The generation and characterization of control signals for decision-making in
industrial robotic applications require essential data from the environment,
gathered through various sensors. Atop these sensors, a camera is employed
to collect information and data from the surroundings. Visual feedback proves
to be an effective and robust technique for closed-loop robotic applications.
This paper proposes a multivariable interaction model, akin to process
control, for the visual-servo system. Variable interaction is inherent in these
Multiple Input Multiple Output (MIMO) system models, which is apt for
explaining the intrinsic flaws of Image-Based Visual Servoing (IBVS). Singular
Value Analysis (SVA) and Relative Gain Array (RGA) serve as pragmatic tools
for the evaluation and analysis of the system. The objective of this paper is to
utilize RGA for the numerical analysis of the visual servo control structure.
Keywords: Visual servoing, MIMO, Condition Number, RGA, SVA