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• W1540984957 abstract "It is generally accepted that machine vision is one of the most important sensory modalities for navigation purposes. Visual control, also called visual servoing, is a very extensive and mature field of research where many important contributions have been presented in the last decade [Malis et al.,1999, Corke and Hutchinson, 2001, Conticelli and Allotta, 2001, Tsakiris et al., 1998, Ma et al., 1999]. Two interesting surveys on this topic are [De Souza and Kak, 2002] and [Hutchinson et al., 1996]. In this work we present a new visual servoing approach for mobile robots with a fixed monocular system on board. The idea of visual servoing is used here in the sense of homing, where the desired robot position is defined by a target image taken at that position. Using the images taken during the navigation the robot is led to the target. A traditional approach is to perform the motion by using the epipolar geometry [Basri et al., 1999, Rives, 2000, Lopez-Nicolas et al., 2006]. These approaches have as drawback that the estimation of the epipolar geometry becomes ill conditioned with short baseline or planar scenes, which are usual in human environments. A natural way to overcome this problem is using the homography model. In [Malis and Chaumette, 2000] it is proposed a method based on the estimation of the homography matrix related to a virtual plane attached to an object. This method provides a more stable estimation when the epipolar geometry degenerates. In [Benhimane et al., 2005] it is presented a visual tracking system for car platooning by estimating the homography between a selected reference template attached to the leading vehicle. A significant issue with monocular camera-based vision systems is the lack of depth information. In [Fang et al., 2005] it is proposed the asymptotic regulation of the position and orientation of a mobile robot by exploiting homography-based visual servo control strategies, where the unknown time-varying depth information is related to a constant depth-related parameter. These homography-based methods usually require the homography decomposition, which is not a trivial issue. Two examples of approaches which do not use the decomposition of the homography are [Sagues and Guerrero, 2005] which is based on a 2D homography and [Benhimane and Malis, 2006] which presents an uncalibrated approach for manipulators. We present a novel homography-based approach by performing the control directly on the" @default.
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• W1540984957 date "2007-06-01" @default.
• W1540984957 modified "2023-09-25" @default.
• W1540984957 title "Shortest Path Homography-Based Visual Control for Differential Drive Robots" @default.
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• W1540984957 doi "https://doi.org/10.5772/5007" @default.
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