Feed-forward parameter identification for precise periodic quadrocopter motions

This paper presents an approach for precisely tracking periodic trajectories with a quadrocopter. In order to improve temporal and spatial tracking performance, we propose a feed-forward strategy that adapts the motion parameters sent to the vehicle controller. The motion parameters are either adjusted on the fly or, in order to avoid initial transients, identified prior to the flight performance. We outline an identification scheme that tunes parameters for a large class of periodic motions, and requires only a small number of identification experiments prior to flight. This reduced identification is based on analysis and experiments showing that the quadrocopter's closed-loop dynamics can be approximated by three directionally decoupled linear systems. We show the effectiveness of this approach by performing a sequence of periodic motions on real quadrocopters using the tuned parameters obtained by the reduced identification.