Self-motion effects on hydrodynamic pressure sensing: part I. forward-backward motion.

In underwater locomotion, extracting meaningful information from local flows is as desirable as it is challenging, due to complex fluid-structure interaction. Sensing and motion are tightly interconnected; hydrodynamic signals generated by the external stimuli are modified by the self-generated flow signals. Given that very little is known about self-generated signals, we used onboard pressure sensors to measure the pressure profiles over the head of a fusiform-shape craft while moving forward and backward harmonically.

Hydrodynamic pressure sensing with an artificial lateral line in steady and unsteady flows.

With the overall goal being a better understanding of the sensing environment from the local perspective of a situated agent, we studied uniform flows and Kármán vortex streets in a frame of reference relevant to a fish or swimming robot. We visualized each flow regime with digital particle image velocimetry and then took local measurements using a rigid body with laterally distributed parallel pressure sensor arrays. Time and frequency domain methods were used to characterize hydrodynamically relevant scenarios in steady and unsteady flows for control applications.

What information do Kármán streets offer to flow sensing?

In this work, we focus on biomimetic lateral line sensing in Kármán vortex streets. After generating a Kármán street in a controlled environment, we examine the hydrodynamic images obtained with digital particle image velocimetry (DPIV). On the grounds that positioning in the flow and interaction with the vortices govern bio-inspired underwater locomotion, we inspect the fluid in the swimming robot frame of reference.