This paper presents a vision-aided uniformly semi-globally exponentially stable (USGES) nonlinear observer for estimation of attitude, gyro bias, position, velocity and specific force of a fixed-wing Unmanned Aerial Vehicle (UAV). The nonlinear observer uses measurements from an Inertial Measurement Unit (IMU), a Global Navigation Satellite System (GNSS) receiver, and a video camera. This paper presents a nonlinear observer representation with a computer vision (CV) system without any assumptions related to the distance to objects in the images and the structure of the terrain being recorded. The CV utilizes a camera and the continuous epipolar constraint to calculate body-fixed linear velocity. The observer is named a Continuous Epipolar Optical Flow (CEOF) nonlinear observer. Experimental data from a UAV test flight and simulated data are presented showing that the CEOF nonlinear observer has robust performance. Experimental results are compared with an Extended Kalman Filter (EKF) and illustrate that the estimates of the states converge to the correct values. Results show that using the proposed CV in addition to IMU and GNSS improves the accuracy of the estimates. The CV provides accurate information about the direction of travel of the UAV, which improves the attitude and gyro bias estimate.
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