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High accurate robotic drilling with external sensor and compliance model-based compensation

: Diaz Posada, Julian Ricardo; Schneider, Ulrich; Pidan, Sergej; Geravand, Milad; Stelzer, Patrick; Verl, Alexander

Postprint urn:nbn:de:0011-n-3995959 (2.5 MByte PDF)
MD5 Fingerprint: 00db134bee6251fc71a8f442b4225644
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Erstellt am: 29.6.2016

Institute of Electrical and Electronics Engineers -IEEE-; IEEE Robotics and Automation Society:
IEEE International Conference on Robotics and Automation, ICRA 2016 : Stockholm, Sweden, May 16th - 21st, 2016
Piscataway, NJ: IEEE, 2016
ISBN: 978-1-4673-8025-6
ISBN: 978-1-4673-8026-3
International Conference on Robotics and Automation (ICRA) <2016, Stockholm>
European Commission EC
FP7-ICT; 287787; SMErobotics
European Commission EC
H2020-EU.2.1.1.; 688217; ROBOTT-NET
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IPA ()
Industrieroboter; Fertigung; Supply Chain; Instandhaltung; maintenance Organisation; calibration; Kalibrieren; Bohren (Spanen); compliance; tolerance compensation; Kompensation

High accurate absolute robot positioning is a requirement, and still a challenge, in many applications, such as drilling in the aerospace industry. The accuracy is affected due to many sources of errors from robot model, tool calibration, sensor and product uncertainties. While model-based error compensation cannot reach the desired accuracy, sensor-based compensation appears as the practical solution to increase the robot positioning accuracy. A structured analysis of the error sources in robotic manufacturing processes can facilitate error identification and further compensation. This paper describes an error source breaking down approach for analyzing robotic manufacturing processes. Moreover, an external sensor-based compensation is proposed for error reduction and error identification. Comparison with a compliance model-based compensation is performed. The proposed approach is applied to a robotic drilling process for aircraft manufacturing, considered a general and real industrial application. Further validation through experimentation is performed. The validation revealed a clear improvement in robot positioning accuracy and the benefits of the proposed error source structure for analysis.