ICUAS 2020 Paper Abstract


Paper ThA3.3

Gu, Weibin (University of Denver), Hu, Dewen (Shanghai FOIA Co.), Cheng, Liang (Shanghai FOIA Co.), Cao, Yabing (Shanghai FOIA Co.), Rizzo, Alessandro (Politecnico di Torino), Valavanis, Kimon P. (University of Denver)

Autonomous Wind Turbine Inspection Using a Quadrotor

Scheduled for presentation during the Regular Session "UAS Applications I" (ThA3), Thursday, September 3, 2020, 10:40−11:00, Edessa

2020 International Conference on Unmanned Aircraft Systems (ICUAS), September 1-4, 2020 (Postponed from June 9-12, 2020), Athens, Greece

This information is tentative and subject to change. Compiled on September 25, 2020

Keywords UAS Applications, Autonomy, Technology Challenges


There has been explosive growth of wind farm installations in recent years due to the fact that wind energy is gaining worldwide popularity. However, the maintenance of these offshore or onshore wind turbines, especially in remote areas, remains a challenging task. In this work, vision-based autonomous wind turbine inspection using a quadrotor is designed based on realistic assumptions. Both simulation and Hardware-In-the-Loop (HIL) testing results have shown the effectiveness of the proposed approach.



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