Ocean Intelligence Technology Center, Shenzhen Institute of Guangdong Ocean University, Shenzhen, Guangdong 518055, People's Republic of China.
College of Ocean Engineering, Guangdong Ocean University, Zhanjiang, Guangdong 524088, People's Republic of China.
Bioinspir Biomim. 2022 Nov 16;18(1). doi: 10.1088/1748-3190/ac9fb5.
Fish are observed to school in different configurations. However, how and why fish maintain a stable schooling formation still remains unclear. This work presents a numerical study of the dense schooling of two free swimmers by a hybrid method of the multi-agent deep reinforcement learning and the immersed boundary-lattice Boltzmann method. Active control policies are developed by synchronously training the leader to swim at a given speed and orientation and the follower to hold close proximity to the leader. After training, the swimmers could resist the strong hydrodynamic force to remain in stable formations and meantime swim in desired path, only by their tail-beat flapping. The tail movement of the swimmers in the stable formations are irregular and asymmetrical, indicating the swimmers are carefully adjusting their body-kinematics to balance the hydrodynamic force. In addition, a significant decrease in the mean amplitude and the cost of transport is found for the followers, indicating these swimmers could maintain the swimming speed with less efforts. The results also show that the side-by-side formation is hydrodynamically more stable but energetically less efficient than other configurations, while the full-body staggered formation is energetically more efficient as a whole.
鱼被观察到以不同的配置成群游动。然而，鱼如何以及为什么保持稳定的鱼群形成仍然不清楚。这项工作通过多主体深度强化学习和浸入边界格子玻尔兹曼方法的混合方法，对两个自由游动者的密集鱼群进行了数值研究。通过同步训练领导者以给定的速度和方向游动，以及跟随者保持与领导者的近距离，制定了主动控制策略。训练后，游泳者仅通过拍打尾巴就能抵抗强大的水动力，保持稳定的编队，并同时按照期望的路径游动。游泳者在稳定编队中的尾巴运动是不规则和不对称的，这表明游泳者正在仔细调整他们的身体运动学以平衡水动力。此外，还发现跟随者的平均振幅和运输成本显著降低，这表明这些游泳者可以用更少的力气保持游泳速度。结果还表明，并排编队在水动力上更稳定，但比其他配置效率更低，而全身交错编队作为一个整体效率更高。
