A Bio-Inspired Strategy for Robotic Fish Swimming in Unsteday Flows

Abstract:

Fish can swim swiftly in complicated flow environments, which conceives inspirations for man-made underwater vehicles. The paper concentrates on some bio-inspired strategies to enable robotic fish better adaptability within changing environments. An adaptive neural method corresponding to environment is proposed and developed with a pair of coupled neural oscillators. A parameters forecasting algorithm is also designed. On the other hand, a notional four joints robotic fish is designed to validate the effectiveness of the model. Simulation results show that the proposed algorithms predict the altering kinematics parameters exactly and improved model can depict the fishs adaptable behaviors. Therefore the effectiveness is further validated for potential applications into robotic fish.

• Periodical: Applied Mechanics and Materials (Volumes 341-342)
• Pages: 754-759
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.341-342.754
• Online since: July 2013
• Authors: Zhao Wei Ma, Han Zhou, Guang Ming Wang, Lin Cheng Shen, Tian Jiang Hu
• Keywords: Adaptive Behavior, Bio-Inspired Strategies, Forecasting Algorithm

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