3D Visual Servoing by Feedforward Evolutionary Recognition

Abstract

This paper deals with position-based 6-DoF visual servoing. With a common sense of feedback control, we stress that improvement of the dynamics of the sensing unit is important for a stable visual servoing. We propose a method to improve dynamics in visual recognition, with compensating the fictional motion of the target in the camera images based on kinematics of the manipulator, by extracting the real motion of the target. We named it as hand-eye motion feedforword (MFF) method. The enhanced dynamics of recognition gave further stability and precision to the total visual servoing system, evaluated by full 6-DoF servoing experiment using 7-link manipulator. The convergence time in step response was about 10[s] and precise visual servoing to a moving target object has been achieved.

Keywords

• evolutionary recognition
• visual servoing
• hand-eye motion feedforword