The MOCA project is dedicated to the study of thin films single crystals from the perovskite family obtained on Silicon substrate by epitaxial routes. The materials developed will be Pb(Zr,Ti)O3 (PZT) with Zr/Ti=52/48 and (Ba,Sr)TiO3 (BST) with Ba/Sr=70/30. Three different deposition techniques will be performed: Molecular Beam Epitaxy (MBE), sol gel and Pulsed Laser Deposition (PLD). The targeted proofs of concept are three fold: acoustic resonators, high-K capacitors and piezoelectric actuators. The final aim of MOCA is to provide a clear status on the superiority of the epitaxial single crystal thin films compared to their polycrystalline counterpart. Four partners will be involved in MOCA. CEA LETI Minatec will be the leader of the project and will process the sol gel layers (PZT and BST) deposited on SrTiO3 (STO) buffered layers, which is mandatory to obtain single crystals on Si. LETI will also realise several proof of concepts devices: resonators with FEMTO, capacitors and piezoelectric or electrostrictive actuators. He will characterize these devices. INL will bring his expertise on MBE to the consortium. He will prepare the template Si wafers with the STO layer and will work specifically on this template layer. He will also prepare BST active layers in order to compare their properties to the one obtained with the other techniques. A demonstrator will be done by the partners (actuators or/and resonators). INL will provide the template layers to the partners. SPMS will work on the PLD route as it is also a recognized way to obtain single crystals as thin films. He will also help the consortium to characterize the structural behaviour of the layers deposited. FEMTO will realize resonators and characterize them. The consortium is very complementary on this dedicated topic of perovskite single crystal on Si. Finally, ST Tours, industrial with a long experience of integrating PZT capacitors with Si, will elaborate specifications and will test the capacitors based on single crystals perovskite in the framework of the MOCA project. The partners have already several common projects and developed the know-how to work together for a long time.

Intelligent vision systems are more and more important in a lot of applications nowadays, ranging from security at home, in cars, navigation of drones and robots, … but their practical applicability is still limited by the large computing system they require. The IRIS project exhibits three facets. The first facet opens a new way by proposing new bio-inspired algorithms for the realization of a stand-alone vision chip for both optic flow (retinal slip speed) measurement and contrasting target localization over a wide luminance range. New algorithms are required because classical algorithms are efficient, but require a large amount of computation (and power) that limit their usability in such applications. Insect-based vision is not used in mainstream applications (pattern recognition, image recording) because it has comparatively lower resolution than vertebrate vision but it evolved to support accurate control of navigation in complex, 3D, dynamic environments. More than fifty years of insect research indicate that it is extremely efficient to detect motion-related events that occur when the animal moves in 3D space. In this project, we propose to design and realize innovative algorithms adapted to the new class of 3D vision chip with 3 stacked layers: perceptive, pre-processing and computing layers. Many studies in robotic field and insect behavior have highlighted the key role of optic flow measurement for visual navigation. Recent studies carried out at ISM in Marseille (Biorobotic department) have shown that robust optic flow measurement can be achieved by merging the output signal of a few number of insect-based motion detectors. This result combined with a technology of vertically integrated retina using 3D-stacking technology (developed by CEA), opens a promising avenue toward the implementation of fast and smart retina featuring a high fill factor, low power consumption, high flexibility and large computational resource without sacrificing the size of the overall chip. This first IRIS facet will involve ISM, LEAD, CEA-LIST and the industrial partner Novadem to determine the specifications of a new vision chip with unique features in terms of size, programmability and computational resources. The second facet will be focused on the development of new visual processing algorithms for motion detection and object localization. These last ten years, many studies on primate visual cortex yielded novel bio-inspired models concerning rapid object categorization and recognition. The second objective of the IRIS project will aim at combining bio-inspired object categorization algorithms (extension of HMAX that will work robustly in the presence of complex scenes and developed by LEAD) with optic flow processing (developed by ISM) in order to improve the performance of the visual processing to detect and track a moving object of interest. This second facet will include a crucial benchmarking of the selected visual processing algorithms that will be implemented into the IRIS processors. The third facet takes its place at the crossroad between the design of a novel vision chip and the use of novel control laws for the visual guidance of an aerial vehicle. Among an increasing number of flying robotic platforms, achieving collision-free vision-based piloting in cluttered indoor and outdoor environments is still a tricky challenge, even with relative large computational resources such as those offered by the IRIS sensor. Much research efforts must be deployed for the use of vision to tackle the problems involved in vital tasks and swift decisional tasks such as obstacle avoidance, odometry and path planning. It is precisely the main objective of this third facet to combine innovative visual sensors with insect-based control laws to improve the ability of future aerial vehicles (provided by Novadem) to avoid obstacles or track moving target in a natural world indoors or outdoors.