Optimal navigation strategies for microswimmers

The quest on how to navigate or steer to optimally reach a target is of paramount importance e.g. for airplanes to save fuel while facing complex wind patterns on their way toward a remote destination. Here, we show that the self-generated flow field induced by microswimmers in a low-Reynolds-number solvent can have a strong influence on the required navigation strategy to reach a target fastest. Accordingly, microswimmers follow swimming trajectories that are qualitatively different from those of dry active particles or motile macroagents. In particular, we demonstrate that the resulting optimal microswimming strategy is useful in the presence of fluctuations where it allows reaching a target up to 50% faster than when following the steering strategy which is optimal for its dry counterparts. Our results provide generic insights regarding the role of hydrodynamics and fluctuations on optimal navigation and might inspire future machine-learning based approaches on optimal microswimming.