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AI-based Safety Analysis for Collaborative Mobile Robots
Ericsson Research.
Ericsson Research.
Ericsson Research.
KTH.
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2019 (English)In: Proceedings of the 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2019, p. 1722-1729Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents implementation details of AI methods used for safety in human robot collaborative scenarios, based on fuzzy logic and state-of-the-art deep learning-based perception. For semantic representation of the environment, a scene graph encodes the environment surrounding the robots with information from camera, which is then fed to risk management system for safety analysis purpose. Transfer learning effects have been observed when starting training based on weights pre-trained on Image Net and COCO data-sets. A fuzzy logic solution for risk analysis, evaluation and mitigation has been compared to a neuro-fuzzy approach. Experiments have been performed in a physically realistic 3D simulation of a warehouse environment to evaluate which configuration presents the best performance for robotic perception and risk mitigation.

Place, publisher, year, edition, pages
2019. p. 1722-1729
National Category
Robotics
Identifiers
URN: urn:nbn:se:kth:diva-268242DOI: 10.1109/ETFA.2019.8869263Scopus ID: 2-s2.0-85074215284OAI: oai:DiVA.org:kth-268242DiVA, id: diva2:1426499
Conference
2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)10-13 Sept. 2019
Note

QC 20200427

Available from: 2020-04-27 Created: 2020-04-27 Last updated: 2020-04-27Bibliographically approved

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