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Maximising quadrotor drone autonomy using state estimation and calibration


C. Frei

Master Thesis, SS16 (10526)

In this work we present a study of how the autonomy of a miniature quadrotor drone can be extended using state estimation and sensor calibration. We introduce two state estimators, one that is purely based on kinematics and one that takes aerodynamics and quadrotor system dynamics into account. In addition, we investigate the influence of sensor calibration as well as noise on gyroscope and accelerometer readings on the quality of the state estimation. This reveals the dominant disturbances that are required to be eliminated in order to prolong the time for which the drones can fly autonomously.

Supervisors: Paul Beuchat, Yvonne Stürz, Henrik Hesse, John Lygeros, Roy Smith


Type of Publication:

(12)Diploma/Master Thesis

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2016:IFA_5507
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