Guided navigation in turbulence

Abstract: Navigation in turbulence is challenging because local flow measurements provide limited information about favorable paths beyond the flow correlation scales. We investigate vertical navigation by swimmers in homogeneous isotropic turbulence and compare strategies using local flow information with strategies guided by high-performing trajectories. Compared with naive upward swimming, local strategies enhance the mean vertical velocity by about 10% of the root-mean-square flow velocity, while guidance by precalculated trajectories reaches enhancements of about 40%. This gain is limited by the time required to intercept favorable trajectories, particularly for slow swimmers. We then show that precalculated trajectories are unnecessary: swimmers can dynamically identify high-performing members of a swarm and use them as targets. For sufficiently fast swimmers, this collective strategy keeps much of the benefit of precalculated guidance using only the instantaneous swarm state. Our results demonstrate how distributed trajectory information can be used to overcome limitations of local sensing for navigation in turbulence.