Optimal Control of Microswimmers for Trajectory Tracking Using Bayesian Optimization

• URL: http://arxiv.org/abs/2602.09563v1
• Date: Tue, 10 Feb 2026 09:14:32 GMT
• Title: Optimal Control of Microswimmers for Trajectory Tracking Using Bayesian Optimization
• Abstract summary: Trajectory tracking for microswimmers remains a key challenge in microrobotics.<n>We formulate the trajectory tracking problem as an optimal control problem using a combination of B-spline parametrization and Bayesian optimization.
• Score: 0.10705399532413612
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Trajectory tracking for microswimmers remains a key challenge in microrobotics, where low-Reynolds-number dynamics make control design particularly complex. In this work, we formulate the trajectory tracking problem as an optimal control problem and solve it using a combination of B-spline parametrization with Bayesian optimization, allowing the treatment of high computational costs without requiring complex gradient computations. Applied to a flagellated magnetic swimmer, the proposed method reproduces a variety of target trajectories, including biologically inspired paths observed in experimental studies. We further evaluate the approach on a three-sphere swimmer model, demonstrating that it can adapt to and partially compensate for wall-induced hydrodynamic effects. The proposed optimization strategy can be applied consistently across models of different fidelity, from low-dimensional ODE-based models to high-fidelity PDE-based simulations, showing its robustness and generality. These results highlight the potential of Bayesian optimization as a versatile tool for optimal control strategies in microscale locomotion under complex fluid-structure interactions.

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