Augmentation for unmanned aerial vehicle position estimation using MARG and optical flow sensors

Abstract

The optical flow sensor can detect the movement of the unmanned aerial vehicle (UAV) on the ground; thus, it is widely used for UAV flight control. The commonly used pinhole model of optical flow sensor describes the optical flow measurement in linear and angular velocities. It is not suitable in the case of discrete-time processing. A novel measurement model for the optical flow sensor is proposed, which directly gives the relationship between the optical flow and the UAV’s translational/angular motions in each sampling period. A data fusion scheme based on cubature transform is also presented, which can augment UAV’s position estimation using optical flow data. The proposed method is proven to be effective through flight tests on UAVs.