Synchronisation through learning for two self-propelled swimmers

Abstract

We study the fluid dynamics of two fish-like bodies with synchronised swimming patterns. Our studies are based on two-dimensional simulations of viscous incompressible flows. We distinguish between motion patterns that are externally imposed on the swimmers and self-propelled swimmers that learn manoeuvres to achieve certain goals. Simulations of two rigid bodies executing pre-specified motion indicate that flow-mediated interactions can lead to substantial drag reduction and may even generate thrust intermittently. In turn we examine two self-propelled swimmers arranged in a leader-follower configuration, with a-priori specified body-deformations. We find that the swimming of the leader remains largely unaffected, while the follower experiences either an increase or decrease in swimming speed, depending on the initial conditions. Finally, we consider a follower that synchronises its motion so as to minimize its lateral deviations from the leader's path. The leader employs a steady gait while the follower uses a reinforcement learning algorithm to adapt its swimming-kinematics. We find that swimming in a synchronised tandem can yield up to about 30% reduction in energy expenditure for the follower, in addition to a 20% increase in its swimming-efficiency. The present results indicate that synchronised swimming of two fish can be energetically beneficial.

On the energetics and stability of a minimal fish school

“…Its most important advantage in the present context is that it provides a 47 direct quantitative estimate to the hydrodynamic power in self-propelled swimming. 48 Although the CFD modelling of collective swimming is not new, most of the prior work 49 has been limited to groups of two-dimensional (2D) swimmers in 2D fluids [16][17][18][19][20][21][22][23][24][25]. To test the influence of phase difference, for each position (circles) we implemented four simulations (δφ = 0, T /4, T /2 and 3T /4, respectively).…”

Numerical Simulation and Analysis of Fish-Like Robots Swarm

“…We illustrate this by analyzing the flow field in Figure 11 and Table 4. Near the head of the fish robot, if the velocity direction of fluid in vertical direction was the same as the direction of fish swinging, the fish had better efficiency [25]. In this work, the wake indicates the vertical velocity of fluid.…”

“…Weihs [24] proposes a hydrodynamic theory of schooling that a fish in a diamond school swimming between two adjacent fish wakes can save energy. Novati et al [25], through employing reinforcement learning, adjust swimming motions and relative positions to reach a stable tandem configuration, at the same time the follower swimmer can reduce energy. Maertens et al [26] establish optimal undulatory propulsion for a single fish by numerical simulation and find that the follower fish saved energy at any position as it can appropriately modulate its body motions according to the oncoming vortices.…”

“…Discuss the influence of the wake [25,31] and the pressure field generated by the fish-like robot tail swing on the Froude efficiency, and analyze the effect of fish-like robot spacing on swarm performance. The influence of the wake especially the direction and size on tandem swarm is analyzed detailedly, and the results of other formations are consistent with it.…”

An Environmental Perception Framework for Robotic Fish Formation Based on Machine Learning Methods

“…A single robot with multiple capabilities cannot necessarily accomplish a complicated task successfully, whereas a robot swarm in which each robot has its own functions, can be more flexible, robust, and cost-effective and do complex tasks [10]. Recent studies [11][12][13][14][15] show that robotic fish formation can improve swimming efficiency. However, in the underwater environment, the velocity and viscosity of fluids, the complex geometry environment condition and even the interaction between robots can affect the stability of underwater robots formation.…”