Current control design for fast vision-based flight tends to rely on high-rate, high-dimensional and perfect state estimation. This is challenging in real-world environments due to imperfect sensing and state estimation drift and noise. In this letter, we present an alternative control design that bypasses the need for a state estimate by exploiting discrete-time flatness. To the best of our knowledge, this is the first work to demonstrate that discrete-time flatness holds for the Euler discretization of multirotor dynamics. This allows us to design a controller using only a window of input and output information. We highlight in simulation how exploiting this property in control design can provide robustness to noisy output measurements (where estimating higher-order derivatives and the full state can be challenging). Fast vision-based navigation requires high performance flight despite possibly noisy high-rate real-time position estimation. In outdoor experiments, we show the application of discrete-time flatness to vision-based flight at speeds up to 10 m/s and how it can outperform controllers that hinge on accurate state estimation.
翻译:快速视觉飞行的现有控制设计往往依赖于高率、高维和完美的状态估计。 在现实环境中,由于不完善的感测和状态估计漂移和噪音,这具有挑战性。 在本信里,我们提出了一个替代控制设计,通过利用离散时间平坦性,绕过国家估计的需要。 据我们所知,这是第一次证明离散时间平坦能维持多色动力的Euler离散状态。这使我们能够只使用输入和输出信息窗口来设计控制器。我们在模拟中强调,在控制设计中利用这种属性能为噪音的产出测量提供稳健性(在评估更高顺序衍生物和整个状态可能具有挑战性的情况下 ) 。 快速视觉导航需要高性运行飞行, 尽管可能高时速超速实时估计。 在户外实验中,我们展示了离散时间平坦性能在速度高达10米/秒的基于视觉的飞行上的应用,以及它如何超越取决于准确状态估计的超速控制器。