Miniaturized, yet highly sensitive and fast LiDAR systems serve market demands for their use on platforms ranging from robots, drones, and autonomous vehicles (cars, trains, boats, etc.) that are mostly used in complex environments. The widespread use of high performance LiDAR tools faces a need for cost and size reduction. A key component of a LiDAR system is the light source. Very few laser light sources exist that provide sufficient performance to achieve the required distance range, distance resolution and velocity accuracy of the emerging applications identified in LiDAR roadmaps. The available sources, namely single mode or multimode laser diodes and fiber lasers, are either very costly, not sufficiently robust or not compact enough. In OPHELLIA, we will investigate advanced materials and integration technologies directed to produce novel PIC building blocks, namely high gain, high output power (booster) amplifiers and on-chip isolators that are not yet available in a PIC format with the required performance. The novel building blocks will be monolithically integrated onto the Si3N4 generic photonic platform to produce high performance laser sources with unprecedented high coherence and high power, which will have a profound impact on the performance of the systems. Advanced packaging will further contribute to a dramatic reduction of the overall cost. To achieve this ambitious goal, OPHELLIA will leverage the expertise of its consortium members, ranging from materials, integration technologies and PIC design to packaging and LiDAR systems integration, which covers the full chain from innovation to the deployment of the technology in a relevant environment. The successful realization of OPHELLIA will not only represent a milestone towards the widespread utilization of LiDAR systems, but the developed building blocks will also have an enormous impact in other emerging application fields such as datacom/telecom, sensing/spectroscopy and quantum technology.

Today’s driver assistance systems offer comfort and safety in sound environmental conditions. However, in harsh environment conditions – when needed most – systems stop working due to reduced sensor information quality. Targeting to the area of highly automated driving the improvement of perception, decision and planning under adverse conditions is one of the main challenges to be addressed. RobustSENSE is a project aiming at automated and safe mobility. Its goal is making systems able to cope with real world requirements under all environmental conditions. The RobustSENSE system introduces reliable, secure and trustable sensors and software by implementing self-diagnosis, adaptation and robustness. By managing diversity, complexity and safety it increases yield, robustness and reliability. RobustSENSE develops metrics to measures sensor system reliability on every level of assistance and automation systems as well as investigate approaches to improve the system. RobustSENSE thus aims at enhancing the robustness of all sensing methods and algorithms required for advanced driver assistance systems and automated driving. RobustSENSE moves from a platform consisting of several independent subsystems to a holistic approach. RobustSENSE introduces both, reliability measures and self monitoring across all levels of the system allowing two things: 1) Taking appropriate actions and algorithms on the respective system level to react on performance reduction caused by technical failure or changing environment conditions and 2) propagating reliability measures to a higher system level for decision making and taking appropriate actions therein. Thus, the area of operation of highly automated driving functions is permanently adapted to the present available performance of the perception and decision making system in order to guarantee a safe driving status at any time.

Zero-SWARM is a mission to achieve climate neutral and digitised production via a multidisciplinary, human centric, objective oriented innovative approach resulting in technical solutions for open swarm framework, non-public 5G network, active information continuum and digital twin. At the core, it establishes a unique forum where separately maturing technologies of 5G and cloud-edge continuum, data technologies and analysis (including data spaces and GAIA-X) and operational technology (automation and agility) break their siloes to co-design and co-create through 10 trials. It will showcase key achievements such as smart assembly, sustainable powertrains, improved resilience with remote operation, 5G powered PLC?s for real time distributed control systems, safe and autonomous transport of goods in factory, 5G enabled process aware AGVs, plug & connect 5G for industry, mobile intelligent agents for zero plastic waste, smart maintenance and optimization, remote quality control for zero defect resilient manufacturing. The project includes 3 nodes (north, center and south) with industrial test facilities from previous public/private investments co/creating with reputable industry players. Aligned with the technical activities, Zero-SWARM includes a tailored engagement program towards a wide audience, including collaboration with Digital Innovation Hubs and key initiatives in Europe. In addition, open innovation practices involves industry player as clients of developed technologies via Zero-SWARM community with 400 users and the expression of interest mechanism. It allows them to be the pioneer of the Zero-SWARM technologies, establishing an impact pathway even after the project end. Zero-SWARM puts strong emphasis on developing various learning materials to promote skill development of talented workforces with minimum efforts in prominent twin transformation, which will strongly contribute to build up European leadership in sustainable data driven manufacturing.