Vision-aided inertial navigation for flight control

Allen D. Wu, Eric N. Johnson, Alison A. Proctor

Research output: Contribution to journalReview article

72 Scopus citations

Abstract

Many onboard navigation systems use the Global Positioning System to bound the errors that result from integrating inertial sensors over time. Global Positioning System information, however, is not always accessible since it relies on external satellite signals. To this end, a vision sensor is explored as an alternative for inertial navigation in the context of an Extended Kalman Filter used in the closed-loop control of an unmanned aerial vehicle. The filter employs an onboard image processor that uses camera images to provide information about the size and position of a known target, thereby allowing the flight computer to derive the target's pose. Assuming that the position and orientation of the target are known a priori, vehicle position and attitude can be determined from the fusion of this information with inertial and heading measurements. Simulation and flight test results verify filter performance in the closed-loop control of an unmanned rotorcraft.

Original languageEnglish (US)
Pages (from-to)348-360
Number of pages13
JournalJournal of Aerospace Computing, Information and Communication
Volume2
Issue number9
DOIs
StatePublished - Sep 2005

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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