The aim of the EDDRIS project is to develop innovative design strategies for imaging systems. Today, most imaging systems consist of an optical system and digital processing. For the imaging system to be optimal (while respecting weight and power constraints), these two elements must be optimized at the same time. However, for these two parts of the imaging system to be jointly optimized, it is necessary to develop and use dedicated software, such as a differentiable ray tracer. In this way, the imaging characteristics (point spread function) taken into account in the digital processing are linked to the derivatives of the optical parameters (radius of curvature, thickness...). This makes possible to consider different digital processing algorithms, ranging from linear deconvolution to learning approaches. We therefore propose to use the ESCL-licensed FORMIDABLE differentiable ray tracer, and to develop an environment specifically dedicated to joint optical/processing design. In the course of the project, we will be looking at imaging systems of increasing complexity (using phase masks in the pupil of the optical device to modify the wavefront, then modifying a larger number of surfaces, possibly freeform). We will propose specific design strategies for the different types of processing envisaged, in line with the size, weight and power consumption constraints of the imaging system. A demonstrator dedicated to car driving will enable us to validate experimentally one of the strategies we have put in place.

With the increased impact of climate change and anthropogenic activities, one of the most critical vegetation ecosystem service is food supply in a context of worldwide population increase. The difficulty is how to combine a substantial food production, sustainable practices and a viable economy while remaining accessible to all. In orchards, agroecology aims at designing production systems relying on the functionalities offered by ecosystems by minimizing environmental pressures and preserving natural resources. Its reach can be broaden with the use of remote sensing data which brings a solution that is non-destructive, high-throughput and dynamic to assess vegetation condition on a large scale. By combining remote sensing and agroecology, the CANOP project wants to give innovative insights, first for tree health characterization against pests and diseases under contrasted managements (phytosanitary products reduction, controlled irrigation) and for different genotypes for a given management (resilient varieties breeding), and second for the optimization of an adapted use of fertilization. Actually, these tree-oriented applications require an appropriate observation scale. While most studies focus on intra- and inter-species variability, the CANOP project targets the leaf scale and the intra-individual variability within a tree canopy. From optical properties measured in the 0,4-2,5 µm spectral range, leaf biochemical traits can be retrieved such as pigments, water and dry matter content. They witness complex physiological processes such as photosynthesis, transpiration, nutrient allocation, growth rate and decomposition. At the tree scale, the objective of CANOP is to map this variability in leaf pigmentation, water stress and biomass. However, four major challenges arise when tackling the centimetric spatial resolution: (1) the anisotropic behavior of leaf optical properties, so far neglected for higher spatial resolutions, (2) the impact of the tree 3D geometry, dominated by leaf distribution and orientation which emphases multiple scattering effects, (3) the spatial upscaling from leaf to the tree and then the orchard from different remote sensing data (including satellite imagery), and (4) the difficulty to relate the biochemical traits with health/nutrition status values (qualitative/quantitative). To address these issues, the ambitiousness of the CANOP project is to combine active and passive optical remote sensing technologies (3D-LiDAR and imaging spectroscopy) with polarization from laboratory measurements and unmanned aerial vehicle acquisitions. Therefore, a large part of the work is dedicated to experiments, but also to data modelling between optical properties and leaf traits, and leaf traits and health/nutrition status. This includes methods from AI data-driven approaches and physics-based ones from the use of radiative transfer models, as well as new models development. Multi-scale robust methods are the key point for delivering tree health/nutrition maps with high estimation accuracies. The studied sites are apricot and peach orchards (3rd and 4th national rank for fruit production) managed by INRAE, respectively at UERI Gotheron near Valence and at Avignon as part of a national orchard network. Finally, the CANOP project is in line with the 4th program “Investing for the Future” (PIA4) funded by the government with two priority research program and equipment (PEPR), “Agroecology and digital” and “Genetics and varietal selection”, respectively co-led and led by INRAE. Thus, the CANOP results and products will have industrial impacts (ex: design of new close-range remote sensing platforms for variety breeding), agri-food societal and economic impacts (optimizing orchard management for better fruit growth and quality by reducing pesticides) thanks to a complete understanding of vegetation functioning with the powerful alliance of remote sensing, modelling and agroecology.

The EFAICTS project proposes to develop and integrate in Active Side-Stick Units (ASSU), optimised coupling and haptic functions for both Pilot/Co-pilot and Crew/Autopilot interactions. The concepts will be validated through modelling and evaluation on a simulation bench with experienced pilots. For dual pilot configuration, ASSU technology can provide intuitive tactile cueing in the cockpit — all resulting in increased situational awareness, safety and improved ergonomic, performance and opens a new mode of communication between the pilot and the co-pilot. In addition, with passive inceptors, the principal information transfer from the aircraft to the pilot still remains visual cueing or alarms. Through ASSU, haptic cueing is an efficient and intuitive communication mode with the crew. EFAICTS project proposes a Human-Centred Design approach, in which the end-users are at the heart of the development, from the beginning to the final evaluation phase. This approach will be applied in the four technical work packages about the flight scenarios definition and evaluation; the PF/PNF/AP interactions and transition phases definition; the specification and development of haptic feedbacks and ergonomic requirements; the evaluation of haptic feedback and ergonomic recommendations. The project will focus on a Tiltrotor aircraft and its specificities since operating as both rotary and fixed wing aircraft and as hybrids in the unique conversion corridor. The activities and proposed solutions will lead to situational awareness improvement, crew coordination, workload reduction, better performances and weight reduction. All these benefits will result in more competitive aeronautic Industry in Europe a safer and greener aeronautics transport. The proposed project is lead and conducted by the ONERA and will run over a period of 42 months, with a grant request is of 594,985€. EFAICTS will deliver a TRL6 level ASSU configurations optimised with intuitive coupling and haptic functio