Fusion of discrete and continuous epipolar geometry for visual odometry and localization | IEEE Conference Publication | IEEE Xplore

Fusion of discrete and continuous epipolar geometry for visual odometry and localization


Abstract:

Localization is a critical problem for building mobile robotic systems capable of autonomous navigation. This paper describes a novel visual odometry method to improve th...Show More

Abstract:

Localization is a critical problem for building mobile robotic systems capable of autonomous navigation. This paper describes a novel visual odometry method to improve the accuracy of localization when a camera is viewing a piecewise planar scene. Discrete and continuous Homography Matrices are used to recover position, heading, and velocity from images of co-planar feature points. A Kalman filter is used to fuse pose and velocity estimates and increase the accuracy of the estimates. Simulation results are presented to demonstrate the performance of the proposed method.
Date of Conference: 15-16 October 2010
Date Added to IEEE Xplore: 23 December 2010
ISBN Information:
Conference Location: Phoenix, AZ, USA

References

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