G.L. Mariottini, S. Scheggi, F. Morbidi, D. Prattichizzo. An Accurate and Robust Visual-Compass Algorithm for Robot-mounted Omnidirectional Cameras. Robotics and Autonomous Systems, Elsevier, 60(9):1179-1190, 2012.
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Due to their wide field of view, omnidirectional cameras are becoming ubiquitous in many mobile robotic applications. A challenging problem consists of using these sensors, mounted on mobile robotic platforms, as visual compasses (VCs) to provide an estimate of the rotational motion of the camera/robot from the omnidirectional video stream. Existing VC algorithms suffer from some practical limitations, since they require the precise knowledge either of the camera-calibration parameters, or the 3-D geometry of the observed scene. In this paper we present a novel multiple-view geometry constraint for paracatadiotpric views of lines in 3D, that we use to design a VC algorithm that does not require either the knowledge of the camera calibration parameters, or the 3-D scene geometry. In addition, our VC algorithm runs in real time since it relies on a closed-form estimate of the camera/robot rotation, and can address the image- feature correspondence problem. Extensive simulations and experiments with real robots have been performed to show the accuracy and robustness of the proposed method
[ Vision ] [ Panoramic cameras ]
@article{MaScMoPr-RAS2012,
Author = {Mariottini, G.L. and Scheggi, S. and Morbidi, F. and Prattichizzo, D.},
Title = {An Accurate and Robust Visual-Compass Algorithm for Robot-mounted Omnidirectional Cameras},
Journal = {{Robotics and Autonomous Systems, Elsevier}},
Volume = {60},
Number = {9},
Pages = {1179--1190},
Year = {2012}
}
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