Flow Currents Support Simple and Versatile Trail-Tracking Strategies

Aquatic animals offer compelling evidence that flow sensing alone, without vision, is sufficient to guide a swimming organism to the source of an unsteady hydrodynamic trail. However, the sensory feedback strategies that allow these remarkable trail tracking abilities remain opaque. Here, by integrating mechanistic flow simulations with reinforcement learning techniques, we discovered two simple and equally effective strategies for hydrodynamic trail following. Though not a priori obvious, these strategies possess parsimonious interpretations, analogous to Braitenbergs simplest vehicles, where the agent senses local flow signals and turns away from or toward the direction of stronger signals. A rigorous stability analysis shows that the effectiveness of these strategies in robustly tracking flow currents is independent of the type of sensor but depends on sensor placement and the traveling nature of the flow signal. Importantly, these results inform a suite of versatile strategies for hydrodynamic trail following applicable to both vortical and turbulent flows. These insights support the future design and implementation of adaptive real-time sensory feedback strategies for autonomous robots in dynamic flow environments.