让无人机在复杂地形上自动停靠四足机器人，实现稳定对接。
Autonomous UAV-Quadruped Docking in Complex Terrains via Active Posture Alignment and Constraint-Aware Control
- 四足机器人用深度强化学习主动调平身体，提供稳定平台。
- 无人机分三阶段对接：远距离探测、近距离约束控制、最后安全降落。
- 能在超过17厘米台阶和30度陡坡上成功对接，适合野外救援场景。
无人机与地面机器人之间的自主对接对异构系统至关重要，但现有方法多针对移动能力受限的轮式平台。四足机器人虽适应性强，但姿态频繁变化，难以为无人机提供稳定着陆面。为此，本文提出一种适用于无GPS环境的无人机-四足机器人自主对接框架。四足侧采用基于深度强化学习训练的混合内部模型水平对齐（HIM-HA），主动稳定躯干以提供水平平台；无人机侧采用三阶段策略：远距离通过中值滤波YOLOv8检测获取目标，近距离使用融合非奇异快速终端滑模控制（NFTSMC）与对数屏障函数（BF）的约束感知控制器，在视场（FOV）限制下保证有限时间误差收敛，末端下降阶段则由安全周期（SP）机制协同验证跟踪精度与平台稳定性。该框架在仿真与真实场景中均得到验证，成功实现对高于17 cm的室外台阶及陡度超过30°的粗糙斜坡的对接。补充材料与视频见：https://uav-quadruped-docking.github.io。
原文摘要 · Abstract (English)
Autonomous docking between Unmanned Aerial Vehicles (UAVs) and ground robots is essential for heterogeneous systems, yet most existing approaches target wheeled platforms whose limited mobility constrains exploration in complex terrains. Quadruped robots offer superior adaptability but undergo frequent posture variations, making it difficult to provide a stable landing surface for UAVs. To address these challenges, we propose an autonomous UAV-quadruped docking framework for GPS-denied environments. On the quadruped side, a Hybrid Internal Model with Horizontal Alignment (HIM-HA), learned via deep reinforcement learning, actively stabilizes the torso to provide a level platform. On the UAV side, a three-phase strategy is adopted, consisting of long-range acquisition with a median-filtered YOLOv8 detector, close-range tracking with a constraint-aware controller that integrates a Nonsingular Fast Terminal Sliding Mode Controller (NFTSMC) and a logarithmic Barrier Function (BF) to guarantee finite-time error convergence under field-of-view (FOV) constraints, and terminal descent guided by a Safety Period (SP) mechanism that jointly verifies tracking accuracy and platform stability. The proposed framework is validated in both simulation and real-world scenarios, successfully achieving docking on outdoor staircases higher than 17 cm and rough slopes steeper than 30 degrees. Supplementary materials and videos are available at: https://uav-quadruped-docking.github.io.
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