Visual Navigation for an Autonomous Mobile Vehicle

Abstract

Image understanding for a mobile robotic vehicle is an important and complex task for ensuring safe navigation and extended autonomous operations. The goal of this work is to implement a working vision-based navigation control mechanism within a known environment onboard the autonomous mobile vehicle Yamabico-11. Although installing a working hardware system was not accomplished, the image processing, model description, pattern matching, and positional correction methods have all been implemented and tested on a graphics workstation. A novel approach for straight-edge feature extraction based upon least squares fitting of edge-related pixels is presented and implemented for the image processing task. A simple method for determining the camera's location and orientation (pose) follows by matching the vertical extracted edges from an image with the linear features of a two-dimensional view of the modelled environment based upon an estimated pose of the robot. Image processing, construction of the two dimensional view of the model, and pose determination are conducted sequentially in less than one minute for a 646 x 86 pixel image on a 35 MHz processor. The pose determination results have been tested to be accurate within a few inches for translational error and within one degree rotational error.

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Document Details

Document Type
Technical Report
Publication Date
Mar 26, 1992
Accession Number
ADA251669

Entities

People

  • Kevin R. Peterson

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Cameras
  • Charge Coupled Devices
  • Computer Languages
  • Computer Programming
  • Computer Science
  • Computer Vision
  • Computers
  • Coordinate Systems
  • Dead Reckoning
  • Image Processing
  • Machine Perception
  • Object Recognition
  • Recognition
  • Three Dimensional
  • Two Dimensional
  • Unmanned Vehicles

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Robotics and Automation.

Technology Areas

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