This paper proposes a novel algorithm for aerobatic trajectory generation for a vertical take-off and landing (VTOL) tailsitter flying wing aircraft. The algorithm differs from existing approaches for fixed-wing trajectory generation, as it considers a realistic six-degree-of-freedom (6DOF) flight dynamics model, including aerodynamics equations. Using a global dynamics model enables the generation of aerobatics trajectories that exploit the entire flight envelope, enabling agile maneuvering through the stall regime, sideways uncoordinated flight, inverted flight etc. The method uses the differential flatness property of the global tailsitter flying wing dynamics, which is derived in this work. By performing snap minimization in the differentially flat output space, a computationally efficient algorithm, suitable for online motion planning, is obtained. The algorithm is demonstrated in extensive flight experiments encompassing six aerobatics maneuvers, a time-optimal drone racing trajectory, and an airshow-like aerobatic sequence for three tailsitter aircraft.
翻译:本文为垂直起飞和着陆的尾翼飞行翼飞机的有氧轨迹生成提出了一种新颖的算法。算法与固定翼轨道生成的现有方法不同,因为它考虑到现实的六度自由飞行动态模型(6DOF),包括空气动力等方程式。使用全球动态模型,可以产生利用整个飞行包体的有氧航空轨迹,能够通过拖拉机、侧道不协调的飞行、倒转飞行等灵活机动。该方法使用了从这项工作中得出的全球尾翼飞行翼动态的差异平性特性。通过在有差异的平板输出空间快速最小化,获得了一种适合在线运动规划的计算高效算法。该算法体现在广泛的飞行实验中,其中包括六次有氧飞行操纵、一个时间-最佳无人驾驶赛轨,以及三架尾尾翼飞行机的空气蒸汽序列。