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Reliably Segmenting Motion Reversals of a Rigid-IMU Cluster Using Screw-Based Invariants
KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. Department of Electronics, Mathematics and Natural Sciences, University of Gävle, Gävle, Sweden.ORCID iD: 0000-0002-5970-2985
KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.ORCID iD: 0000-0002-9171-8768
KTH, School of Engineering Sciences (SCI), Mechanics.ORCID iD: 0000-0001-5417-5939
Department of Electronics, Mathematics and Natural Sciences, University of Gävle, Gävle, Sweden.
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2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Human-robot interaction (HRI) is movingtowards the human-robot synchronization challenge. Inrobots like exoskeletons, this challenge translates to thereliable motion segmentation problem using wearabledevices. Therefore, our paper explores the possibility ofsegmenting the motion reversals of a rigid-IMU clusterusing screw-based invariants. Moreover, we evaluate thereliability of this framework with regard to the sensorplacement, speed and type of motion. Overall, our resultsshow that the screw-based invariants can reliably segmentthe motion reversals of a rigid-IMU cluster.

Place, publisher, year, edition, pages
2018.
National Category
Robotics
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-241104DOI: 10.1109/HUMANOIDS.2018.8624969ISI: 000458689700013Scopus ID: 2-s2.0-85062299962OAI: oai:DiVA.org:kth-241104DiVA, id: diva2:1277367
Conference
IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids) Beijing, China, November 6-9
Note

QC 20190111

Available from: 2019-01-10 Created: 2019-01-10 Last updated: 2019-04-11Bibliographically approved

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Rakesh, KrishnanCruciani, SilviaGutierrez-Farewik, ElenaSmith, Christian

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