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Math. Comput. Appl. 2013, 18(3), 361-372; doi:10.3390/mca18030361

Performance Improvement in Vslam Using Stabilized Feature Points

Faculty of Engineering and Natural Sciences, Sabanci University, 34956, Orhanlı- Tuzla, Istanbul, Turkey
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Published: 1 December 2013
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Abstract

Simultaneous localization and mapping (SLAM) is the main prerequisite for the autonomy of a mobile robot. In this paper, we present a novel method that enhances the consistency of the map using stabilized corner features. The proposed method integrates template matching based video stabilization and Harris corner detector. Extracting Harris corner features from stabilized video consistently increases the accuracy of the localization. Data coming from a video camera and odometry are fused in an Extended Kalman Filter (EKF) to determine the pose of the robot and build the map of the environment. Simulation results validate the performance improvement obtained by the proposed technique.
Keywords: vSLAM; Video stabilization; Feature extraction; Extended Kalman Filter vSLAM; Video stabilization; Feature extraction; Extended Kalman Filter
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Şahin, C.; Ünel, M. Performance Improvement in Vslam Using Stabilized Feature Points. Math. Comput. Appl. 2013, 18, 361-372.

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