The robotics community is increasingly interested in autonomous aerial transportation. Unmanned aerial vehicles with suspended payloads have advantages over other systems, including mechanical simplicity and agility, but pose great challenges in planning and control. To realize fully autonomous aerial transportation, this paper presents a systematic solution to address these difficulties. First, we present a real-time planning method that generates smooth trajectories considering the time-varying shape and non-linear dynamics of the system, ensuring whole-body safety and dynamic feasibility. Additionally, an adaptive NMPC with a hierarchical disturbance compensation strategy is designed to overcome unknown external perturbations and inaccurate model parameters. Extensive experiments show that our method is capable of generating high-quality trajectories online, even in highly constrained environments, and tracking aggressive flight trajectories accurately, even under significant uncertainty. We plan to release our code to benefit the community.

翻译：机器人学界对自主空中运输的兴趣日益增长。相较于其他系统，携带悬挂载荷的无人机具有机械结构简单和敏捷性优势，但其规划与控制面临重大挑战。为实现完全自主的空中运输，本文提出一种系统性解决方案。首先，提出一种实时规划方法，充分考虑系统时变形态与非线性动力学特性，生成保证全身安全与动态可行性的平滑轨迹。其次，设计自适应非线性模型预测控制（NMPC）与分层扰动补偿策略，以克服未知外界扰动和模型参数不准确问题。大量实验表明，该方法即使在高度受限环境中也能在线生成高质量轨迹，并在存在显著不确定性的情况下精确跟踪激进飞行轨迹。我们将开源代码以回馈学界。