Learning Control for Biomimetic Undulating Fins: An Experimental Study

Learning control should focus on imitating natural fish’s adaptability to complex and dynamic environment to some extent, rather than mimicking streamlined shapes or specific actuators to develop more mechanical prototypes. In this paper, an experimental study on a proposed learning control of the robotic undulating fin, RoboGnilos, is suggested and explored. This study takes inspirations from biological world to practical control algorithms. In detail, an iterative learning scheme based control is studied with the cooperation of a filter to reduce the measurement noise, and a curve fitting component to keep the necessary phase difference between neighboring fin rays. Moreover, the iterative learning control algorithm is designed and implemented for practical applications. The experimental results validate that the proposed learning control can effectively improve the propulsion of RoboGnilos. For instance, the steady propulsion velocity may be enhanced by over 40% with some specified parameters.

[1]  Chunlin Zhou,et al.  Gait Planning for Steady Swimming Control of Biomimetic Fish Robots , 2009, Adv. Robotics.

[2]  Michael Sfakiotakis,et al.  Review of fish swimming modes for aquatic locomotion , 1999 .

[3]  Huosheng Hu,et al.  Biological inspiration: From carangiform fish to multi-joint robotic fish , 2010 .

[4]  Xiaobo Tan,et al.  Modeling of Biomimetic Robotic Fish Propelled by An Ionic Polymer–Metal Composite Caudal Fin , 2010, IEEE/ASME Transactions on Mechatronics.

[5]  K. H. Low,et al.  Modelling and parametric study of modular undulating fin rays for fish robots , 2009 .

[6]  Malcolm A. MacIver,et al.  A Biologically Inspired Robotic Ribbon Fin , 2005 .

[7]  Daibing Zhang,et al.  Computational hydrodynamics and statistical modeling on biologically inspired undulating robotic fins: A two-dimensional study , 2010 .

[8]  G. Lauder,et al.  Fish Exploiting Vortices Decrease Muscle Activity , 2003, Science.

[9]  Danwei W. Wang.  On D-type and P-type ILC designs and anticipatory approach , 2000 .

[10]  Yoseph Bar-Cohen,et al.  Biomimetics—using nature to inspire human innovation , 2006, Bioinspiration & biomimetics.

[11]  Richard W. Longman,et al.  Disturbance rejection in repetitive controllers , 1992 .

[12]  Tianjiang Hu,et al.  Effective motion control of the biomimetic undulating fin via iterative learning , 2009, 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[13]  Yang Jie.  Research on Biomimetic Fish Fin Driven by NiTi Shape Memory Alloy , 2007 .

[14]  P. Webb.  Form and Function in Fish Swimming , 1984 .

[15]  H. K. Low.  Design, Development and locomotion Control of Bio-Fish robot with undulating Anal fins , 2007, Int. J. Robotics Autom..

[16]  M. A. MacIver,et al.  The hydrodynamics of ribbon-fin propulsion during impulsive motion , 2008, Journal of Experimental Biology.

[17]  Tianjiang Hu,et al.  Biological inspirations, kinematics modeling, mechanism design and experiments on an undulating robotic fin inspired by Gymnarchus niloticus , 2009 .

[18]  Kin Huat Low,et al.  Bionic asymmetry: from amiiform fish to undulating robotic fins , 2009 .

[19]  Barry W. Williams,et al.  Improved Control of DFIG Systems During Network Unbalance Using PI–R Current Regulators , 2009, IEEE Transactions on Industrial Electronics.

[20]  Promode R. Bandyopadhyay.  Guest Editorial: Biology-Inspired Science and Technology for Autonomous Underwater Vehicles , 2004 .

[21]  J. Liao,et al.  A review of fish swimming mechanics and behaviour in altered flows , 2007, Philosophical Transactions of the Royal Society B: Biological Sciences.

[22]  David M. Lane,et al.  An experimental undulating-fin device using the parallel bellows actuator , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[23]  Suguru Arimoto,et al.  Bettering operation of Robots by learning , 1984, J. Field Robotics.

[24]  Long Wang,et al.  Vision-Based Target Tracking and Collision Avoidance for Two Autonomous Robotic Fish , 2009, IEEE Transactions on Industrial Electronics.