Autonomous Vision-based Rotorcraft Landing and Accurate Aerial Terrain Mapping in an Unknown Environment

Abstract

In this report, we present research toward a vision-based landing system for unmanned rotorcraft in unknown terrain that is centered around our Recursive Multi-Frame Planar Parallax algorithm for high-accuracy terrain mapping. We give an in-depth description of the vision system, an overview of our experimental platforms, and both synthetic and experimental terrain mapping results.

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Document Details

Document Type
Technical Report
Publication Date
Jan 22, 2007
Accession Number
ADA637136

Entities

People

  • Todd R. Templeton

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Biomedical
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Aircrafts
  • Algorithms
  • Collision Avoidance
  • Computer Programs
  • Computers
  • Control Systems
  • Coordinate Systems
  • Detectors
  • Flight Control Systems
  • Global Positioning Systems
  • Grids
  • Kalman Filters
  • Model Predictive Control
  • Navigation
  • Three Dimensional
  • Unmanned Aerial Vehicles

Readers

  • Astronomy and Astrophysics.
  • Image Processing and Computer Vision.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • Autonomy