Link Foundation Ocean Engineering and Instrumentation Fellowship Reports
Stream-dwelling fish and aquatic mammals have an innate ability to navigate often-tumultuous environments with impressive precision, a highly desirable trait for underwater vehicle applications. For example, trout use their lateral line to sense vortices shed by an upstream obstacle and slalom between the vortices to reduce energy expenditure compared to free-stream swimming . Moreover, harbor seals can use their whiskers to follow the trail of flow disturbances created in the wake of an object that has passed minutes before . Recent developments in materials science have produced sensors that can measure local flow velocity similar to seal whiskers, and integration of this sensing modality may enhance the navigation abilities of underwater vehicles beyond traditional means. The goal of this project was to assimilate measurements from a bio-inspired, multi-modal sensor array composed of local flow velocity sensors and pressure sensors to improve the guidance and navigation of underwater vehicles. Specifically, the theoretical and experimental aims of the project include 1) to derive estimation algorithms that assimilate measurements from a multi-modal, bio-inspired sensor array to allow an underwater vehicle to estimate the size and position of an obstacle based on the properties of the wake it produces, 2) to derive control algorithms steering the vehicle to station-holding behavior in which the vehicle holds its position behind the obstacle, and 3) to validate theoretical results by creating an underwater testbed in a stream-like environment. Within the context of current activities in the field, this work incorporates local flow velocity and pressure gradient measurements, creating a multi-modal, distributed sensor array to estimate properties of the fluid environment. Prior works have investigated using pressure gradient measurements for purposes including obstacle , or vortex detection ,, however, these methods assume a single sensing modality rather than a multi-modal array and did not incorporate feedback control using estimated properties of the environment.
DeVries, Levi, "Bio-Inspired Flow Sensing for Underwater Guidance and Navigation" (2014). Link Foundation Ocean Engineering and Instrumentation Fellowship Reports. 22.