A real-time fuzzy reasoning based control system for catching a moving goldfish

Abstract

Designing a real-time visual tracking system to catch a goldfish is a complex task because of the large amount of streaming video data that must be transmitted and processed immediately when tracking the goldfish. Usually, building such visual servoing systems requires the application of high-cost specialized hardware and the development of complicated visual control software. In this paper, a novel low-cost, real-time visual servo control system is presented. The system uses stereo vision consisting of two calibrated cameras to acquire images of the goldfish, and applies the continuously adaptive mean shift (CAMSHIFT) vision-tracking algorithm to provide feedback of a fish’s real-time position at a high frame rate. It then employs a 5-axis robot manipulator controlled by a fuzzy reasoning system to catch the fish. This visual tracking and servoing system is less sensitive to lighting influences and thus performs more efficiently. Experiments with the proposed method yielded very good results, as the system’s real-time 3D vision successfully tracked two fish and guided the manipulator, which has a net attached to its end effector, to catch one of them.