  This paper presents a novel method for fast and robust detection of actuator
failures on quadrotors. The proposed algorithm has very little model
dependency. A Kalman filter estimator estimates a stochastic effectiveness
factor for every actuator, using only onboard RPM, gyro and accelerometer
measurements. Then, a hypothesis test identifies the failed actuator. This
algorithm is validated online in real-time, also as part of an active fault
tolerant control system. Loss of actuator effectiveness is induced by ejecting
the propellers from the motors. The robustness of this algorithm is further
investigated offline over a range of parameter settings by replaying real
flight data containing 26 propeller ejections. The detection delays are found
to be in the 30 to 130 ms range, without missed detections or false alarms
occurring.
