Title | ||
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Monocular Odometry In Country Roads Based On Phase-Derived Optical Flow And 4-Dof Ego-Motion Model |
Abstract | ||
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Purpose - Positioning is a key task in most field robotics applications but can be very challenging in GPS-denied or high-slip environments. The purpose of this paper is to describe a visual odometry strategy using only one camera in country roads.Design/methodology/approach - This monocular odometery system uses as input only those images provided by a single camera mounted on the roof of the vehicle and the framework is composed of three main parts: image motion estimation, ego-motion computation and visual odometry. The image motion is estimated based on a hyper-complex wavelet phase-derived optical flow field. The ego-motion of the vehicle is computed by a blocked RANdom SAmple Consensus algorithm and a maximum likelihood estimator based on a 4-degrees of freedom motion model. These as instantaneous ego-motion measurements are used to update the vehicle trajectory according to a dead-reckoning model and unscented Kalman filter.Findings - The authors' proposed framework and algorithms are validated on videos from a real automotive platform. Furthermore, the recovered trajectory is superimposed onto a digital map, and the localization results from this method are compared to the ground truth measured with a GPS/INS joint system. These experimental results indicate that the framework and the algorithms are effective.Originality/value - The effective framework and algorithms for visual odometry using only one camera in country roads are introduced in this paper. |
Year | DOI | Venue |
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2011 | 10.1108/01439911111154081 | INDUSTRIAL ROBOT-THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH AND APPLICATION |
Keywords | Field | DocType |
Monocular odometry, Ego-motion estimation, 4-DOF ego-motion model, Phase-derived optical flow, Blocked RANSAC, Road vehicles, Motion, Robotics | Computer vision,Visual odometry,Simulation,Odometry,Kalman filter,Artificial intelligence,Engineering,Monocular,Optical flow,Trajectory,Robotics,Wavelet | Journal |
Volume | Issue | ISSN |
38 | 5 | 0143-991X |
Citations | PageRank | References |
2 | 0.36 | 18 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Cailing Wang | 1 | 20 | 2.08 |
Chunxia Zhao | 2 | 264 | 19.32 |
Jing-yu Yang | 3 | 6061 | 345.83 |