Coordination of Multiple Robotic Fish With Applications to Underwater Robot Competition

This paper is concerned with the coordination control of multiple biomimetic robotic fish in highly dynamic aquatic environments by building a hybrid centralized system. With the aid of the results of biorobotics and control techniques, a radio-controlled multijoint robotic fish and its locomotion control are developed. To enable a closed control loop, a visual subsystem that is responsible for tracking of multiple moving objects is constructed and implemented in real time. Furthermore, a behavior-based hierarchical architecture in conjunction with fuzzy reinforcement learning is proposed to accomplish effective coordination among multiple swimming robots. Finally, experiments on 2vs2 water polo game are carried out to verify the proposed coordination control scheme. Over the past eight years, this multirobot platform has been successfully applied to international underwater robot competitions to promote innovative research and education in underwater robotics.

[1]  Jianwei Zhang,et al.  Amphibious Pattern Design of a Robotic Fish with Wheel‐propeller‐fin Mechanisms , 2013, J. Field Robotics.

[2]  Oussama Khatib,et al.  Springer Handbook of Robotics , 2007, Springer Handbooks.

[3]  Ming Wang,et al.  Three-Dimensional Swimming , 2011, IEEE Robotics & Automation Magazine.

[4]  Nicolas Jouandeau,et al.  A Survey and Analysis of Multi-Robot Coordination , 2013 .

[5]  Peter Dayan,et al.  Q-learning , 1992, Machine Learning.

[6]  Fei Wang,et al.  A Robust Real-Time Vision System for Autonomous Cargo Transfer by an Unmanned Helicopter , 2015, IEEE Transactions on Industrial Electronics.

[7]  KasabovNikola,et al.  2008 Special issue , 2008 .

[8]  Long Wang,et al.  Cooperation of Multiple Fish-like Microrobots Based on Reinforcement Learning , 2007, 2007 IEEE Symposium on Artificial Life.

[9]  Tianmiao Wang,et al.  Parameter Synthesis of Coupled Nonlinear Oscillators for CPG-Based Robotic Locomotion , 2014, IEEE Transactions on Industrial Electronics.

[10]  Junzhi Yu,et al.  Development of a biomimetic robotic fish and its control algorithm , 2004, IEEE Trans. Syst. Man Cybern. Part B.

[11]  Benjamin J. Southwell,et al.  Human Object Recognition Using Colour and Depth Information from an RGB-D Kinect Sensor , 2013 .

[12]  Guangming Xie,et al.  CPG-Based Locomotion Control of a Robotic Fish: Using Linear Oscillators and Reducing Control Parameters via PSO , 2011 .

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

[14]  Jianwei Zhang,et al.  A Survey on CPG-Inspired Control Models and System Implementation , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[15]  Auke Jan Ijspeert,et al.  Controlling swimming and crawling in a fish robot using a central pattern generator , 2008, Auton. Robots.

[16]  Frank E. Fish,et al.  Advantages of natural propulsive systems , 2013 .

[17]  Long Wang,et al.  Visual Tracking of Multiple Robotic Fish for Cooperative Control , 2006, 2006 IEEE International Conference on Robotics and Biomimetics.

[18]  Li Wen,et al.  Novel Method for the Modeling and Control Investigation of Efficient Swimming for Robotic Fish , 2012, IEEE Transactions on Industrial Electronics.

[19]  K. S. Rattan,et al.  Design of a neuro-fuzzy controller , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[20]  Chia-Feng Juang,et al.  Reinforcement Ant Optimized Fuzzy Controller for Mobile-Robot Wall-Following Control , 2009, IEEE Transactions on Industrial Electronics.

[21]  Auke Jan Ijspeert,et al.  Central pattern generators for locomotion control in animals and robots: A review , 2008, Neural Networks.

[22]  Huosheng Hu.  Biologically Inspired Design of Autonomous Robotic Fish at Essex , 2006 .

[23]  Paul Zarchan,et al.  Tactical and strategic missile guidance , 1990 .

[24]  Antonios Tsourdos,et al.  Guest Editorial Introduction to the Special Issue on Multivehicle Systems Cooperative Control With Application , 2007 .

[25]  Andrew W. Moore,et al.  Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..

[26]  Li Wen,et al.  Development of a two‐joint robotic fish for real‐world exploration , 2011, J. Field Robotics.

[27]  Wenwu Yu,et al.  An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination , 2012, IEEE Transactions on Industrial Informatics.

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

[29]  Peter Dayan,et al.  Technical Note: Q-Learning , 2004, Machine Learning.