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Lafont F.,University of Toulon | Busvelle E.,CNRS Laboratory of Electronics Informatics and Images | Gauthier J.-P.,University of Toulon
Journal of Process Control | Year: 2011

The purpose of this paper is twofold: (1) we apply the adaptive observer developed in Boizot et al. [1] to a wastewater system, following two cascade steps. First, we apply it to a simplified model of the system. Second, we use this "simplified" estimation as a measurement for the full system. (2) Although the observability analysis is trivial, the equations contain rather complicated terms. Therefore, it is not reasonable to change coordinates for those of the required observability canonical form. Hence, we have to establish and work with the "unusual" equations of the observer in natural coordinates. Let us point out that the simulations are done taking into account the small number of measurements (three) available in practice. © 2011 Elsevier Ltd. All rights reserved.

Ait-Aoudia S.,National School in Computer Science | Foufou S.,CNRS Laboratory of Electronics Informatics and Images
Advances in Engineering Software | Year: 2010

Modeling by constraints enables users to describe shapes by specifying relationships between geometric elements. These relationships are called constraints. A constraint solver derives then automatically the design intended by exploiting these constraints. The constraints solvers can be classified in four categories: symbolic, numerical, rule-oriented and graph-constructive solvers. The graph constructive approach is widely used in recent Computer Aided Design (CAD) systems. In this paper, we present a decomposition-recombination (DR) planning algorithm, called S-DR, that uses a graph reduction method to solve systems of 2D geometric constraints. Based on the key concept of skeletons, S-DR planner figures out a plan for decomposing a well constrained system into small sub-systems and recombines the solutions of these sub-systems to derive the solution of the entire system.

Koon K.T.V.,University Claude Bernard Lyon 1 | Marquie P.,CNRS Laboratory of Electronics Informatics and Images | Dinda P.T.,Laboratory Interdisciplinaire Carnot de Bourgogne
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2014

We address the problem of supratransmission of waves in a discrete nonlinear system, driven at one end by a periodic excitation at a frequency lying above the phonon band edge. In an experimental electrical transmission line made of 200 inductance-capacitance LC cells, we establish the existence of a voltage threshold for a supratransmission enabling the generation and propagation of cut-off solitons within the line. The decisive role of modulational instability in the onset and development of the process of generation of cut-off solitons is clearly highlighted. The phenomenon of dissipation is identified as being particularly harmful for the soliton generation, but we show that its impact can be managed by a proper choice of the amplitude of the voltage excitation of the system. © 2014 American Physical Society.

Bazin J.-C.,University of Tokyo | Demonceaux C.,CNRS Laboratory of Electronics Informatics and Images | Vasseur P.,CNRS Informatics Systems Laboratory | Kweon I.,KAIST
International Journal of Robotics Research | Year: 2012

Rotation estimation is a fundamental step for various robotic applications such as automatic control of ground/aerial vehicles, motion estimation and 3D reconstruction. However it is now well established that traditional navigation equipments, such as global positioning systems (GPSs) or inertial measurement units (IMUs), suffer from several disadvantages. Hence, some vision-based works have been proposed recently. Whereas interesting results can be obtained, the existing methods have non-negligible limitations such as a difficult feature matching (e.g. repeated textures, blur or illumination changes) and a high computational cost (e.g. analyze in the frequency domain). Moreover, most of them utilize conventional perspective cameras and thus have a limited field of view. In order to overcome these limitations, in this paper we present a novel rotation estimation approach based on the extraction of vanishing points in omnidirectional images. The first advantage is that our rotation estimation is decoupled from the translation computation, which accelerates the execution time and results in a better control solution. This is made possible by our complete framework dedicated to omnidirectional vision, whereas conventional vision has a rotation/translation ambiguity. Second, we propose a top-down approach which maintains the important constraint of vanishing point orthogonality by inverting the problem: instead of performing a difficult line clustering preliminary step, we directly search for the orthogonal vanishing points. Finally, experimental results on various data sets for diverse robotic applications have demonstrated that our novel framework is accurate, robust, maintains the orthogonality of the vanishing points and can run in real-time. © SAGE Publications 2011.

Bazin J.-C.,ETH Zurich | Li H.,Australian National University | Kweon I.S.,KAIST | Demonceaux C.,CNRS Laboratory of Electronics Informatics and Images | And 2 more authors.
IEEE Transactions on Pattern Analysis and Machine Intelligence | Year: 2013

Data correspondence/grouping under an unknown parametric model is a fundamental topic in computer vision. Finding feature correspondences between two images is probably the most popular application of this research field, and is the main motivation of our work. It is a key ingredient for a wide range of vision tasks, including three-dimensional reconstruction and object recognition. Existing feature correspondence methods are based on either local appearance similarity or global geometric consistency or a combination of both in some heuristic manner. None of these methods is fully satisfactory, especially in the presence of repetitive image textures or mismatches. In this paper, we present a new algorithm that combines the benefits of both appearance-based and geometry-based methods and mathematically guarantees a global optimization. Our algorithm accepts the two sets of features extracted from two images as input, and outputs the feature correspondences with the largest number of inliers, which verify both the appearance similarity and geometric constraints. Specifically, we formulate the problem as a mixed integer program and solve it efficiently by a series of linear programs via a branch-and-bound procedure. We subsequently generalize our framework in the context of data correspondence/grouping under an unknown parametric model and show it can be applied to certain classes of computer vision problems. Our algorithm has been validated successfully on synthesized data and challenging real images. © 1979-2012 IEEE.

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