Data-driven and Physics-based Flow Characterization using Bioinspired Sensory Systems

Abstract

Data-driven and Physics-based Flow Characterization using Bioinspired Sensory SystemsThe proposed research aims at establishing general design rules for bio-inspired underwater sensory systems. We will develop a mathematical framework for analyzing such sensory systems. This problem consists of (i) identifying the relevant hydrodynamic features orsignatures that need to be reconstructed by the sensors, and (ii) designing sensory layouts that best estimate these hydrodynamic features. The latter involves two aspects: analyzing the effects of the geometric properties of the sensory systems (e.g., layout and number of sensors) on the estimation problem; and devising appropriate strategies for the dynamic deployment of sensors and how they are affected by, and in turn, influence, the properties of the sensory systems (geometry and decoding algorithms). To solve these problems, we will use techniques fromestimation theory coupled to physics-based models and nonlinear control strategies. The ultimate goal is to develop sensory systems that support the autonomous operation of underwater vehicles and the detection of unusual or suspicious flow structures and their sources.

Document Details

Document Type
DoD Grant Award
Publication Date
Mar 03, 2017
Source ID
N000141712287

Entities

People

  • Eva Kanso

Organizations

  • Office of Naval Research
  • United States Navy
  • University of Southern California

Tags

Fields of Study

  • Engineering

Readers

  • Distributed Systems and Data Platform Development
  • Robotics and Automation.

Technology Areas

  • Biotechnology