Visual Servoing to Catch Fish Using Global/Local GA Search

Abstract

This paper presents a vision-related technique for a real-time visual servoing. The method utilizes the global search feature of a genetic algorithm (GA) and a local search technique of the GA. In the GA process, the computation of the fitness function is based on the configuration of an object model designated as the surface-strips model. To evaluate the effectiveness of the proposed recognition method, experiments to track a fish by a hand-eye camera and catch the fish with a net attached to the hand of the manipulator have been performed.