Dynamic Image Interpretation for Autonomous Vehicle Navigation.

Abstract

The contractor's Autonomous Land Vehicle Project has been concerned with a variety of problems associated with sensor momotion analysis and dynamic image interpretation of autononmous navigation. Ling-range research goals include: 1. Determine the motion parameters of a senor relative to the static environment. 2. Distinguish moving objects from the static environment and determine their motion parameters. 3. Develop algorithms for tracking and predicting the motion and environmental location of the sensor and moving objects. 4. Build a reliable depth map of the environment from combined motion, stereo, and laser range data. 5. Identify major objects (both static and moving) in the environment while the sensor is either stationary or in motion. 6. Interpretation of the environment (i.e., object idnetification in road scenes) to provide constraints for identifying and tracking moving objects. 7. Provide information to update an environmental model of the moving sensor, including location of the sensor, other moving objects and distinguished stationary objects. 8. Provide control information to an expert navigational and spatial-reasoning system for the purposes of path planning and obstacle avoidance. 9. Integrate all of the above capabilities into a flexible and extensible system for dynamic scene interpretation.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1986
Accession Number
ADA173209

Entities

People

  • Allen R. Hanson
  • Edward M. Riseman

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Algorithms
  • Autonomous Vehicles
  • Boundaries
  • Classification
  • Collision Avoidance
  • Computations
  • Computer Vision
  • Environment
  • Errors
  • Hypotheses
  • Image Recognition
  • Massachusetts
  • Navigation
  • Universities
  • Vehicles

Readers

  • Computer Vision.
  • Robotics and Automation.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • Autonomy
  • Directed Energy