Distributed flow sensing using Bayesian estimation for a flexible fish robot

Flexibility plays an important role in fish behaviors by enabling high maneuverability for predator avoidance and swimming in turbulence. In this paper, we present a novel, flexible fish robot equipped with distributed pressure sensors for flow sensing. The body of the robot is made of a soft, hyperelastic material that provides flexibility. The fish robot features a Joukowski-foil shape conducive to modeling the fluid analytically. A quasisteady potential-flow model is adopted for real-time flow estimation, whereas a discrete-time vortex-shedding flow model is used for higher-fidelity simulation. The dynamics for the flexible fish robot are presented, and a reduced model for one-dimensional swimming is derived. A recursive Bayesian filter assimilates pressure measurements for estimating the flow speed, angle of attack, and foil camber. Simulation and experimental results are presented to show the effectiveness of the flow estimation algorithm.Copyright © 2015 by ASME

[1]  Xiaobo Tan,et al.  Autonomous robotic fish as mobile sensor platforms: Challenges and potential solutions , 2011 .

[2]  P.R. Bandyopadhyay,et al.  Trends in biorobotic autonomous undersea vehicles , 2005, IEEE Journal of Oceanic Engineering.

[3]  Sheryl Coombs,et al.  The Hydrodynamics and Structural Mechanics of the Lateral Line System , 2006 .

[4]  Neil J. Gordon,et al.  A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..

[5]  Naomi Ehrich Leonard,et al.  Dynamics of the Kirchhoff equations I: coincident centers of gravity and buoyancy , 1998 .

[6]  D. T. Greenwood.  Principles of dynamics , 1965 .

[7]  Kristi A. Morgansen,et al.  Geometric Methods for Modeling and Control of Free-Swimming Fin-Actuated Underwater Vehicles , 2007, IEEE Transactions on Robotics.

[8]  Hong Lei,et al.  Distributed flow estimation and closed-loop control of an underwater vehicle with a multi-modal artificial lateral line , 2015, Bioinspiration & biomimetics.

[9]  Derek A. Paley,et al.  Bio-inspired flow sensing and control: Autonomous rheotaxis using distributed pressure measurements , 2013 .

[10]  Fumin Zhang,et al.  Tail-Enabled Spiraling Maneuver for Gliding Robotic Fish , 2014, Journal of Dynamic Systems, Measurement, and Control.

[11]  Honghai Liu,et al.  Navigation Technologies for Autonomous Underwater Vehicles , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[12]  M. Porfiri,et al.  Design, Modeling, and Characterization of a Miniature Robotic Fish for Research and Education in Biomimetics and Bioinspiration , 2013, IEEE/ASME Transactions on Mechatronics.

[13]  K. Mohseni,et al.  Lift evaluation of a two-dimensional pitching flat plate , 2013 .

[14]  Joel W. Burdick,et al.  Fluid locomotion and trajectory planning for shape-changing robots , 2003 .

[15]  Knut Streitlien,et al.  Extracting energy from unsteady flows through vortex control , 1994 .