Image Understanding for Robot Navigation

Abstract

This paper presents a method to forecast terrain trafficability from visual appearance. During training, the system identifies a set of image chips (or exemplars) that span the range of terrain appearance and measures terrain trafficability characteristics as the vehicle traverses the terrain. Each chip is assigned a vector tag representing the measured vehicle-terrain interaction properties. After training, the system uses the exemplars to segment images into regions, based on visual similarity to terrain patches observed during training, and assigns the appropriate vehicle-terrain interaction tag to them. The system will therefore allow the online forecasting of vehicle performance on upcoming terrain.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2006
Accession Number
ADA481641

Entities

People

  • Gary Witus
  • Robert E. Karlsen

Organizations

  • Tank-automotive and Armaments Command

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Autonomous Navigation
  • Cameras
  • Coding
  • Cognition
  • Coordinate Systems
  • Data Analysis
  • Data Processing
  • Image Processing
  • Image Recognition
  • Image Reconstruction
  • Navigation
  • Psychology
  • Range Finders
  • Recognition
  • Robot Navigation
  • Robots
  • Standards

Fields of Study

  • Computer science

Readers

  • Computer Vision.

Technology Areas

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