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| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | Learning Perception-Aware Agile Flight in Cluttered Environments |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| ISBN | 979-8-3503-2365-8 |
| ISSN | 1050-4729 |
| Page Range | 1989 - 1995 |
| Event Title | 2023 IEEE International Conference on Robotics and Automation, ICRA 2023 |
| Event Type | conference |
| Event Location | London, United Kingdom of Great Britain and Northern Ireland |
| Event Start Date | May 29 - 2023 |
| Event End Date | June 2 - 2023 |
| Series Name | IEEE International Conference on Robotics and Automation. Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers |
| Abstract Text | Recently, neural control policies have outperformed existing model-based planning-and-control methods for autonomously navigating quadrotors through cluttered environments in minimum time. However, they are not perception aware, a crucial requirement in vision-based navigation due to the camera's limited field of view and the underactuated nature of a quadrotor. We propose a learning-based system that achieves perception-aware, agile flight in cluttered environments. Our method combines imitation learning with reinforcement learning (RL) by leveraging a privileged learning-by-cheating framework. Using RL, we first train a perception-aware teacher policy with full-state information to fly in minimum time through cluttered environments. Then, we use imitation learning to distill its knowledge into a vision-based student policy that only perceives the environment via a camera. Our approach tightly couples perception and control, showing a significant advantage in computation speed (10×faster) and success rate. We demonstrate the closed-loop control performance using hardware-in-the-loop simulation. |
| Digital Object Identifier | 10.1109/ICRA48891.2023.10160563 |
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