A Kalman filter based force-feedback control system for hydrodynamic investigation of unsteady aquatic propulsion

Recent advances in understanding fish locomotion with robotic devices have included the use of different robotic prototypes that swim at a controlled but constant swimming speeds. However, the speed of even steadily swimming live fishes is not constant because the fish commonly accelerate and decelerate throughout tail beat cycles. In this paper, we implement a bass body-shaped robot, programmed to display the carangiform fish locomotion. The robotic fish was then mounted on a servo towing system and initially at rest, can determine its self-propelled speed by measuring the external force acting upon it. A Kalman filter was used for filtering the measured external force. By using this method, we tested the speed profiles of both a customized ROV and the robotic fish model. The results show that this experimental method can well predict the speed profiles of both the traditional propeller-based and the undulatory robotic swimmers. In particular, we show that the linear acceleration phase can be reproduced by this experimental method. Finally, we discuss this force-feedback-controlled method and the relative self-propelled hydrodynamic results of the robot.