Visual evaluation and fuzzy voice commands for controlling a robot manipulator

Abstract

This paper proposes a method for learning and controlling an industrial robot manipulator through Fuzzy Voice Commands (FVCs) guided by visual motor coordination. Supervised Self-Organising Map (SSOM) is proposed to implement the visual motor coordination. The FVCs are used to control the robot manipulator toward a goal. Visual evaluation process is adapted by the supervision of the human coach. The learned system is capable of navigating the robot manipulator to a point in 3D working space as instructed by the voice commands. The proposed idea is demonstrated with a PA-10 industrial manipulator.