2024-02-22 Created: 2024-02-22 Last updated: 2024-04-08Bibliographically approved

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Miksits, AdamJohansson, Karl H.

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  • fi-FI
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  • nn-NB
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Output format
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  • asciidoc
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