Using a robotic platform to study the influence of relative tailbeat phase on the energetic costs of side-by-side swimming in fish

  • Liang Li
    Department of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany
  • Sridhar Ravi
    School of Engineering and Information Technology, University of New South Wales - Canberra, Australia
  • Guangming Xie
    State Key Laboratory for Turbulence and Complex Systems, College of Engineering, Peking University, Beijing, People’s Republic of China
  • Iain D. Couzin
    Department of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany

説明

<jats:p> A potential benefit of swimming together in coordinated schools is to allow fish to extract energy from vortices shed by their neighbours, thus reducing the costs of locomotion. This hypothesis has been very hard to test in real fish schools, and it has proven very difficult to replicate the complex hydrodynamics at relevant Reynolds numbers using computational simulations. A complementary approach, and the one we adopt here, is to develop and analyse the performance of biomimetic autonomous robotic models that capture the salient kinematics of fish-like swimming, and also interact via hydrodynamic forces. We developed bio-inspired robotic fish which perform sub-carangiform locomotion, and measured the speed and power consumption of robots when swimming in isolation and when swimming side-by-side in pairs. We found that swimming side-by-side confers a substantial increase in both the speed and efficiency of locomotion of both fish regardless of the relative phase relationship of their body undulations. However, we also find that each individual can slightly increase their own power efficiency if they change relative tailbeat phase by approximately 0.25 <jats:italic>π</jats:italic> with respect to, and at the energetic expense of, their neighbour. This suggests the possibility of a competitive game-theoretic dynamic between individuals in swimming groups. Our results also demonstrate the potential applicability of our platform, and provide a natural connection between the biology and robotics of collective motion. </jats:p>

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