Image-Based Visual Servoing of Unmanned Aerial Manipulators for Tracking and Grasping a Moving Target

In this article, an image-based visual servoing (IBVS) control strategy is proposed for the unmanned aerial manipulator (UAM) system to track and grasp a moving target. Specifically, a robust-adaptive velocity observer is designed to estimate the relative velocity between the tracked target and the UAM platform. Based on the velocity observer, an IBVS controller using onboard camera of the UAM platform is proposed for moving target tracking without velocity measurement. Then, the barrier Lyapunov function is introduced into the UAM platform IBVS controller to ensure the safety of target tracking. Besides, another virtual camera is constructed on manipulator end-effector to compensate for the tracking error of the UAM platform. As a benefit, the eye-to-hand onboard camera ensures the global view of the UAM, and the eye-in-hand virtual camera of the manipulator ensures the accuracy of the grasping task. Finally, the stability of the proposed IBVS control strategy is analyzed through Lyapunov theory. The comparative simulations are provided to illustrate the target tracking performance of the proposed method. The experimental results demonstrate that the proposed method can be applied to the UAM with a low-cost sensor suite to realize the tasks of tracking and grasping a moving target.

Automated summary

This article proposes an image-based visual servoing (IBVS) control strategy for an unmanned aerial manipulator (UAM) system to track and grasp a moving target. A robust-adaptive velocity observer is designed to estimate the relative velocity between the tracked target and the UAM platform, and an IBVS controller using the onboard camera is proposed for moving target tracking. The stability of the proposed IBVS control strategy is analyzed using Lyapunov theory, and comparative simulations are provided to demonstrate the target tracking performance.