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Fault-tolerant control is crucial for safety-critical systems, such asquadrotors. State-of-art flight controllers can stabilize and control aquadrotor even when subjected to the complete loss of a rotor. However, thesemethods rely on external sensors, such as GPS or motion capture systems, forstate estimation. To the best of our knowledge, this has not yet been achievedwith only onboard sensors. In this paper, we propose the first algorithm thatcombines fault-tolerant control and onboard vision-based state estimation toachieve position control of a quadrotor subjected to complete failure of onerotor. Experimental validations show that our approach is able to accuratelycontrol the position of a quadrotor during a motor failure scenario, withoutthe aid of any external sensors. The primary challenge to vision-based stateestimation stems from the inevitable high-speed yaw rotation (over 20 rad/s) ofthe damaged quadrotor, causing motion blur to cameras, which is detrimental tovisual inertial odometry (VIO). We compare two types of visual inputs to thevision-based state estimation algorithm: standard frames and events.Experimental results show the advantage of using an event camera especially inlow light environments due to its inherent high dynamic range and high temporalresolution. We believe that our approach will render autonomous quadrotorssafer in both GPS denied or degraded environments. We release both ourcontroller and VIO algorithm open source.

Autonomous Quadrotor Flight Despite Rotor Failure With Onboard Vision Sensors: Frames vs. Events