Performance Improvement in Vslam Using Stabilized Feature Points
AbstractSimultaneous 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.
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Şahin, C.; Ünel, M. Performance Improvement in Vslam Using Stabilized Feature Points. Math. Comput. Appl. 2013, 18, 361-372.
Şahin C, Ünel M. Performance Improvement in Vslam Using Stabilized Feature Points. Mathematical and Computational Applications. 2013; 18(3):361-372.Chicago/Turabian Style
Şahin, Caner; Ünel, Mustafa. 2013. "Performance Improvement in Vslam Using Stabilized Feature Points." Math. Comput. Appl. 18, no. 3: 361-372.