Heading Prediction in Unmanned Ground Vehicles by Laser Compass

Abstract

This paper presents an on-line algorithm which provides high signal to noise ratio heading predictions for unmanned ground vehicles. The algorithm uses cross correlation of SICK laser scans to improve the heading predictions from GPS. It is tested on our ground vehicles in outdoor urban environment and verified to provide accurate smooth heading predictions which help with the accurate localization of the vehicle.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2009
Accession Number
AD1108266

Entities

People

  • Bob Grabowski
  • Cindy Cicalese
  • Keven Ring
  • Kevin Forbes
  • Mey Khalili
  • Richard Weatherly
  • Robert Bolling

Organizations

  • MITRE Corporation

Tags

Communities of Interest

  • Autonomy
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programming
  • Computer Vision
  • Corporations
  • Cross Correlation
  • Environment
  • Global Positioning Systems
  • Ground Vehicles
  • Interpolation
  • Meteors
  • Navigation
  • Operating Systems
  • Pattern Recognition
  • Probability Distributions
  • Programming Languages
  • Robotics
  • Robots
  • Simulations
  • Simultaneous Localization And Mapping
  • Statistics
  • Unmanned Ground Systems
  • Unmanned Ground Vehicles
  • Vehicles

Fields of Study

  • Engineering
  • Physics

Readers

  • Computational Fluid Dynamics (CFD)
  • Image Processing and Computer Vision.
  • Robotics and Automation.

Technology Areas

  • Autonomy
  • Directed Energy
  • Space