Active gyrotactic stability of microswimmers using hydromechanical signals
Jingran Qiu, Navid Mousavi, Lihao Zhao, Kristian Gustavsson

TL;DR
This paper proposes an active gyrotactic mechanism for microswimmers that uses hydromechanical signals and reinforcement learning to maintain vertical alignment in turbulent flows, improving upward migration efficiency.
Contribution
It introduces a novel active steering strategy for plankton that enhances gyrotactic stability under turbulence, unlike passive mechanisms.
Findings
Active steering improves upward migration in turbulence.
Passive swimmers show reduced or downward migration in turbulence.
Reinforcement learning identifies optimal alignment strategies.
Abstract
Many plankton species undergo daily vertical migration to large depths in the turbulent ocean. To do this efficiently, the plankton can use a gyrotactic mechanism, aligning them with gravity to swim downwards, or against gravity to swim upwards. Many species show passive mechanisms for gyrotactic stability. For example, bottom-heavy plankton tend to align upwards. This is efficient for upward migration in quiescent flows, but it is often sensitive to turbulence which upsets the alignment. Here we suggest a simple, robust active mechanism for gyrotactic stability, which is only lightly affected by turbulence and allows alignment both along and against gravity. We use a model for a plankton that swims with a constant speed and can actively steer in response to hydrodynamic signals encountered in simulations of a turbulent flow. Using reinforcement learning, we identify the optimal…
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Taxonomy
TopicsMicro and Nano Robotics · Biomimetic flight and propulsion mechanisms · Underwater Vehicles and Communication Systems
