Autonomous Micro Aerial Vehicles (MAVs) such as quadrotors equipped with manipulation mechanisms have the potential to assist humans in tasks such as construction and package delivery. Cables are a promising option for manipulation mechanisms due to their low weight, low cost, and simple design. However, designing control and planning strategies for cable mechanisms presents challenges due to indirect load actuation, nonlinear configuration space, and highly coupled system dynamics. In this paper, we propose a novel Nonlinear Model Predictive Control (NMPC) method that enables a team of quadrotors to manipulate a rigid-body payload in all 6 degrees of freedom via suspended cables. Our approach can concurrently exploit, as part of the receding horizon optimization, the available mechanical system redundancies to perform additional tasks such as inter-robot separation and obstacle avoidance while respecting payload dynamics and actuator constraints. To address real-time computational requirements and scalability, we employ a lightweight state vector parametrization that includes only payload states in all six degrees of freedom. This also enables the planning of trajectories on the $SE(3)$ manifold load configuration space, thereby also reducing planning complexity. We validate the proposed approach through simulation and real-world experiments.

翻译：自主微型飞行器（如配备操控机构的四旋翼）具有在建筑和包裹递送等任务中辅助人类的潜力。绳缆因重量轻、成本低、设计简单而成为操控机构的有前景选择。然而，由于载荷间接驱动、非线性构型空间以及高度耦合的系统动力学，为绳缆机构设计控制与规划策略面临挑战。本文提出一种新型非线性模型预测控制方法，使四旋翼编队能够通过悬吊绳缆在全部六个自由度上操控刚体载荷。作为滚动时域优化的一部分，我们的方法可同步利用机械系统冗余完成附加任务（如机器人间分离与避障），同时满足载荷动力学和作动器约束。为满足实时计算需求与可扩展性，我们采用仅包含六自由度载荷状态的轻量化状态向量参数化方案，这还能在SE(3)流形载荷构型空间上进行轨迹规划，从而降低规划复杂度。通过仿真与真实实验验证了所提方法的有效性。