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:装有操纵装置的自动微型航空飞行器(MAV),如装有操纵装置的磁带装置等,有可能协助人类完成建筑和包装交付等任务。电缆由于其重量低、成本低和设计简单,是操纵机制的一个很有希望的选择。然而,电缆装置的控制和规划战略由于间接负载激活、非线性配置空间和高度结合的系统动态而构成挑战。在本文件中,我们提出了一个新的非线性模型预测控制(NMPC)方法,使一个四重船轮能够通过悬浮电缆在所有6度自由度上操纵硬体有效载荷。我们的方法可以同时利用现有的机械系统冗余来完成其他任务,例如机器人之间的分离和障碍避免,同时尊重有效载荷动力和动作限制。我们采用了一种轻量的状态矢量预测控制(NMPC)方法,该方法仅包括所有6度自由度国家。我们的方法还使得能够规划USE(3)元的多元载荷配置空间的轨迹,从而通过模拟来降低复杂性。</s>