Partial aircraft state estimation from optical flow using non-model-based optimization

Computer vision is an enabling technology for autonomous micro aerial vehicle (MAV) applications. This paper presents an approach for the estimation of aircraft angular rates and wind-axis angles using monocular vision. The solution is obtained through nonlinear optimization techniques applied to the optical flow of tracked feature points in the image. The coupled equations of motion for an aircraft and image-based features are developed and utilized to establish a mathematical framework for the estimation process. The technique is then demonstrated in simulation.