Stereo-Image Matching Using a Speeded Up Robust Feature Algorithm in an Integrated Vision Navigation System

Visual navigation is comparatively advanced without a Global Positioning System (GPS). It obtains environmental information via real-time processing of the data gained through visual sensors. Compared with other methods, visual navigation is a passive method that does not launch light or other radiation applications, thus making it easier to hide. The novel navigation system described in this paper uses stereo-matching combined with Inertial Measurement Units (IMU). This system applies photogrammetric theory and a matching algorithm to identify the matching points of two images of the same scene taken from different views and obtains their 3D coordinates. Integrated with the orientation information output by the IMU, the system reduces model-accumulated errors and improves the point accuracy.

[1]  Larry H. Matthies,et al.  Two years of Visual Odometry on the Mars Exploration Rovers , 2007, J. Field Robotics.

[2]  Jan Skaloud,et al.  Vision-aided inertial navigation system for robotic mobile mapping , 2008 .

[3]  Kurt Konolige,et al.  Large-Scale Visual Odometry for Rough Terrain , 2007, ISRR.

[4]  Avinash C. Kak,et al.  Vision for Mobile Robot Navigation: A Survey , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[6]  Feng Zhu,et al.  Design of a novel stereo vision navigation system for mobile robots , 2005, 2005 IEEE International Conference on Robotics and Biomimetics - ROBIO.

[7]  C. Morandi,et al.  Registration of Translated and Rotated Images Using Finite Fourier Transforms , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Takeo Kanade,et al.  Vision and Navigation for the Carnegie-Mellon Navlab , 1987 .

[9]  Christopher Hunt,et al.  Notes on the OpenSURF Library , 2009 .

[10]  Larry H. Matthies,et al.  Visual odometry on the Mars Exploration Rovers , 2005, 2005 IEEE International Conference on Systems, Man and Cybernetics.

[11]  Cordelia Schmid,et al.  A performance evaluation of local descriptors , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.