A quadrotor with a cable-suspended payload imposes great challenges in impact-aware planning and control. This joint system has dual motion modes, depending on whether the cable is slack or not, and presents complicated dynamics. Therefore, generating feasible agile flight while preserving the retractable nature of the cable is still a challenging task. In this article, we propose a novel impact-aware planning and control framework that resolves potential impacts caused by motion mode switching. Our method leverages the augmented Lagrangian method to solve an optimization problem with nonlinear complementarity constraints, which ensures trajectory feasibility with high accuracy while maintaining efficiency. We further propose a hybrid nonlinear model predictive control method to address the model mismatch issue in agile flight. Our methods have been comprehensively validated in both simulation and experiments, demonstrating superior performance compared to existing approaches. To the best of our knowledge, we are the first to successfully perform automatic multiple motion mode switching for aerial payload systems in real-world experiments.

中文翻译：

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具有悬挂有效载荷的空中机器人的影响感知规划和控制

具有缆绳悬挂有效负载的四旋翼飞行器给影响感知规划和控制带来了巨大挑战。该关节系统具有两种运动模式，具体取决于电缆是否松弛，并呈现复杂的动力学。因此，在保持电缆可伸缩性质的同时产生可行的敏捷飞行仍然是一项具有挑战性的任务。在本文中，我们提出了一种新颖的影响感知规划和控制框架，可以解决运动模式切换造成的潜在影响。我们的方法利用增强拉格朗日方法来解决具有非线性互补约束的优化问题，这在保持效率的同时确保了高精度的轨迹可行性。我们进一步提出了一种混合非线性模型预测控制方法来解决敏捷飞行中的模型失配问题。我们的方法已经在模拟和实验中得到了全面验证，与现有方法相比，证明了其优越的性能。据我们所知，我们是第一个在实际实验中成功实现空中有效载荷系统自动多运动模式切换的公司。