This paper aims to address the open problem of designing a globally stable vision-based controller for robot manipulators. Accordingly, based on a hybrid mechanism, this paper proposes a novel task-space control law attained by taking the gradient of a potential function in SE(3). The key idea is to employ the Visual Simultaneous Localization and Mapping (VSLAM) algorithm to estimate a robot pose. The estimated robot pose is then used in the proposed hybrid controller as feedback information. Invoking Barbalats lemma and Lyapunov's stability theorem, it is guaranteed that the resulting closed-loop system is globally asymptotically stable, which is the main accomplishment of the proposed structure. Simulation studies are conducted on a six degrees of freedom (6-DOF) robot manipulator to demonstrate the effectiveness and validate the performance of the proposed VSLAM-based control scheme.

翻译：本文旨在解决设计全局稳定的基于视觉的机器人操作臂控制器这一开放性问题。为此，基于混合机制，本文提出了一种新颖的任务空间控制律，该控制律通过取SE(3)中势能函数的梯度而获得。核心思想是采用视觉同时定位与地图构建算法估计机器人位姿。随后将估计的机器人位姿作为反馈信息应用于所提出的混合控制器中。借助Barbalat引理和Lyapunov稳定性定理，可确保所得闭环系统全局渐近稳定，这是所提出结构的主要成果。通过在六自由度机器人操作臂上进行仿真研究，验证了所提出的基于VSLAM控制方案的有效性及性能表现。