Aerial Visual-Inertial Odometry Performance Evaluation

Abstract

With the cheapening of optical camera technology and an increasing interest in reducing GPS dependency, computer vision-based navigation algorithms have grown in popularity. This experiment implementsfive visual odometry algorithms into a common framework, evaluating their accuracy in a variety of situations on an unprecedented level. A variety of techniques are compared and contrasted including FAST-features versus gridded pixel-features, inertial-aided and inertial-independent rotation estimation, the effectiveness of image histogram equalization, the benefits of image rectification, and two-frame versus multi-frame visual odometry.

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Document Details

Document Type
Technical Report
Publication Date
Mar 23, 2017
Accession Number
AD1054725

Entities

People

  • Daniel J. Carson

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Autonomous Vehicles
  • Computer Programs
  • Computer Vision
  • Detectors
  • Fixed Wing Aircraft
  • Global Positioning Systems
  • Governments
  • Inertial Measurement Units
  • Inertial Navigation
  • Inertial Navigation Systems
  • Kalman Filters
  • Measurement
  • Navigation
  • Simultaneous Localization And Mapping
  • Three Dimensional
  • United States Government

Readers

  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Computational Modeling and Simulation
  • Image Processing and Computer Vision.

Technology Areas

  • AI & ML
  • Space