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Type Journal Article
Scope Discipline-based scholarship
Title Autonomous Quadrotor Flight Despite Rotor Failure With Onboard Vision Sensors: Frames vs. Events
Organization Unit
Authors
  • Sihao Sun
  • Giovanni Cioffi
  • Coen de Visser
  • Davide Scaramuzza
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Journal Title IEEE Robotics and Automation Letters
Publisher Institute of Electrical and Electronics Engineers
Geographical Reach international
ISSN 2377-3766
Volume 6
Number 2
Page Range 580 - 587
Date 2022
Abstract Text Fault-tolerant control is crucial for safety-critical systems, such as quadrotors. State-of-art flight controllers can stabilize and control a quadrotor even when subjected to the complete loss of a rotor. However, these methods rely on external sensors, such as GPS or motion capture systems, for state estimation. To the best of our knowledge, this has not yet been achieved with only onboard sensors. In this letter, we propose the first algorithm that combines fault-tolerant control and onboard vision-based state estimation to achieve position control of a quadrotor subjected to complete failure of one rotor. Experimental validations show that our approach is able to accurately control the position of a quadrotor during a motor failure scenario, without the aid of any external sensors. The primary challenge to vision-based state estimation stems from the inevitable high-speed yaw rotation (over 20 rd/s) of the damaged quadrotor, causing motion blur to cameras, which is detrimental to visual inertial odometry (VIO). We compare two types of visual inputs to the vision-based state estimation algorithm: standard frames and events. Experimental results show the advantage of using an event camera especially in low light environments due to its inherent high dynamic range and high temporal resolution. We believe that our approach will render autonomous quadrotors safer in both GPS denied or degraded environments. We release both our controller and VIO algorithm open source.
Digital Object Identifier 10.1109/LRA.2020.3048875
Other Identification Number merlin-id:22154
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