Title: Image-Aided Navigation Using Cooperative Binocular Stereopsis
Author(s): Justin Soeder and John Raquet
Published in: NAVIGATION, Journal of the Institute of Navigation, Volume 62, Number 3
Pages: 239 - 248
Cite this article: Soeder, Justin, Raquet, John, "Image-Aided Navigation Using Cooperative Binocular Stereopsis", NAVIGATION, Journal of The Institute of Navigation, Vol. 62, No. 3, Fall 2015, pp. 239-248.
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Abstract: This paper proposes a novel method for estimating the positions of two vehicles in a global reference frame based on synchronized image and navigational information. The proposed technique leverages one vehicle’s ability to localize itself relative to another using image data, enabling motion estimation from tracking common features. The visual odometry algorithm of this work uses the optimal vehicle motion over a single time interval estimated from the positions of common features in a bundle adjustment algorithm as a delayed state extended Kalman filter (EKF) measurement. The algorithm achieves accurate motion estimation and is a potential alternative to map-based simultaneous localization and mapping (SLAM) algorithms.