具备接触感知的机载感知与混合控制的空中操作
Aerial Manipulation with Contact-Aware Onboard Perception and Hybrid Control
AI总结：
本文提出了一种无需外部运动捕捉的机载感知与混合控制方法，实现了接触丰富任务的精准运动跟踪和稳定接触力控制。
摘要：
空中操作（AM）有望将无人驾驶航空器（UAVs）从被动检查扩展到接触丰富的任务，如抓取、组装和现场维护。大多数先前的AM演示依赖于外部运动捕捉（MoCap）并强调位置控制用于粗略交互，限制了部署能力。我们提出了一个完全机载感知-控制管道，用于接触丰富的AM，实现了准确的运动跟踪和受控的接触力矩，而无需MoCap。主要组件是（1）一个增强型视觉-惯性里程计（VIO）估计器，具有接触一致性因子，仅在交互期间激活，收紧接触框架的不确定性并减少漂移，以及（2）基于图像的视觉伺服（IBVS）以缓解感知-控制耦合，再加上一个混合力-运动控制器，用于调节接触力矩和横向运动以实现稳定的接触。实验表明，我们的方法仅使用机载传感闭合感知到力矩的循环，实现了接触时速度估计的66.01%提升，可靠的目标准备，以及稳定的力保持，朝着可部署的、现实中的空中操作迈进。
英文摘要：
Aerial manipulation (AM) promises to move Unmanned Aerial Vehicles (UAVs) beyond passive inspection to contact-rich tasks such as grasping, assembly, and in-situ maintenance. Most prior AM demonstrations rely on external motion capture (MoCap) and emphasize position control for coarse interactions, limiting deployability. We present a fully onboard perception-control pipeline for contact-rich AM that achieves accurate motion tracking and regulated contact wrenches without MoCap. The main components are (1) an augmented visual-inertial odometry (VIO) estimator with contact-consistency factors that activate only during interaction, tightening uncertainty around the contact frame and reducing drift, and (2) image-based visual servoing (IBVS) to mitigate perception-control coupling, together with a hybrid force-motion controller that regulates contact wrenches and lateral motion for stable contact. Experiments show that our approach closes the perception-to-wrench loop using only onboard sensing, yielding an velocity estimation improvement of 66.01% at contact, reliable target approach, and stable force holding-pointing toward deployable, in-the-wild aerial manipulation.
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。
