Abstract
A monocular visual odometry algorithm is presented that is able to estimate the rover’s 3D motion by maximizing the conditional probability of the intensity differences between two consecutive images, which were captured by a monocular video camera before and after the rover’s motion. The camera is supposed to be rigidly attached to the rover. The intensity differences are measured at observation points only that are points with high linear intensity gradients. It represents an alternative to traditionally stereo visual odometry algorithms, where the rover’s 3D motion is estimated by maximizing the conditional probability of the 3D correspondences between two sets of 3D feature point positions, which were obtained from two consecutive stereo image pairs that were captured by a stereo video camera before and after the rover’s motion. Experimental results with synthetic and real image sequences revealed highly accurate and reliable estimates, respectively. Additionally, it seems to be an excellent candidate for mobile robot missions where space, weight and power supply are really very limited.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
