Learning Perception-Aware Agile Flight in Cluttered Environments

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00366389" target="_blank" >RIV/68407700:21230/23:00366389 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/ICRA48891.2023.10160563" target="_blank" >https://doi.org/10.1109/ICRA48891.2023.10160563</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICRA48891.2023.10160563" target="_blank" >10.1109/ICRA48891.2023.10160563</a>

Result language
angličtina
Original language name
Learning Perception-Aware Agile Flight in Cluttered Environments
Original language description
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 ($10times$ faster) and success rate. We demonstrate the closed-loop control performance using hardware-in-the-loop simulation.
Czech name
—
Czech description
—

Project
<a href="/en/project/GM23-06162M" target="_blank" >GM23-06162M: TOPFLIGHT: Trajectory and Mission Planning for Agile Flight of Aerial Robots in Cluttered Environments</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2023 IEEE International Conference on Robotics and Automation
ISBN
979-8-3503-2365-8
ISSN
1050-4729
e-ISSN
2577-087X
Number of pages
7
Pages from-to
1989-1995
Publisher name
IEEE
Place of publication
Piscataway
Event location
Londýn
Event date
May 29, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001036713001114

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