Nonlinear Attitude Estimation in SO(3): Application to a Quadrotor UAV

The objective of this work is to study and compare nonlinear attitude estimation methods to be used for a quadrotor state estimation and control. We begin by introducing the QuavIST quadrotor Unamnned Aerial Vehile (UAV) platform, alongside with the mathematical equations that govern the aircraft motion in flight. The nonlinear equations of motion are linearized about an operating point, and finally the computational model is presented. We then focus on the problem of attitude estimation, and start by reviewing the current state of the art. Three nonlinear estimators from current literature are selected and presented: one Extended Kalman filter and two formulated in the Special Orthogonal Group SO(3) . A fourth, self-developed method in SO(3) is formulated using Lyapunov theory and considerations are made about the impact of gyroscope bias and of using Global Positioning System (GPS) measurements to assist attitude estimation. We then introduce a selected position estimator, to be used as complementary information to the attitude filters. The performance of the presented attitude and position estimators is evaluated in a series of simulation scenarios emulating real life quadrotor applications.