ICARL Seminar Series - 2024 Spring

Champion-Level Drone Racing using Deep Reinforcement Learning
Seminar by Leonard Bauersfeld

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Abstract:

First-person view (FPV) drone racing is a televised sport in which professional competitors pilot high-speed quadcopters through a 3D circuit. The pilots see the environment from the perspective of their drone by means of an onboard camera video-stream. In this talk I will explain Swift, an autonomous system that can race quadcopters at the level of the human world champions. The system combines deep reinforcement learning (RL) in simulation with data collected in the physical world. Our Swift drone competed against three human champions, including the world champions of two international leagues, in real-world head-to-head races and won several races against each of the human champions. The autonomous drone demonstrated the fastest recorded race time.

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About the Speaker:

Leonard Bauersfeld did his Masters at ETH Zurich in "Robotics, Systems, and Control" where he graduated with distinction in 2021. Currently he is a PhD Student in Robotics at the University of Zurich working in the "Robotics and Perception Group" under the lead of roboticist Davide Scaramuzza. He works on drone modeling, agile vision-based flight and novel machine learning approaches to push the frontiers of autonomous UAV navigation. He was part of the team that impressively beat the world champions of drone racing in a fair head-to-head race with an autonomous drone. Besides working on drones, he is a photographer and enjoys taking pictures of nature as well as far-away astronomical objects, such as nebulas and galaxies.

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Links
Leonard Bauersfeld
Site: lbfd.github.io
Twitter: x.com/l_bauersfeld

ICARL
Site: icarl.doc.ic.ac.uk
Twitter: x.com/ic_arl
YouTube: @ICARLSeminars
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