基于图像的视觉伺服控制用于全驱动无人机的空中作业
Image-based Visual Servo Control for Aerial Manipulation Using a Fully-Actuated UAV
AI总结：
本文提出一种基于图像的视觉伺服控制策略，用于全驱动无人机桥梁维护，无需外部位姿估计或预定义标记，实现运动与力控制。
摘要：
使用无人机（UAV）执行高空作业任务，而不仅仅是被动视觉应用，可以减少人员的时间、成本和风险。以往关于空中作业的研究依赖于地面真值状态估计或GPS/全站仪结合一些同步定位与建图（SLAM）算法，这对于许多靠近GPS信号退化或无特征环境的基础设施应用可能不实用。视觉伺服可以避免估计机器人位姿的需求。现有的关于空中作业视觉伺服的研究要么仅涉及末端执行器位置控制，要么依赖精确的速度测量和已知模式的预定义视觉标记。此外，大多数先前的工作使用欠驱动无人机，导致末端执行器的机械和控制系统设计复杂化。本文开发了一种基于图像的视觉伺服控制策略，用于全驱动无人机的桥梁维护。主要组成部分包括（1）视觉线条检测与跟踪系统，（2）混合阻抗力与运动控制系统。我们的方法不依赖外部定位系统的机器人位姿/速度估计，也不依赖预定义视觉标记。由于全驱动的特性，机械系统和控制器架构的复杂性也降至最低。实验表明，该系统能够仅依靠视觉引导有效地执行桥梁涂装的运动跟踪和力保持。据我们所知，这是首批利用视觉伺服实现运动和力控制而无需外部位姿/速度信息或预定义视觉引导的空中作业研究之一。
英文摘要：
Using Unmanned Aerial Vehicles (UAVs) to perform high-altitude manipulation tasks beyond just passive visual application can reduce the time, cost, and risk of human workers. Prior research on aerial manipulation has relied on either ground truth state estimate or GPS/total station with some Simultaneous Localization and Mapping (SLAM) algorithms, which may not be practical for many applications close to infrastructure with degraded GPS signal or featureless environments. Visual servo can avoid the need to estimate robot pose. Existing works on visual servo for aerial manipulation either address solely end-effector position control or rely on precise velocity measurement and pre-defined visual visual marker with known pattern. Furthermore, most of previous work used under-actuated UAVs, resulting in complicated mechanical and hence control design for the end-effector. This paper develops an image-based visual servo control strategy for bridge maintenance using a fully-actuated UAV. The main components are (1) a visual line detection and tracking system, (2) a hybrid impedance force and motion control system. Our approach does not rely on either robot pose/velocity estimation from an external localization system or pre-defined visual markers. The complexity of the mechanical system and controller architecture is also minimized due to the fully-actuated nature. Experiments show that the system can effectively execute motion tracking and force holding using only the visual guidance for the bridge painting. To the best of our knowledge, this is one of the first studies on aerial manipulation using visual servo that is capable of achieving both motion and force control without the need of external pose/velocity information or pre-defined visual guidance.
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。
