Abstract
Artificial bacteria flagella (ABFs) are magnetic helical microswimmers that can be remotely controlled via a uniform, rotating magnetic field. Previous studies have used the heterogeneous response of microswimmers to external magnetic fields for achieving independent control. Herein, analytical and reinforcement learning control strategies for path planning to a target by multiple swimmers using a uniform magnetic field are introduced. The comparison of the two algorithms shows the superiority of reinforcement learning in achieving minimal travel time to a target. The results demonstrate, for the first time, the effective independent navigation of realistic microswimmers with a uniform magnetic field in a viscous flow field.
Highlights
The magnetic control of micro-swimming devices [1, 2, 3, 4, 5] through micro-manipulation [6, 7], targeted drug delivery [8, 9] or convection-enhanced transport [10], has created new frontiers for bio-medicine
We note that independent navigation of mm-sized micro-swimmers has been shown in [14] through experiments and simulations, while in [15] a reinforcement learning (RL) algorithm was applied to adjust the velocity of an idealized swimmer in simulations with one way coupling with a complex flow field
We have presented two methods to guide multiple ABFs individually towards targets with a uniform magnetic field
Summary
The magnetic control of micro-swimming devices [1, 2, 3, 4, 5] through micro-manipulation [6, 7], targeted drug delivery [8, 9] or convection-enhanced transport [10], has created new frontiers for bio-medicine. The steering of two micro-propellers along two distinct paths in 3 dimensions has been accomplished with the help of magnetic fields gradients [21] These advances exploited the heterogeneous response of micro-swimmers to a uniform input to achieve independent trajectories along a prescribed path. These control methods are based on short horizon objectives (stay on the prescribed path) and do not provide the trajectory that minimizes the travel time to a target position, in the presence of a background flow. We first present a semi-analytical solution for the simple yet instructive setup of multiple, geometrically distinct ABFs in free space, with zero background flow This result enables understanding of the design constraints for the ABFs necessary for independent control and how their geometric characteristics relate to their travel time. We employ RL to control multiple ABFs trajectories in a broad range of flow conditions including a non-zero background flow
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