Modélisation géométrique et reconstruction de formes équipées de capteurs d'orientation (2013)

This PhD thesis in applied mathematics was conducted within the Electronic Systems andSensors department of the CEA-Leti (Atomic Energy and Alternative Energies Commission - Laboratory for Electronics and Information Technologies), a major organism for technological research located in Grenoble, France. This work originated from a partnership with the applied mathematics laboratory (LJK) of the Joseph Fourier university (UJF). The Leti develops embedded systems equiped with micro-sensors (magnetometers, accelerometers...) from which it is possible to retrieve informations about their spatial orientation. These systems allow for innovative applications in the field of shape acquisition and reconstruction. The problem of reconstructing surfaces from unstructured orientation data is ill-posed. However, previous work done within the Leti came up with a valid reconstruction protocol. The micro-sensors were integrated into the Morphosense ribbon : this flexible ribbon instrumented with sensor knots according to a known geometry is at the core of a number of reconstruction algorithms for the curves followed by the ribbon. When lied on a physical surface, Morphosense ribbons then allow the acquisition and reconstruction of a network of curves on the surface, that are then used for the reconstruction of the entire surface. We first propose new algorithms for curve reconstruction thanks to the Morphosense ribbon. Those new methods now integrate the orientation informations provided by the sensors in their entirety, as well as the mechanical properties of the ribbon that force it to follow geodesic curves on a surface. From this point of view, the curve reconstruction can be considered optimal, as it integrates all the information embedded in the ribbons' structure. We then study a set of methods for the reconstruction of surfaces using a network of ribbon curves. Such a network generally leads to problems linked to the closure of the network and missing data estimation. The closure of the network is essentially a numerical problem related to differential constraints. The missing data corresponds to the lack of information on the surface outside the network of curves. In order to deal with these problems and propose practical solutions for the reconstruction, hypotheses either on the surface models or the topology of the network of curves are required. Therefore, the developed methods fall within the two following approaches.– On the one hand, reconstruction methods for developable and quasi-developable surfaces, which are a good approximation for the surfaces considered in numerous applications.– On the other hand, reconstruction methods from networks of curves with specific topologies (quasi-planar curves, open network) so as to deal with the closure problem.The set of methods developed in this work allow to formulate a global process for the reconstruction of surfaces, with flexible algorithms adapting to the different practical situations, so as to propose a solution both simple and precise in each case. The validation of our results in the case of real sensors data provided by the Morphosense ribbons also led us to develop metrological device. Finally, notice that the general context of reconstruction from orientation data studied here raises original theorical problems, to which we tried to answer with innovative solutions through interpolation and optimization algorithms.