Belgian SME providing solid-state LiDAR and sensor fusion technology for fail-operational autonomous vehicle perception systems.
XenomatiX is a Belgian technology SME specializing in solid-state LiDAR sensor technology and perception systems for highly automated and autonomous vehicles. Their core contribution to EU research projects is the development and integration of LiDAR and RADAR sensor fusion pipelines that enable vehicles to perceive their environment reliably enough to operate without human intervention. They focus specifically on fail-operational architectures — systems that continue functioning correctly even when individual components fail — which is the critical safety challenge separating prototype autonomy from deployable autonomy. In consortium projects, they bring industrial-grade sensor hardware and automotive-domain validation expertise that academic and Tier-1 partners typically lack.
NewControl (2019–2023) explicitly lists LIDAR as a core keyword, pointing to XenomatiX's role as a sensor technology provider in a cognitive perception and planning system for highly automated vehicles.
NewControl's keyword set — lidar, radar, fusion — signals that XenomatiX contributes multi-sensor data integration, not just single-modality sensing.
Both AutoDrive and NewControl target fail-operational designs; AutoDrive addresses fail-safe electronic components broadly, while NewControl applies that principle specifically to cognitive perception and control systems.
Every H2020 project XenomatiX joined is squarely in the automated driving domain, from electronic safety architectures in AutoDrive to full perception-planning-control integration in NewControl.
AutoDrive (2017–2020) focused on advancing fail-aware and fail-safe electronic components and system architectures, indicating hardware-level safety expertise beyond software perception.
XenomatiX entered H2020 through AutoDrive (2017), where the focus was broad: fail-aware and fail-safe electronic components and system architectures for automated vehicles — a foundational safety layer applicable across many hardware types. By NewControl (2019), their contribution had sharpened considerably: the project explicitly names LiDAR, RADAR, and sensor fusion, suggesting XenomatiX moved from general safety architecture toward their specific sensor product domain. The trajectory is one of increasing specialization — from contributing to the safety framework around autonomous vehicles to being a named technology provider for the perception layer that makes those vehicles see.
XenomatiX is moving toward being the LiDAR and perception specialist in automated driving consortia, making them a valuable industrial partner for any project requiring validated sensor hardware in a safety-critical, fail-operational context.
XenomatiX participates exclusively as a consortium partner — they have never coordinated an H2020 project — which is typical for technology SMEs that bring a specific product or capability rather than managing multi-partner research programs. Despite only two projects, they have accumulated 97 unique consortium partners across 17 countries, indicating they joined large, well-networked consortia (both AutoDrive and NewControl are flagship automated driving projects with many participants). This suggests they are sought out as a specialist hardware contributor, not a generalist partner.
XenomatiX has built a notably wide network for its size — 97 unique partners across 17 countries from just two projects — reflecting the large-consortium structure of flagship EU automated driving initiatives like AutoDrive and NewControl. Their connections span automotive OEMs, Tier-1 suppliers, research institutes, and universities across Europe.
XenomatiX occupies a rare intersection in EU research: a small Belgian company with deployable LiDAR hardware that meets automotive safety standards, operating in consortia otherwise dominated by large OEMs and research institutes. Where academic partners provide algorithms and car manufacturers provide platforms, XenomatiX provides the physical sensor layer — which means any consortium needing real LiDAR data in a fail-operational vehicle context has a concrete reason to include them. Their combination of SME agility and automotive-grade sensor technology makes them a practical bridge between research prototypes and producible systems.
