The paper proposes two control methods for performing a backflip maneuver with miniature quadcopters. First, an existing feedforward control approach is improved by finding the optimal sequence of motion primitives via Bayesian optimization, using a surrogate Gaussian Process model. To evaluate the cost function, the flip maneuver is performed 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 case of model uncertainties. The controller is constructed by augmenting the nominal model of the drone with a Gaussian Process that is trained by using measurement data. Second, an efficient trajectory planning algorithm is proposed, which designs feasible trajectories for the flip maneuver by using only quadratic programming. The two approaches are analyzed in simulations and in real experiments using Bitcraze Crazyflie 2.1 quadcopters.
翻译:本文建议了两种使用微型四分位仪进行回翻转操作的控制方法。 首先,通过使用代位高斯进程模型,通过贝叶西亚优化找到运动原始体的最佳序列,改进了现有的饲料向前控制方法。 为了评估成本功能,在模拟环境中反复进行翻转操作。第二种方法基于闭路控制,由两个主要步骤组成:首先,一个新型的强大适应性控制器的设计是为了提供可靠的参考跟踪,即使模型的不确定性也如此。控制器的构建方式是通过使用测量数据培训的高斯进程扩大无人机的名义模型。第二,提出了高效的轨迹规划算法,该算法仅使用四分位仪程序为翻转动设计可行的轨迹。在模拟中和在实际实验中使用Bitcraze Marseflie 2.1 Quadcopters进行两种方法的分析。</s>