  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.
