Bailey Alana A, Guy Robert D
Department of Mathematics, University of California Davis, One Shields Ave, Davis, CA, 95616, USA.
Eur Phys J E Soft Matter. 2025 Aug 8;48(8-9):48. doi: 10.1140/epje/s10189-025-00511-5.
Metachronal paddling is a swimming strategy in which an organism oscillates sets of adjacent limbs with a constant phase lag, propagating a metachronal wave through its limbs and propelling it forward. This limb coordination strategy is utilized by swimmers across a wide range of Reynolds numbers, which suggests that this metachronal rhythm was selected for its optimality of swimming performance. In this study, we apply reinforcement learning to a swimmer at zero Reynolds number and investigate whether the learning algorithm selects this metachronal rhythm, or if other coordination patterns emerge. We design the swimmer agent with an elongated body and pairs of straight, inflexible paddles placed along the body for various fixed paddle spacings. Based on paddle spacing, the swimmer agent learns qualitatively different coordination patterns. At tight spacings, a back-to-front metachronal wave-like stroke emerges which resembles the commonly observed biological rhythm, but at wide spacings, different limb coordinations are selected. Across all resulting strokes, the fastest stroke is dependent on the number of paddles; however, the most efficient stroke is a back-to-front wave-like stroke regardless of the number of paddles.
错时划水是一种游泳策略，即生物体以恒定的相位滞后摆动相邻的肢体组，通过其肢体传播错时波并推动自身向前。这种肢体协调策略被广泛雷诺数范围内的游泳者所采用，这表明这种错时节奏因其游泳性能的最优性而被选择。在本研究中，我们将强化学习应用于零雷诺数的游泳者，并研究学习算法是否会选择这种错时节奏，或者是否会出现其他协调模式。我们设计了一个具有细长身体的游泳者智能体，并沿着身体放置成对的直的、不可弯曲的桨叶，以实现各种固定的桨叶间距。基于桨叶间距，游泳者智能体学习到质上不同的协调模式。在紧密间距下，会出现一种从后到前的类似错时波的划水动作，类似于常见的生物节奏，但在宽间距下，会选择不同的肢体协调方式。在所有产生的划水动作中，最快的划水动作取决于桨叶的数量；然而，无论桨叶数量如何，最有效的划水动作是从后到前的波状划水动作。
