arXiv:2601.03037cs.RO2026-01被引 2

让无人机和移动平台双向协作,实现快速精准降落。

A Bi-directional Adaptive Framework for Agile UAV Landing

  • 无人机与移动平台互相配合,不再单向跟踪。
  • 降落过程加速,可在动态环境下稳定完成。
  • 适合需要快速回收的无人机任务场景。

自主降落于移动平台对拓展四旋翼飞行器的作业灵活性至关重要,但传统方法在高度动态场景中效率低下。其核心瓶颈在于普遍采用的“追踪-下降”范式,将平台视为被动目标,迫使无人机执行复杂且顺序化的机动操作。本文挑战该范式,提出双向协同降落框架,将单一无人机追踪问题转化为耦合系统优化。关键创新在于:移动平台不仅是目标,更是主动参与者,通过主动倾斜表面为接近的无人机创造最优、稳定的终端姿态。这种主动协作从根本上打破顺序模型,实现对齐与下降阶段并行。同时,无人机规划流程专注于生成时间最优且动态可行的轨迹,以最小化能耗。双向协调使系统能以敏捷方式完成回收,表现为激进的轨迹跟踪和瞬态窗口内的快速状态同步。该框架在动态场景中的有效性已验证,显著提升了复杂且时间受限任务中四旋翼自主回收的效率、精度与鲁棒性。

原文摘要 · Abstract (English)

Autonomous landing on mobile platforms is crucial for extending quadcopter operational flexibility, yet conventional methods are often too inefficient for highly dynamic scenarios. The core limitation lies in the prevalent ``track-then-descend'' paradigm, which treats the platform as a passive target and forces the quadcopter to perform complex, sequential maneuvers. This paper challenges that paradigm by introducing a bi-directional cooperative landing framework that redefines the roles of the vehicle and the platform. The essential innovation is transforming the problem from a single-agent tracking challenge into a coupled system optimization. Our key insight is that the mobile platform is not merely a target, but an active agent in the landing process. It proactively tilts its surface to create an optimal, stable terminal attitude for the approaching quadcopter. This active cooperation fundamentally breaks the sequential model by parallelizing the alignment and descent phases. Concurrently, the quadcopter's planning pipeline focuses on generating a time-optimal and dynamically feasible trajectory that minimizes energy consumption. This bi-directional coordination allows the system to execute the recovery in an agile manner, characterized by aggressive trajectory tracking and rapid state synchronization within transient windows. The framework's effectiveness, validated in dynamic scenarios, significantly improves the efficiency, precision, and robustness of autonomous quadrotor recovery in complex and time-constrained missions.

无人机协同控制自主降落

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