Carnegie Mellon University
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Semi-Dense Visual Odometry for Monocular Navigation in Cluttered Environment

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journal contribution
posted on 2015-05-01, 00:00 authored by Shreyansh Daftry, Debadeepta Dey, Harsimrat Sandhawalia, Sam Zeng, J. Andrew Bagnell, Martial Hebert

Recently, there have been numerous advances in the development of biologically inspired lightweight Micro Aerial Vehicles (MAVs). Due to payload and power constraints it is necessary for such systems to have autonomous navigation and flight capabilites in highly dense and cluttered environments using only passive sensors such as cameras. This is a challenging problem, given they have to operate in highly variable illumination conditions and be responsive to large environmental variations. In this paper we describe a scale-aware monocular vision based semi-dense direct depth perception system that enables robust autonomous navigation of small agile MAVs at low altitude through natural forest environments. We also show qualitative results in an outdoor dense forest area. I




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