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There is an immense disconnect between the flight performance of autonomous systems and human pilots. Human pilots are capable of guiding remote-controlled drones at impressive speeds through a track in a sport called drone racing. Why is there such a dwelling gap between human and machine performance? Clearly, industrial applications would greatly benefit from agile and fast flight capabilities in terms of profitability and robustness, and companies aspire to achieve ever-increasing efficiency and productivity. The Ph.D. thesis of Philipp Foehn investigates how novel optimization-based planning and control strategies can be applied to enable autonomous quadrotors to exploit their full performance envelope and allow for agile and robust autonomous flight. Among others, his thesis provides contributions allowing quadrotors to fly at their actuation limit, culminating in a framework that even beats expert human racing pilots in a time trial drone race. Reference: Philipp Foehn Agile Aerial Autonomy: Planning and Control Thesis: https://rpg.ifi.uzh.ch/docs/PHDTHESIS... Google Scholar: https://scholar.google.com/citations?... Our research page on high-speed flight: http://rpg.ifi.uzh.ch/research_mav.html Our research page on drone racing: http://rpg.ifi.uzh.ch/research_drone_... Affiliation: Philipp Foehn is with the Robotics and Perception Group, Dept. of Informatics, University of Zurich, and Dept. of Neuroinformatics, University of Zurich and ETH Zurich, Switzerland http://rpg.ifi.uzh.ch