Monocular vision SLAM for indoor aerial vehicles

Koray Çelik, Soon Jo Chung, Matthew Clausman, Arun K. Somani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a novel indoor navigation and ranging strategy by using a monocular camera. The proposed algorithms are integrated with simultaneous localization and mapping (SLAM) with a focus on indoor aerial vehicle applications. We experimentally validate the proposed algorithms by using a fully self-contained micro aerial vehicle (MAV) with on-board image processing and SLAM capabilities. The range measurement strategy is inspired by the key adaptive mechanisms for depth perception and pattern recognition found in humans and intelligent animals. The navigation strategy assumes an unknown, GPS-denied environment, which is repre-sentable via corner-like feature points and straight architectural lines. Experimental results show that the system is only limited by the capabilities of the camera and the availability of good corners.

Original languageEnglish (US)
Title of host publication2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009
Pages1566-1573
Number of pages8
DOIs
StatePublished - Dec 11 2009
Event2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009 - St. Louis, MO, United States
Duration: Oct 11 2009Oct 15 2009

Publication series

Name2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009

Other

Other2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009
Country/TerritoryUnited States
CitySt. Louis, MO
Period10/11/0910/15/09

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Control and Systems Engineering

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