Public defence in Robotics and Autonomous Systems, M.Sc.(Tech.) Jouko Kinnari

The title of the thesis: Infrastructureless unmanned aerial vehicle localization

Thesis defender: Jouko Kinnari
Opponent: Prof. Juha Röning, University of Oulu, Finland
Custos: Prof. Ville Kyrki, Aalto University School of Electrical Engineering, Department of Electrical Engineering and Automation

Localization, the capability to approximate one's position with respect to an operating environment, is essential for autonomous robots, enabling navigation and place-specific actions and observations. The thesis addresses robust localization for flying autonomous robots, or Unmanned Aerial Vehicles (UAVs). UAVs commonly use Global Navigation Satellite Systems (GNSS) like GPS and Galileo for localization. GNSS are vulnerable to signal path propagation errors and interference from malicious actors. The reliance on GNSS limits safe commercial autonomous UAV operations, prompting the need for infrastructure-independent localization methods. 

The thesis proposes a localization approach using a visual camera, an inertial measurement unit (IMU), and a magnetometer compass. The approach uses georeferenced orthophotos or satellite images as reference maps. The thesis addresses three major issues related to the localization problem: allowing variation of camera orientation with respect to the ground, building tolerance towards appearance variation due to time of year, and enabling localization with no knowledge of starting location. In addition, the thesis evaluates performance of the resulting algorithm in a real-time, real-world experiment. In summary, this thesis presents innovative solutions to enhance the robustness and practicality of infrastructure-independent UAV localization, paving the way for safer and more reliable autonomous operations.

Keywords: Localization, autonomy, unmanned aerial vehicle

Thesis available for public display 10 days prior to the defence at: https://aaltodoc.aalto.fi/doc_public/eonly/riiputus/

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Doctoral theses in the School of Electrical Engineering: https://aaltodoc.aalto.fi/handle/123456789/53