Robust Visual Control of Parallel Robots under Uncertain Camera Orientation

Abstract

This work presents a stability analysis and experimental assessment of a visual control algorithm applied to a redundant planar parallel robot under uncertainty in relation to camera orientation. The key feature of the analysis is a strict Lyapunov function that allows the conclusion of asymptotic stability without invoking the Barbashin-Krassovsky-LaSalle invariance theorem. The controller does not rely on velocity measurements and has a structure similar to a classic Proportional Derivative control algorithm. Experiments in a laboratory prototype show that uncertainty in camera orientation does not significantly degrade closed-loop performance.