Tilt-rotor aerial robots are more dynamic and versatile than fixed-rotor platforms, since the thrust vector and body orientation are decoupled. However, the coordination of servos and propellers (the allocation problem) is not trivial, especially accounting for overactuation and actuator dynamics. We incrementally build and present three novel allocation methods for tilt-rotor aerial robots, comparing them to state-of-the-art methods on a real system performing dynamic maneuvers. We extend the state-of-the-art geometric allocation into a differential allocation, which uses the platform's redundancy and does not suffer from singularities. We expand it by incorporating actuator dynamics and propeller power dynamics. These allow us to model dynamic propeller acceleration limits, bringing two main advantages: balancing propeller speed without the need for nullspace goals and allowing the platform to selectively turn off propellers during flight, opening the door to new manipulation possibilities. We also use actuator dynamics and limits to normalize the allocation problem, making it easier to tune and allowing it to track 70% faster trajectories than a geometric allocation.

翻译：倾斜旋翼空中机器人比固定旋翼平台更具动态性和多功能性，因为其推力矢量与机体姿态解耦。然而，舵机与螺旋桨的协调（即分配问题）并非易事，尤其是在考虑过驱动和执行器动力学的情况下。我们逐步构建并提出了三种适用于倾斜旋翼空中机器人的新型分配方法，并在执行动态机动的真实系统上将其与最先进方法进行了比较。我们将最先进的几何分配方法扩展为微分分配法，该方法利用平台的冗余性且不受奇异性影响。我们通过融合执行器动力学和螺旋桨功率动力学进一步拓展了该方法。这使得我们能够对动态螺旋桨加速度限制进行建模，从而带来两大主要优势：无需零空间目标即可平衡螺旋桨转速，并允许平台在飞行中选择性关闭螺旋桨，为新型操控可能性开辟了道路。我们还利用执行器动力学和限制条件对分配问题进行归一化处理，使其更易于调参，并能跟踪比几何分配快70%的轨迹。