Sankaewtong Krongtum, Molina John J, Turner Matthew S, Yamamoto Ryoichi
Department of Chemical Engineering, Kyoto University, Kyoto 615-8510, Japan.
Department of Physics, University of Warwick, Coventry CV4 7AL, United Kingdom.
Phys Rev E. 2023 Jun;107(6-2):065102. doi: 10.1103/PhysRevE.107.065102.
Microswimmers can acquire information on the surrounding fluid by sensing mechanical queues. They can then navigate in response to these signals. We analyze this navigation by combining deep reinforcement learning with direct numerical simulations to resolve the hydrodynamics. We study how local and nonlocal information can be used to train a swimmer to achieve particular swimming tasks in a nonuniform flow field, in particular, a zigzag shear flow. The swimming tasks are (1) learning how to swim in the vorticity direction, (2) learning how to swim in the shear-gradient direction, and (3) learning how to swim in the shear-flow direction. We find that access to laboratory frame information on the swimmer's instantaneous orientation is all that is required in order to reach the optimal policy for tasks (1) and (2). However, information on both the translational and rotational velocities seems to be required to accomplish task (3). Inspired by biological microorganisms, we also consider the case where the swimmers sense local information, i.e., surface hydrodynamic forces, together with a signal direction. This might correspond to gravity or, for microorganisms with light sensors, a light source. In this case, we show that the swimmer can reach a comparable level of performance to that of a swimmer with access to laboratory frame variables. We also analyze the role of different swimming modes, i.e., pusher, puller, and neutral.
微型游动器可以通过感知机械信号来获取周围流体的信息。然后，它们可以根据这些信号进行导航。我们通过将深度强化学习与直接数值模拟相结合来解析流体动力学，从而分析这种导航行为。我们研究如何利用局部和非局部信息来训练游动器，使其在非均匀流场中，特别是在锯齿形剪切流中完成特定的游动任务。这些游动任务包括：（1）学习如何在涡度方向上游动；（2）学习如何在剪切梯度方向上游动；（3）学习如何在剪切流方向上游动。我们发现，为了实现任务（1）和（2）的最优策略，只需要获取关于游动器瞬时方向的实验室坐标系信息。然而，完成任务（3）似乎需要平移速度和旋转速度的信息。受生物微生物的启发，我们还考虑了游动器感知局部信息（即表面流体动力）以及信号方向的情况。这可能对应于重力，或者对于具有光传感器的微生物来说，对应于光源。在这种情况下，我们表明游动器可以达到与能够获取实验室坐标系变量的游动器相当的性能水平。我们还分析了不同游动模式（即推进器、牵拉器和中性模式）的作用。
