High Altitude Stereo Visual Odometry
Author(s) -
Michael Warren,
Ben Upcroft
Publication year - 2013
Publication title -
science & engineering faculty
Language(s) - English
Resource type - Conference proceedings
DOI - 10.15607/rss.2013.ix.003
Subject(s) - computer vision , visual odometry , artificial intelligence , computer science , stereopsis , computer graphics (images) , robot
Stereo visual odometry has received little investigation in high altitude applications due to the generally poor performance of rigid stereo rigs at extremely small baseline-to-depth ratios. Without additional sensing, metric scale is considered lost and odometry is seen as effective only for monocular perspectives. This paper presents a novel modification to stereo based visual odometry that allows accurate, metric pose estimation from high altitudes, even in the presence of poor calibration and without additional sensor inputs. By relaxing the (typically fixed) stereo transform during bundle adjustment and reducing the dependence on the fixed geometry for triangulation, metrically scaled visual odometry can be obtained in situations where high altitude and structural deformation from vibration would cause traditional algorithms to fail. This is achieved through the use of a novel constrained bundle adjustment routine and accurately scaled pose initializer. We present visual odometry results demonstrating the technique on a short-baseline stereo pair inside a fixed-wing UAV flying at significant height (~30-100m).
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