Computer Science – Computer Vision and Pattern Recognition
Scientific paper
2011-07-02
Proceedings of the IEEE International Conference on Robotics and Biomimetics (ROBIO), 2011 , Page(s): 1591 - 1596
Computer Science
Computer Vision and Pattern Recognition
26 pages, 3 figures, in English and in Russian. arXiv admin note: substantial text overlap with arXiv:1106.6341, arXiv:1107.14
Scientific paper
10.1109/ROBIO.2011.6181516
An algorithm for pose and motion estimation using corresponding features in images and a digital terrain map is proposed. Using a Digital Terrain (or Digital Elevation) Map (DTM/DEM) as a global reference enables recovering the absolute position and orientation of the camera. In order to do this, the DTM is used to formulate a constraint between corresponding features in two consecutive frames. The utilization of data is shown to improve the robustness and accuracy of the inertial navigation algorithm. Extended Kalman filter was used to combine results of inertial navigation algorithm and proposed vision-based navigation algorithm. The feasibility of this algorithms is established through numerical simulations.
Kupervasser Oleg
Voronov Vladimir V.
No associations
LandOfFree
Vision-Based Navigation I: A navigation filter for fusing DTM/correspondence updates does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Vision-Based Navigation I: A navigation filter for fusing DTM/correspondence updates, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Vision-Based Navigation I: A navigation filter for fusing DTM/correspondence updates will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-175312