Swissphotonics’ Post

🚀 Ommatidia LIDAR is now a proud member of Asociación Española de la Industria de Semiconductores - AESEMI.   Ommatidia LIDAR leads the way in the development of LiDAR and 3D metrology sensors, harnessing the capabilities of integrated photonics. Their LiDAR products, driven by proprietary technology inspired by the compound eyes of insects, offer faster, more accurate, and longer-range 3D imaging. Mimicking insect eyes, Ommatidia LIDAR products use an array of individual elements to sample reflected light from the scene being captured. This bioinspired architecture enables continuous wide-beam illumination, allowing for the safe use of high-power illumination in 3D imaging for the first time. Paired with photonic sensitivity, it delivers exceptional performance.   Asociación Española de la Industria de Semiconductores - AESEMI, representing leading Spanish companies in microelectronic design and semiconductor manufacturing, is glad to welcome Ommatidia LIDAR into its fold. The association aims to elevate the entire semiconductor ecosystem in Spain on both national and international fronts.   With Ommatidia LIDAR's addition, Asociación Española de la Industria de Semiconductores - AESEMI reaffirms its commitment to unite and strengthen the Spanish semiconductor ecosystem. Ommatidia LIDAR plays a role in developing lidar sensors and optics for 3D characterization across diverse sectors, including civil engineering, energy, aerospace, robotics, and autonomous mobility.   Exciting collaborations lie ahead as we embark on this journey together to push the boundaries of technology and innovation! 💡🌐 #OmmatidiaLiDAR #AESEMI #IntegratedPhotonics #LiDAR #Semiconductors #Innovation #TechnologyLeadership #ANTLIDAR

Do you already know the benefits of the TRUMPF VCSEL? Our #VSCEL is small and robust. It shows solid performance over a wide temperature range, from -40 to 120 degrees. Another advantage is that the VCSEL is robust against back reflections in the facet. High-tech applications for our VCSEL are for example 3D sensor technology, LiDAR or optical data communication. Find out more here: https://bit.ly/3tGha9M #photonics

The importance of vision technology in applications ranging from AR/VR to robotics.

Announced at #GTC24, NVIDIA Isaac Perceptor, optimized on Jetson Orin, uses multiple cameras for 3D surround perception to detect hazards invisible to standard 2D lidar. Using robust AI-based depth estimation, GPU-accelerated 3D reconstruction, and semantic segmentation, see how a mobile robot can work more safely alongside humans.

🌟 Friday = an exciting new weekend read! 🌟 This week, we're spotlighting the innovative work of Scantinel Photonics, a global leader in LiDAR sensor technology. Scantinel Photonics has reinforced its position with the introduction of its next-generation Photonic Single Chip, based on standard CMOS technology. This new PIC features a fully integrated, massively parallel detector system for coherent LiDAR. Recently tested at Scantinel, the chip demonstrated a significant improvement in signal-to-noise ratio, about 20dB better than previous solid-state LiDAR scanners. Designed for automotive LiDAR applications, the scanner-detector chip is a fully integrated, automotive-ready device. It includes a photonic chip and a low-noise electronics board. With enhanced SNR, the system has achieved a tenfold reduction in LiDAR power consumption, enabling faster pixel rates. Unlike market systems using proprietary technology or two-mirror scanners, this generation leverages the full advantages of FMCW technology over existing TOF LiDAR systems. The PIC production has been fully transferred to high-volume standard CMOS fabrication, showcasing the advanced maturity of Scantinel’s technology. For more details, click here: https://bit.ly/45YSfB7 #ScantinelPhotonics #LiDAR #PhotonicChips #Innovation #TechNews #AutomotiveTech

📊 Technology, process, and cost - GaAs Multi-Junction VCSEL from Lumentum and OSRAM Yole SystemPlus found multi-junction VCSELs in two #automotive LiDARs, the Velodyne H800 and in the Hesai Technology AT128. The two LiDARs are very different: for the Hesai, each Lumentum’s #VCSEL die generates one point/channel of the far-field LiDAR and the Velodyne or the ams OSRAM’s VCSEL dies are combined to illuminate the scene in a flash. Lumentum and ams OSRAM have developed a very different VCSEL structure dedicated to two different LiDAR technologies with very different beam diffusion and wideband diffusion needs. This report conducts a detailed physical analysis, including #teardown of the two LiDAR, cross-sectional analysis, circuit delayering, and scanning electron microscopy for the VCSEL dies from Lumentum and ams Osram. 👉 Read more https://lnkd.in/exBpRAzR

📃Scientific paper: Application of Image Fusion Algorithm Combined with Visual Saliency in Target Extraction of Reflective Tomography Lidar Image Abstract: Reflective tomography Lidar has been proved to be a new Lidar system with long distance and high resolution. The reflective tomography Lidar image is prone to clutter and artifacts; thus, it is important for space target recognition to extract the target from the image. In this study, we proposed image fusion algorithm combined with visual saliency could be applied to the target extraction of reflective tomography Lidar image, which can not only preserve the target information but also eliminate the clutter and artifacts in the image. The efficiency of this algorithm is shown by simulation and the experiment of the reflective tomography Lidar system. Also, we analyzed the main source of reflective tomography Lidar image artifacts and the reason why this algorithm could remove clutter and artifacts. Continued on ES/IODE ➡️ https://etcse.fr/ZGwJP ------- If you find this interesting, feel free to follow, comment and share. We need your help to enhance our visibility, so that our platform continues to serve you.

Check out this Simulation Platform for sensors simulation course. https://lnkd.in/djm_AxT2 This course is designed to approach simulation-driven development of highly automated systems from both a latest and a future technology perspective. The course builds on standardization projects such as ASAM OpenX and covers software approaches to simplify participants' entry into the technology area. Learn how to simulate Radar , Camera and Lidar sensors for autonomous systems using SimX simulator. Learn to detect obstacles in lidar point clouds through clustering and segmentation, apply thresholds and filters to radar data. Process raw lidar data using Velodyne sensors with filtering, segmentation, and clustering to detect other vehicles on the road. Analyze radar signatures to detect and track objects. Calculate velocity and orientation by correcting for radial velocity distortions, noise, and occlusion.

Announced at #GTC24, NVIDIA Isaac Perceptor, optimized on Jetson Orin, uses multiple cameras for 3D surround perception to detect hazards invisible to standard 2D lidar. Using robust AI-based depth estimation, GPU-accelerated 3D reconstruction, and semantic segmentation, see how a mobile robot can work more safely alongside humans.

Announced at #GTC24, NVIDIA Isaac Perceptor, optimized on Jetson Orin, uses multiple cameras for 3D surround perception to detect hazards invisible to standard 2D lidar. Using robust AI-based depth estimation, GPU-accelerated 3D reconstruction, and semantic segmentation, see how a mobile robot can work more safely alongside humans.