无人机投送系统通过机械臂主动补偿误差，提升精准度与稳定性。
AeroThrow: An Autonomous Aerial Throwing System for Precise Payload Delivery
- 用飞行机械臂增加自由度，主动补偿跟踪误差。
- 抛物线落点约束使释放时机不敏感，提升投送精度。
- 结合非线性模型预测控制，抗扰动能力强，适合复杂环境投送。
自主空中系统在复杂环境下的运输与投送任务中作用日益重要。空投任务中，这些平台面临控制模式突变、系统延迟及控制误差的双重挑战。本文提出一种基于空中机械臂（AM）的自主空投系统。引入额外的主动自由度，实现对无人机跟踪误差的主动补偿。通过施加平滑连续的抛物线落点约束，所提方法生成对释放时机不敏感的空中投掷轨迹。在非线性模型预测控制（NMPC）框架中融入分层扰动补偿策略，以缓解系统参数突变的影响，同时利用NMPC的预测能力进一步提升空中投掷精度。仿真与真实实验结果均表明，该系统在空投任务中实现了更高的敏捷性与精确性。
原文摘要 · Abstract (English)
Autonomous aerial systems play an increasingly vital role in a wide range of applications, particularly for transport and delivery tasks in complex environments. In airdrop missions, these platforms face the dual challenges of abrupt control mode switching and inherent system delays along with control errors. To address these issues, this paper presents an autonomous airdrop system based on an aerial manipulator (AM). The introduction of additional actuated degrees of freedom enables active compensation for UAV tracking errors. By imposing smooth and continuous constraints on the parabolic landing point, the proposed approach generates aerial throwing trajectories that are less sensitive to the timing of payload release. A hierarchical disturbance compensation strategy is incorporated into the Nonlinear Model Predictive Control (NMPC) framework to mitigate the effects of sudden changes in system parameters, while the predictive capabilities of NMPC are further exploited to improve the precision of aerial throwing. Both simulation and real-world experimental results demonstrate that the proposed system achieves greater agility and precision in airdrop missions.
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