Advances in Simultaneous Localization and Mapping in Confined Underwater Environments Using Sonar and Optical Imaging

Abstract

This thesis reports on the incorporation of surface information into a probabilistic simultaneous localization and mapping (SLAM) framework used on an autonomous underwater vehicle (AUV) designed for underwater inspection. AUVs operating in cluttered underwater environments, such as ship hulls or dams, are commonly equipped with Doppler based sensors, whichin addition to navigationprovide a sparse representation of the environment in the form of a three-dimensional (3D) point cloud. The goal of this thesis is to develop perceptual algorithms that take full advantage of these sparse observations for correcting navigational drift and building a model of the environment. In

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2016
Accession Number
AD1015537

Entities

People

  • Paul Ozog

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Autonomy
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Autonomous Underwater Vehicles
  • Cameras
  • Computational Complexity
  • Computational Science
  • Computer-Aided Design
  • Geometry
  • Global Positioning Systems
  • Information Science
  • Kalman Filters
  • Mathematical Filters
  • Measurement
  • Monte Carlo Method
  • Navigation
  • Simultaneous Localization And Mapping
  • Surveys
  • Three Dimensional
  • Unmanned Aerial Vehicles

Readers

  • Acoustical Oceanography.
  • Computer Vision.