Articles tagged with "machine-vision"
IDS Imaging adds Sony Starvis 2 sensors to GigE uEye LE series
IDS Imaging Development Systems GmbH is set to expand its GigE uEye LE series of project cameras by introducing models equipped with Sony Starvis 2 sensors by the end of June 2025. These new single-board cameras, compliant with GigE Vision standards, are designed for high-volume, cost-sensitive industrial applications such as quality assurance, medical technology, and automation. The Starvis 2 sensors, based on CMOS technology, offer enhanced light sensitivity, reduced noise, and extended dynamic range, enabling consistent high-quality imaging even in low-light environments. The new camera models will feature sensor options including the IMX675 (5 MP), IMX676 (12.5 MP), and IMX678 (8 MP), with the 12.5 MP IMX676 sensor particularly suited for applications like microscopy due to its square 1/1.6″ sensor format. IDS emphasizes that these cameras maintain the GigE uEye LE family’s design-to-cost philosophy, making them suitable for integration into
robotindustrial-automationmachine-visionCMOS-sensorsimage-processingembedded-systemsquality-assurancePerovskite image sensor triples light capture, sharpens resolution
Researchers at ETH Zurich and Empa in Switzerland have developed a novel perovskite-based image sensor that significantly outperforms traditional silicon sensors in light sensitivity, resolution, and color accuracy. Unlike conventional sensors that rely on color filters—resulting in substantial light loss by capturing only about one-third of incoming photons per pixel—the new sensor uses stacked layers of lead halide perovskite crystals. Each layer is chemically tuned to absorb a specific wavelength (red, green, or blue) without filters, enabling each pixel to capture the full spectrum of light. This design allows the sensor to capture up to three times more light and achieve three times greater spatial resolution than current silicon-based sensors. The perovskite sensor’s tunability comes from adjusting the chemical composition of the crystals, specifically the ratios of iodine, bromine, and chlorine ions, to target different colors. This approach not only enhances image clarity and color precision but also reduces digital artifacts. The researchers have successfully miniaturized the technology
materialsperovskiteimage-sensorlight-capturesemiconductormachine-visiondigital-photographyReservoir Farms opens applications for inaugural cohort - The Robot Report
Reservoir Farms, an agricultural technology incubator located in California’s Salinas Valley, has opened applications for its inaugural cohort of 12 startups. The incubator aims to accelerate innovation in specialty crop production by connecting AgTech startups with growers, leveraging the expertise and network of the Western Growers Association’s 2,500 members. Supported by the Western Growers Association and established through a long-term lease with the Tanimura family and Tanimura & Antle, Reservoir Farms offers office and shop space, secure storage, and year-round test fields near some of the world’s most productive farmland in Salinas. The incubator provides startups with access to a fully equipped maker space featuring machine tools, welders, CNC routers, and 3D printers to facilitate rapid prototyping and in-field testing of robotic solutions. Focus areas include robotic harvesting, rugged mobility, machine vision, lightweight end effectors, modular field robotics, edge AI, and precision soil analytics. Reservoir Farms emphasizes a collaborative approach,
robotagroboticsagriculture-technologyprecision-farmingmachine-visionedge-AIrobotic-harvestingOxipital AI and Schmalz extend partnership for automated picking - The Robot Report
Oxipital AI and J. Schmalz GmbH have extended their partnership to integrate Oxipital AI’s advanced machine vision technology with Schmalz’s mGrip robotic fingers and vacuum end-of-arm tooling (EOAT). This collaboration aims to deliver next-generation robotic grasping solutions that improve operational efficiency, reduce labor dependence, and ensure consistent, safe, and profitable production, particularly in the food and beverage industry. Oxipital AI, originally founded as Soft Robotics, has shifted its focus from soft robotic grippers to AI-enabled machine vision systems, exemplified by its recent release of the VX2 Vision System designed for food-grade inspection and picking. Schmalz, a global leader in vacuum industrial automation and ergonomic material handling since 1910, benefits from this partnership by expanding the applicability of its tooling solutions to more complex manufacturing processes. The integration of Oxipital AI’s vision technology enhances Schmalz’s robotic grasping capabilities, enabling more capable and higher-performing picking solutions. Both companies emphasize their shared focus on robotic automation and digitalization, with Schmalz leveraging acquisitions and new technologies to strengthen its offerings in packaging, food, and pharmaceutical industries. The partnership was highlighted at the recent Automate event, signaling ongoing collaboration and innovation in automated picking systems.
roboticsartificial-intelligencemachine-visionrobotic-pickingautomationend-of-arm-toolingindustrial-roboticsPhotoneo launches MotionCam-3D Color (Blue) to improve robot perception - The Robot Report
robotIoTmachine-visionautomation3D-scanningdigital-twinssensor-technology