Computational geometric identification for quadrotor dynamics in wind fields

This paper presents a computational framework to identify the effects of wind on the dynamics of a quadrotor unmanned aerial vehicle. Then, using the identified model, the strength and the direction of the wind are estimated with the inertial measurements. The proposed approach is based on a geometric numerical integrator on the special Euclidean group, referred to as a Lie group variational integrator such that singularities or complexities associated with the local coordinates or quaternions are completely avoided. We illustrate through numerical examples that the presented methods successfully identify the effects of the wind even for the challenging case of large initial estimation errors.