Conference Paper

Outdoor visual path following experiments

IRISA/NRIA, Rennes
DOI: 10.1109/IROS.2007.4399247 Conference: 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, October 29 - November 2, 2007, Sheraton Hotel and Marina, San Diego, California, USA
Source: DBLP

ABSTRACT In this paper the performance of a topological- metric visual path following framework is investigated in different environments. The framework relies on a monocular camera as the only sensing modality. The path is represented as a series of reference images such that each neighboring pair contains a number of common landmarks. Local 3D geometries are reconstructed between the neighboring reference images in order to achieve fast feature prediction which allows the recovery from tracking failures. During navigation the robot is controlled using image-based visual servoing. The experiments show that the framework is robust against moving objects and moderate illumination changes. It is also shown that the system is capable of on-line path learning.

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Available from: François Chaumette, Aug 18, 2015
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    • "En termes d'asservissement visuel, cela revientà ce que les informations visuelles restent au sein d'un intervalle, au lieu qu'elles atteignent des valeurs spécifiques. L'application de cette approche pour la navigation d'un Cycab est décrite dans [23] "
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    • "In our proposal, the visual servoing problem is transformed in a reference tracking problem for the selected tensor element. It avoids the recurrent problem of discontinuous rotational velocity at key image switching of image-based schemes [6], [7], [8]. The use of the TT allows the gathering of many visual features into a single measurement, so that, undesired pseudoinverse of matrices is not needed. "
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    ABSTRACT: In this paper, we present a control scheme for visual path-following of wheeled mobile robots based on a robust geometric constraint: the trifocal tensor (TT). The proposed control law only needs one element of the TT as feedback information, which is computed from the current and the target images along the sequence of the visual path. The scheme is valid for images captured by cameras having approximately a unique center of projection, e.g., conventional, central catadioptric and some fisheye cameras. The benefits of the proposed scheme are that explicit pose parameters decomposition is not required and the rotational velocity is smooth or eventually piece-wise constant avoiding discontinuities that generally appear when a new target image must be reached. Additionally, the translational velocity is adapted as required for the path. The validity and performance of the approach is shown through realistic simulations using synthetic images.
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    • "The contribution of this paper, based on [12] 1 , is the application of the vision system to a robotic vehicle using an image-based visual servoing strategy and the experimental exploration of the implementation's limits 2 . Experiments were carried out mostly on roads using an autonomous electric vehicle capable of carrying two passengers. "
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    ABSTRACT: In this paper, the performance of a topological-metric visual-path-following framework is investigated in different environments. The framework relies on a monocular camera as the only sensing modality. The path is represented as a series of reference images such that each neighboring pair contains a number of common landmarks. Local 3-D geometries are reconstructed between the neighboring reference images to achieve fast feature prediction. This condition allows recovery from tracking failures. During navigation, the robot is controlled using image-based visual servoing. The focus of this paper is on the results from a number of experiments that were conducted in different environments, lighting conditions, and seasons. The experiments with a robot car show that the framework is robust to moving objects and moderate illumination changes. It is also shown that the system is capable of online path learning.
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