Position Estimation of Small Robotic Fish Based on Camera Information and Gyro Sensors

Abstract

Robotic fish are ideal for surveying fish resources and performing underwater structural inspections. If a robot is sufficiently fishlike in appearance and does not use a screw propeller, real fish will not be easily surprised by it. However, it is comparatively difficult for such a robot to determine its own position in water. Radio signals, such as those used by GPS, cannot be easily received. Moreover, sound ranging is impractical because of the presence of rocks and waterweed in places where fish spend a lot of time. For practical applications such as photographing fish, a robotic fish needs to follow the target fish without losing awareness of its own position, in order to be able to swim autonomously. We have developed a robotic fish named FOCUS (FPGA Offline Control Underwater Searcher) which is equipped with two CMOS cameras and a field-programmable gate array (FPGA) circuit board for data processing. The forward-facing camera is used to track red objects, since this is the color of the fish of interest. In addition, using visual information obtained with the bottom-facing camera, the robot can estimate its present position. This is achieved by performing real-time digital image correlation using the FPGA. However, until now, the position estimation accuracy has been poor due to the influence of yaw and roll. In the present study, the position estimation method has been greatly improved by taking into account the yaw and roll values measured using gyro sensors.