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Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title Deep Drone Racing: Learning Agile Flight in Dynamic Environments
Organization Unit
Authors
  • Elia Kaufmann
  • Antonio Loquercio
  • Rene Ranftl
  • Alexey Dosovitskiy
  • Vladlen Koltun
  • Davide Scaramuzza
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Event Title Conference on Robotic Learning (CoRL), Zurich, 2018
Event Type conference
Event Location Zurich
Event Start Date October 1 - 2018
Event End Date October 5 - 2018
Place of Publication Conference on Robotic Learning (CoRL), Zurich, 2018.
Publisher CoRL
Abstract Text Autonomous agile flight brings up fundamental challenges in robotics, such as coping with unreliable state estimation, reacting optimally to dynamically changing environments, and coupling perception and action in real time under severe resource constraints. In this paper, we consider these challenges in the context of autonomous, vision-based drone racing in dynamic environments. Our approach combines a convolutional neural network (CNN) with a state-of-the-art path-planning and control system. The CNN directly maps raw images into a robust representation in the form of a waypoint and desired speed. This information is then used by the planner to generate a short, minimum-jerk trajectory segment and corresponding motor commands to reach the desired goal. We demonstrate our method in autonomous agile flight scenarios, in which a vision-based quadrotor traverses drone-racing tracks with possibly moving gates. Our method does not require any explicit map of the environment and runs fully onboard. We extensively test the precision and robustness of the approach in simulation and in the physical world. We also evaluate our method against state-of-the-art navigation approaches and professional human drone pilots.
Free access at Official URL
Official URL http://rpg.ifi.uzh.ch/docs/CORL18_Kaufmann.pdf
Other Identification Number merlin-id:18693
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