Modeling of a Dynamic Wave Environment for Unmanned Surface Vessel Control

Abstract

Modeling and simulation methods for the seakeeping dynamics of surface vessels vary widely. Higher fidelity models often demand high computational complexity that limits application to offline computation and are not applicable to all development cycles. These models are often based on solving nonlinear fluid flow equations, which cost time and computational power. Simplified models can reduce complexity, supporting rapid development. For developing control and autonomy of small unmanned surface vessels, choosing model fidelity requires a tradeoff between the accuracy of results and complexity of simulation. This thesis compares two methods for modeling and simulating the seakeeping of a small unmanned vessel: Gazeboan open source, real-time robotics simulator, with an extension that integrates a model for the hydrodynamic wave forces into the rigid-body dynamics engine, and AEGIRa nonlinear motion solver that leverages a high order boundary element method and numerical methods of motion integration. The forces, motions and runtimes are compared for various wave cases. The results suggest that the simplified models generate vessel motions of acceptable fidelity for the development of autonomy, but that for certain wave environments, the differences are significant. The results provide guidance for how the simplified Gazebo extension could be improved without adding significant computational load.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2018
Accession Number
AD1069659

Entities

People

  • Joshua F Malia

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Computational Complexity
  • Computational Fluid Dynamics
  • Computational Science
  • Computers
  • Equations
  • Equations Of Motion
  • Flow
  • Fluid Flow
  • Graphical User Interface
  • Mathematical Models
  • Operating Systems
  • Reliability
  • Robotics
  • Simulations
  • Simulators
  • Unmanned Surface Vehicles
  • Unmanned Vehicles

Readers

  • Computational Fluid Dynamics (CFD)
  • Computational Modeling and Simulation
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • Autonomy