全方位双臂空中机械臂配备本体感觉接触定位用于斜屋顶着陆
Omnidirectional Dual-Arm Aerial Manipulator with Proprioceptive Contact Localization for Landing on Slanted Roofs
AI总结：
本文提出了一种具备本体感觉接触定位的双臂空中机械臂，通过物理交互实现斜屋顶着陆的精准倾斜度检测，实验验证了其在高倾斜角度下的稳健性能。
摘要：
在城市环境中操作无人机往往意味着需要在屋顶着陆，这些屋顶可能有不同的几何形状和表面不规则性。使用传统传感方法（如基于视觉或声学的技术）准确检测屋顶倾斜度可能不可靠，因为测量质量强烈受外部因素影响，包括天气条件和表面材料。为克服这些挑战，我们提出了一种新型无人驾驶空中机械臂形态，其特征是具有全方位3D工作空间和延长范围的双臂空中机械臂。基于此设计，我们开发了一种基于动量基扭矩观测器的本体感觉接触检测和接触定位策略。这使UAM能够通过物理交互在着陆前盲推测斜面的倾斜度。我们在飞行实验中验证了该方法，证明了在倾斜角度高达30.5度的表面上实现稳健着陆，并在9次不同倾斜角度实验中实现了平均表面倾斜度估计误差为2.87度。
英文摘要：
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.
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。
