Backflipping with Miniature Quadcopters by Gaussian Process Based Control and Planning

The paper proposes two control methods for performing a backflip maneuver with miniature quadcopters. First, an existing feedforward control strategy designed specifically for backflipping is revised and improved. Bayesian optimization with surrogate Gaussian Process model is applied to find the optimal sequence of motion primitives by performing the flip maneuver repeatedly in a simulation environment. The second method is based on closed-loop control and it consists of two main steps: first a novel robust, adaptive controller is designed to provide reliable reference tracking even in the case of model uncertainties. The controller is constructed by augmenting the nominal model of the drone with a Gaussian Process that is tuned by measurement data. Second, an efficient trajectory planning algorithm is proposed, which designs feasible trajectories for the backflip maneuver by using only quadratic programming. The two approaches are analyzed in simulations and in real experiments using Bitcraze Crazyflie 2.1 quadcopters.