In this paper, an image-based impedance control strategy for force tracking of an unmanned aerial manipulator (UAM) is presented. Firstly, image features with nice decoupling characteristics are designed and the relationship between the camera motion and the image features is derived. Then, a two-stage strategy is proposed to achieve force tracking of the UAM on a planar object in an arbitrary pose. The first stage drives the end-effector perpendicular to the object’s planer surface by pure visual servoing. To achieve force tracking under the visual guidance, an adaptive visual impedance control method which adjusts the target stiffness according to the force tracking error and the visual feature error is proposed in the second stage. The closed-loop system is proved asymptotically stable by means of Lyapunov analysis. Further, the stability in free flight phase of the stage two is also analyzed and ensured. Finally, experiments were carried out including a whiteboard cleaning task in different poses. The experimental results illustrate the validity and effectiveness of the proposed approach. Note to Practitioners—This work is motivated by the contact force tracking problem of an unmanned aerial manipulator (UAM) without the position measurement. In recent years, impedance control is widely used in force tracking problems. However, position measurement is needed both for the robot and the object in most studies. To generate desired force under visual guidance, image-based visual servoing is combined with a novel impedance controller with variable stiffness. The idea is intuitive. For a human in contact with a wall, the contact force is controlled by adjusting his arm stiffness, which means the stiffness is adapted to the difference between the desired and actual contact force. Furthermore, the stiffness is also adapted to the visual tracking error, removing the assumption that no tracking error is in the inner loop of the impedance controller in the previous works. The proposed strategy is a promising solution for real applications and is validated by a board cleaning experiment in this paper.

中文翻译：

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基于图像的接触式空中操纵视觉阻抗力控制


本文提出了一种基于图像的阻抗控制策略，用于无人机力跟踪（UAM）。首先，设计具有良好解耦特性的图像特征，并推导相机运动与图像特征之间的关系。然后，提出了一种两阶段策略来实现 UAM 在任意姿态的平面物体上的力跟踪。第一级通过纯视觉伺服驱动垂直于物体平面的末端执行器。为了实现视觉引导下的力跟踪，第二阶段提出了一种根据力跟踪误差和视觉特征误差调整目标刚度的自适应视觉阻抗控制方法。通过Lyapunov分析证明了闭环系统渐近稳定。此外，还对第二级自由飞行阶段的稳定性进行了分析和保证。最后，进行了包括不同姿势的白板清洁任务在内的实验。实验结果说明了该方法的有效性和有效性。从业人员注意事项——这项工作的动机是无人机操纵器（UAM）的接触力跟踪问题，没有位置测量。近年来，阻抗控制广泛应用于力跟踪问题。然而，在大多数研究中，机器人和物体都需要位置测量。为了在视觉引导下产生所需的力，基于图像的视觉伺服与具有可变刚度的新型阻抗控制器相结合。这个想法很直观。 对于与墙壁接触的人，通过调整其手臂刚度来控制接触力，这意味着刚度适应于期望接触力和实际接触力之间的差异。此外，刚度还适应视觉跟踪误差，消除了先前工作中阻抗控制器的内环中没有跟踪误差的假设。所提出的策略对于实际应用来说是一个有前景的解决方案，并通过本文中的电路板清洁实验进行了验证。