Indoor Navigation for Unmanned Aerial Vehicles

Abstract

The ability for vehicles to navigate unknown environments is critical for autonomous operation. Mapping of a vehicle's environment and self-localization within that environment are especially difficult for an Unmanned Aerial Vehicle (UAV) due to the complexity of UAV attitude and motion dynamics, as well as interference from external influences such as wind. By using a stable vehicle platform and taking advantage of the geometric structure typical of most indoor environments, the complexity of the localization and mapping problem can be reduced. Interior wall and obstacle location can be measured using low-cost range sensors. Relative vehicle location within the mapped environment can then be determined. By alternating between mapping and localization, a vehicle can explore its environment autonomously. This paper examines available low-cost range sensors for suitability in solving the mapping and localization problem. A control system and navigation algorithm are developed to perform mapping of indoor environments and localization. Simulation and experimental results are provided to determine feasibility of the proposed approach to indoor navigation.

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Document Details

Document Type
Technical Report
Publication Date
Aug 13, 2009
Accession Number
ADA507764

Entities

People

  • D. M. Sobers Jr.
  • Eric N. Johnson
  • Girish Chowdhary

Organizations

  • Georgia Tech

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Collision Avoidance
  • Control Systems
  • Coordinate Systems
  • Global Positioning Systems
  • Ground Control Stations
  • Guidance
  • Infrared Detectors
  • Kalman Filters
  • Measurement
  • Navigation
  • Range Finders
  • Rotary Wing Aircraft
  • Two Dimensional
  • Unmanned Aerial Vehicles
  • Vehicles

Fields of Study

  • Engineering

Readers

  • Acoustical Oceanography.
  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Robotics and Automation.

Technology Areas

  • Autonomy