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Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten. Towards improving the absolute accuracy of lightweight robots by nonparametric calibration
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Postprint urn:nbn:de:0011-n-5072882 (2.1 MByte PDF) MD5 Fingerprint: 181cc11e02281cdb97681a4a3c211768 © IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Erstellt am: 16.11.2018 |
| Institute of Electrical and Electronics Engineers -IEEE-: ETFA 2017, 22nd IEEE International Conference on Emerging Technologies and Factory Automation : 12-15 September 2017, Limassol, Cyprus Piscataway, NJ: IEEE, 2017 ISBN: 978-1-5090-6505-9 ISBN: 978-1-5090-6504-2 ISBN: 978-1-5090-6506-6 S.1314-1317 |
| International Conference on Emerging Technologies and Factory Automation (ETFA) <22, 2017, Limassol/Cyprus> |
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| Englisch |
| Konferenzbeitrag, Elektronische Publikation |
| Fraunhofer IFF () |
Abstract
In this work, preparations for the nonparametric calibration of a 7 DOF light-weight robot using machine learning techniques are presented. The approach was developed to satisfy the requirements on absolute accuracy for robot-assisted surgery. With the kinematic and non-kinematic properties in mind, we showed that a decomposition of the robot's kinematic chain can drastically reduce the number of necessary samples for a sophisticated training set. Thus, the data acquisition can be accomplished in a feasible time frame. Furthermore, we cope with the problem of data registration between the robot's internal model and the external measurements. We can show that by carefully choosing the split point for the decomposition, errors caused by the dependency between sub-chains of the robot are small enough to yield satisfying results.