Prescribed performance image based visual servoing under field of view constraints

In this paper, we propose a novel image based visual servoing scheme that imposes prescribed transient and steady state response on the image feature coordinate errors and satisfies the visibility constraints that inherently arise owing to the limited field of view (FOV) of cameras. Visualizing the aforementioned performance specifications as error bounds, the key idea is to provide an error transformation that converts the original constrained problem into an equivalent unconstrained one, the stabilization of which proves sufficient to achieve prescribed performance guarantees and satisfy the inherent visibility constraints. The performance of the developed scheme is a priori and explicitly imposed by certain designer-specified performance functions, and is fully decoupled by the control gains selection, thus simplifying the control design. Moreover, its computational complexity proves significantly low. It is actually a static scheme involving very few and simple calculations to output the control signal, which enables easily its implementation on fast embedded control platforms. Finally, real-time experiments using an eye-in-hand robotic system verify the theoretical findings.