无人机靠物理接触感知斜屋顶角度，无需视觉依赖。
Omnidirectional Dual-Arm Aerial Manipulator with Proprioceptive Contact Localization for Landing on Slanted Roofs
- 用双臂机械臂结合自感应扭矩观测实现接触定位。
- 在30.5度斜面上稳定着陆，平均误差仅2.87度。
- 适合城市复杂屋顶环境，对光照天气不敏感。
在城市环境中操作无人机常需在屋顶着陆，而屋顶具有不同几何形状和表面不规则性。传统基于视觉或声学的倾斜度检测方法易受天气和材质影响，可靠性差。为此，本文提出一种新型无人飞行机械臂结构，具备全向3D工作空间与延伸臂展。在此基础上，开发基于动量扭矩观测器的本体感知接触检测与定位策略，使无人机可在触地前通过物理接触盲测斜面倾角。飞行实验验证了该方法的有效性，在不同倾角下完成9次测试，最大可适应30.5度斜面，平均倾角估计误差为2.87度。
原文摘要 · Abstract (English)
Operating drones in urban environments often means they need to land on rooftops, which can have different geometries and surface irregularities. Accurately detecting roof inclination using conventional sensing methods, such as vision-based or acoustic techniques, can be unreliable, as measurement quality is strongly influenced by external factors including weather conditions and surface materials. To overcome these challenges, we propose a novel unmanned aerial manipulator morphology featuring a dual-arm aerial manipulator with an omnidirectional 3D workspace and extended reach. Building on this design, we develop a proprioceptive contact detection and contact localization strategy based on a momentum-based torque observer. This enables the UAM to infer the inclination of slanted surfaces blindly - through physical interaction - prior to touchdown. We validate the approach in flight experiments, demonstrating robust landings on surfaces with inclinations of up to 30.5 degrees and achieving an average surface inclination estimation error of 2.87 degrees over 9 experiments at different incline angles.
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