Quadrotors can carry slung loads to hard-to-reach locations at high speed. Since a single quadrotor has limited payload capacities, using a team of quadrotors to collaboratively manipulate a heavy object is a scalable and promising solution. However, existing control algorithms for multi-lifting systems only enable low-speed and low-acceleration operations due to the complex dynamic coupling between quadrotors and the load, limiting their use in time-critical missions such as search and rescue. In this work, we present a solution to significantly enhance the agility of cable-suspended multi-lifting systems. Unlike traditional cascaded solutions, we introduce a trajectory-based framework that solves the whole-body kinodynamic motion planning problem online, accounting for the dynamic coupling effects and constraints between the quadrotors and the load. The planned trajectory is provided to the quadrotors as a reference in a receding-horizon fashion and is tracked by an onboard controller that observes and compensates for the cable tension. Real-world experiments demonstrate that our framework can achieve at least eight times greater acceleration than state-of-the-art methods to follow agile trajectories. Our method can even perform complex maneuvers such as flying through narrow passages at high speed. Additionally, it exhibits high robustness against load uncertainties and does not require adding any sensors to the load, demonstrating strong practicality.

翻译：四旋翼无人机能够以高速将悬挂负载运送至难以抵达的区域。由于单架四旋翼的负载能力有限，采用多机协同操控重型物体是一种可扩展且前景广阔的解决方案。然而，现有多机吊运系统的控制算法因四旋翼与负载间复杂的动态耦合效应，仅能实现低速、低加速度操作，限制了其在搜救等时间敏感任务中的应用。本研究提出一种显著提升缆绳悬挂多机吊运系统敏捷性的解决方案。与传统级联式方案不同，我们引入一种基于轨迹的框架，在线求解整体系统的运动动力学规划问题，充分计及四旋翼与负载间的动态耦合效应及约束条件。规划生成的轨迹以滚动时域方式作为参考指令下发给各四旋翼，并由机载控制器通过实时观测与补偿缆绳张力进行跟踪。真实环境实验表明，本框架在跟踪敏捷轨迹时能实现至少八倍于现有先进方法的加速度。该方法甚至能执行高速穿越狭窄通道等复杂机动动作。此外，系统对负载不确定性表现出强鲁棒性，且无需在负载端加装任何传感器，展现出极强的实用价值。