Yaw Rate Bias Fault Detection and Vision-Based Recovery System for Quadrotor

Abstract

This work presents fault detection and recovery system when the bias fault occurs in the yaw rate part of the gyro (z-gyro) during the quadrotor flight. Kalman filter based on the dynamic model of the quadrotor and chi-square test is used to detect the fault. The auxiliary yaw rate was calculated through the homography matrix between the image frames obtained by the camera which is filming the ground plane. This was used as a redundant z-gyro sensor and switched with the faulty sensor to perform the recovery process. Additionally, in constant bias fault scenario, camera is used to correct biased sensor data. Through this, it was possible to follow the path stably even if there was a bias during flights. The system was implemented with the ROS environment and simulated in Gazebo.