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Monocular Vision SLAM for Indoor Aerial Vehicles
Journal of Electrical and Computer Engineering
  • Koray Celik, Iowa State University
  • Arun K. Somani, Iowa State University
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This paper presents a novel indoor navigation and ranging strategy via monocular camera. By exploiting the architectural orthogonality of the indoor environments, we introduce a new method to estimate range and vehicle states from a monocular camera for vision-based SLAM. The navigation strategy assumes an indoor or indoor-like manmade environment whose layout is previously unknown, GPS-denied, representable via energy based feature points, and straight architectural lines. We experimentally validate the proposed algorithms on a fully self-contained microaerial vehicle (MAV) with sophisticated on-board image processing and SLAM capabilities. Building and enabling such a small aerial vehicle to fly in tight corridors is a significant technological challenge, especially in the absence of GPS signals and with limited sensing options. Experimental results show that the system is only limited by the capabilities of the camera and environmental entropy.

This article is from Journal of Electrical and Computer Engineering 2013 (2013): 374165, doi: 10.1155/2013/374165. Posted with permission.

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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K. C¸ elik and A. K. Somani
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Koray Celik and Arun K. Somani. "Monocular Vision SLAM for Indoor Aerial Vehicles" Journal of Electrical and Computer Engineering Vol. 2013 (2013) p. 374165-1 - 374165-15
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