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Theses

Accuracy enhancement for robotic assembly of large-scale parts in the aerospace industry

Abstract : This thesis concerns the development of different methods and strategies to improve the accuracy of robotic assembly in the aerospace industry, in particular the assembly of a Main Landing Gear Door of the Airbus A350 XWB. The research addresses three main issues: the improvement of the industrial robot's absolute accuracy, the precise identification of the position of large-scale objects, and the robotic surface-surface contact between two large-scale parts. Concerning the industrial robot's absolute accuracy, we proved the efficiency of the sensor-based correction methods through the development of a 6DoF real-time control of a KUKA robot's pose. This controller was also implemented in a hybrid position/effort control. A new calibration strategy for a 3D measurement system mounted on a robotic arm has contributed significantly to improving the accurate identification of the position of large objects. Thus, it was determined that the robot needs to adopt a single joint configuration during the calibration procedure while guaranteeing the system's constant measurement accuracy throughout its entire working volume. Finally, a new admittance control strategy is presented to guarantee the contact of multiple surfaces on large-scale parts. This controller can be adapted to any position-controller robot and avoids any overshoot of its force/torque setpoint. A full-scale prototype of the assembly cell has been developed in collaboration with KUKA Systems Aerospace France and DAHER. It integrates all the strategies proposed in this work and demonstrates that it can be applied in the industrial environment.
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Submitted on : Friday, September 25, 2020 - 12:14:18 PM
Last modification on : Saturday, September 26, 2020 - 3:07:06 AM

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  • HAL Id : tel-02949048, version 1

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Sebastian Rendon Fernandez. Accuracy enhancement for robotic assembly of large-scale parts in the aerospace industry. Other [cs.OH]. HESAM Université, 2020. English. ⟨NNT : 2020HESAE018⟩. ⟨tel-02949048⟩

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