Robotic Manifold Tracking of Coherent Structures in Flows

Abstract

Tracking Lagrangian coherent structures in dynamical systems is important for many applications such as oceanography and weather prediction. In this paper, we present a collaborative robotic control strategy designed to track stable and unstable manifolds. The technique does not require global information about the fluid dynamics, and is based on local sensing, prediction, and correction. The collaborative control strategy is implemented on a team of three robots to track coherent structures and manifolds on static flows as well as a noisy time-dependent model of a wind-driven double-gyre often seen in the ocean. We present simulation and experimental results and discuss theoretical guarantees of the collaborative tracking strategy.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2012
Accession Number
ADA568142

Entities

People

  • Eric Forgoston
  • Ira B. Schwartz
  • M. A. Hsieh
  • T. W. Mather

Organizations

  • Drexel University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Autonomous Underwater Vehicles
  • Boundaries
  • Computational Science
  • Cooperative Control
  • Differential Equations
  • Dynamics
  • Fluid Dynamics
  • Measurement
  • Mechanical Engineering
  • Mechanics
  • Military Research
  • Oceans
  • Physics
  • Simulations
  • Stratified Fluids
  • Time Intervals
  • Two Dimensional

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Coastal Oceanography
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control