Fish can save energy via proprioceptive sensing.

Journal: Bioinspiration & biomimetics
Published Date:

Abstract

Fish have evolved diverse and robust locomotive strategies to swim efficiently in complex fluid environments. However, we know little, if anything, about how these strategies can be achieved. Although most studies suggest that fish rely on the lateral line system to sense local flow and optimise body undulation, recent work has shown that fish are still able to gain benefits from the local flow even with the lateral line impaired. In this paper, we hypothesise that fish can save energy by extracting vortices shed from their neighbours using only simple proprioceptive sensing with the caudal fin. We tested this hypothesis on both computational and robotic fish by synthesising a central pattern generator (CPG) with feedback, proprioceptive sensing, and reinforcement learning. The CPG controller adjusts the body undulation after receiving feedback from the proprioceptive sensing signal, decoded via reinforcement learning. In our study, we consider potential proprioceptive sensing inputs to consist of low-dimensional signals (e.g. perceived forces) detected from the flow. With simulations on a computational robot and experiments on a robotic fish swimming in unknown dynamic flows, we show that the simple proprioceptive sensing is sufficient to optimise the body undulation to save energy, without any input from the lateral line. Our results reveal a new sensory-motor mechanism in schooling fish and shed new light on the strategy of control for robotic fish swimming in complex flows with high efficiency.

Authors

  • Liang Li
    School of Psychological and Cognitive Sciences, Peking University, Beijing, 100871, China.
  • Danshi Liu
    Department of Mechanics, Zhejiang University, Hangzhou 310027, People's Republic of China.
  • Jian Deng
    Department of Mechanics, Zhejiang University, Hangzhou 310027, People's Republic of China.
  • Matthew J Lutz
    Department of Collective Behaviour, Max Planck Institute of Animal Behavior, Radolfzell am Bodensee 78315, Germany.
  • Guangming Xie