Evolving Fuzzy Modeling of an Uncalibrated Visual Servoing System

Abstract

In this paper, inverse fuzzy models obtained online for uncalibrated visual servoing, are developed and validated in a six degrees of freedom robotic manipulator. This approach will recursively update the inverse fuzzy model based only on measurements at a given time instant. The uncalibrated approach does not require calibrated kinematic and camera models, as needed in classical visual servoing to obtain the Jacobian. Experimental results obtained in a PUMA robot performing eye-to-hand visual servoing are used to demonstrate the validity of the proposed approach, when compared to the previous developed off-line learning.KeywordsFuzzy SystemCluster CenterInverse ModelRobotic ManipulatorVisual ServoingThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.