AeroThrow：一种用于精确载荷投送的自主空中抛投系统
AeroThrow: An Autonomous Aerial Throwing System for Precise Payload Delivery
AI总结：
本文提出AeroThrow自主空中抛投系统，通过空中机械臂引入额外自由度并结合分层扰动补偿的NMPC框架，主动补偿跟踪误差、降低释放时刻敏感度，实现空投任务中更高的灵活性与精确性。
摘要：
自主空中系统在广泛的应用中发挥着日益重要的作用，尤其是在复杂环境中的运输与投送任务中。在空投任务中，这些平台面临控制模式突然切换以及固有系统延迟和控制误差的双重挑战。为解决这些问题，本文提出了一种基于空中机械臂（AM）的自主空投系统。引入额外的驱动自由度使得能够主动补偿无人机（UAV）的跟踪误差。通过对抛物线落点施加平滑且连续的约束，所提出的方法生成的空中抛投轨迹对载荷释放时刻的敏感度更低。在非线性模型预测控制（NMPC）框架中引入了一种分层扰动补偿策略，以减轻系统参数突然变化的影响，同时进一步利用NMPC的预测能力来提高空中抛投的精度。仿真和真实世界实验结果均表明，所提出的系统在空投任务中实现了更高的灵活性和精确性。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
