Abstract: A method for locating a vehicle, including at least one vision sensor and at least one item of equipment from among an inertial navigation unit, a satellite navigation module and an odometry sensor. The method including carrying out vision-localization from image data supplied by the at least one vision sensor, to produce first location data, and applying a Bayesian filtering via a Kalman filter, taking into account the first location data, to the data derived from the at least one item of equipment and the data from a scene model, to produce second data for locating the vehicle.

Abstract: A method for geo-localizing a carrier, comprises: acquiring a plurality of shots of the environment of the carrier; determining at least one datum relating to the position of the carrier for a set of shots; generating a virtual reconstruction of the environment from the shots of the set, from the positional data and from a measurement bias parameter for each position, the virtual reconstruction being parameterized depending on the measurement bias; and modifying the measurement bias parameter to be applied at each position to obtain a virtual reconstruction parameterized by a modified measurement bias, the modification being carried out so as to minimize the distance between the modified virtual reconstruction and an a priori virtual representation of the environment.

Abstract: A method for locating a camera and 3D reconstruction of its static environment, comprising an object of interest, the 3D model of which is known, includes: calculating an initial pose of the camera in the environment and an initial reconstruction; calculating the pose of the camera for each new image by pairing 3D primitives of the environment with 2D primitives of said image and reconstructing 3D primitives of the environment by triangulation; and simultaneously optimizing the poses of the camera and 3D primitives by minimizing a reprojection error over a plurality of images. The 3D model is a geometric description of the object of interest, the reprojection error has only two types of terms, a first type associated with primitives constrained by the 3D model and a second type associated with primitives of the environment other than the object, the optimization associating the primitives with the environment or 3D model.

Abstract: A method for locating a camera and 3D reconstruction of its static environment, comprising an object of interest, the 3D model of which is known, includes: calculating an initial pose of the camera in the environment and an initial reconstruction; calculating the pose of the camera for each new image by pairing 3D primitives of the environment with 2D primitives of said image and reconstructing 3D primitives of the environment by triangulation; and simultaneously optimizing the poses of the camera and 3D primitives by minimizing a reprojection error over a plurality of images. The 3D model is a geometric description of the object of interest, the reprojection error has only two types of terms, a first type associated with primitives constrained by the 3D model and a second type associated with primitives of the environment other than the object, the optimization associating the primitives with the environment or 3D model.

Abstract: The method for configuring a network of deposited wireless sensors. In certain aspects, these methods include defining performance criteria forming constraints, with associated threshold values, and at least one performance criterion to be optimized, for at least one zone to be equipped with nodes, each performance criterion being defined by a model; defining for said or each zone; the allocation to said or each zone to be equipped, a number of nodes; applying an optimization process per zone on said or each zone; increasing the number of nodes or modifying the performance criteria defined in said or each zone where the performance criteria are not met and reproducing in these zones the optimization process per zone with the new number of nodes or the new performance criteria, and applying the configuration determined at each node in said or each zone.

Abstract: The method for configuring a network of deposited wireless sensors. In certain aspects, these methods include defining performance criteria forming constraints, with associated threshold values, and at least one performance criterion to be optimized, for at least one zone to be equipped with nodes, each performance criterion being defined by a model; defining for said or each zone; the allocation to said or each zone to be equipped, a number of nodes; applying an optimization process per zone on said or each zone; increasing the number of nodes or modifying the performance criteria defined in said or each zone where the performance criteria are not met and reproducing in these zones the optimization process per zone with the new number of nodes or the new performance criteria, and applying the configuration determined at each node in said or each zone.