Robust Nonlinear Fusion of Inertial and Visual Data for position, velocity and attitude estimation of UAV

Abstract

This paper presents a coupled observer that uses accelerometer, gyrometer and vision sensors to provide estimates of pose and linear velocity for an aerial robotic vehicle. The observer is based on a non-linear complimentary filter framework and incorporates adaptive estimates of measurement bias in gyrometers and accelerometers commonly encountered in low-cost inertial measurement systems. Asymptotic stability of the observer estimates is proved as well as bounded energy of the observer error signals. Experimental data is provided for the proposed filter run on data obtained from an experiment involving a remotely controlled helicopter.