Performance of optical flow techniques
International Journal of Computer Vision
Uncalibrated obstacle detection using normal flow
Machine Vision and Applications
3D environment modeling from multiple cylindrical panoramic images
Panoramic vision
Vision for Mobile Robot Navigation: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
Dominant plane detection from optical flow for robot navigation
Pattern Recognition Letters
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Estimation of ego-motion and obstacle depth detection plays an important role in environment recognition for navigation of mobile robots. In this paper obstacle perception is performed by using pattern matching between the planar flow and the normal optical flow observed by means of a monocular vision system installed on a mobile robot. The obstacle depth and robot velocity then can be estimated through the coordinate transformation between the image coordinate and the robot coordinate. An experiment is also performed under several different environment settings and shows a good performance for estimation of velocity and the obstacle depth for a mobile robot.