Sick Visionary-S Specifications

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Ranked Nr. 81 of 93 3D Vision Systems

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Thanks to the innovative 3D snapshot technology, Visionary-S 3D vision sensors from SICK offer maximum flexibility for countless applications in factory automation. Based on the stereo vision principle, with the Visionary-S, SICK is offering solutions for the highest demands on accuracy and speed, even for stationary applications. The Visionary-S combines structured illumination with the proven technology of a color camera and delivers colorful depth images in real time. Powerful visualization tools, broad support of common programming languages and reliable 2D and 3D information make the Visionary-S the ideal solution for robotics, intralogistics and various quality assurance tasks in production, to name a few examples.


At a glance:

Up to 30 color depth images per second

Works in absolute darkness and in daylight of up to 40 klx

Resolution: 640 px x 512 px; depth resolution down to the sub-millimeter

Output of 3D color data via a Gigabit Ethernet interface

Temperature range: 0 °C ... 50 °C (depending on the housing), enclosure rating: IP67

HDR mode

Working distance 500-65000 mm
Protection (IP) 67

Visionary-S Downloads

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Visionary-S Alternatives

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Basler blaze Time-of-Flight 3D Camera
Near-infrared | Working distance 940mm

4.6/5 (1)

The Basler blaze Time-of-Flight 3D Camera is a cutting-edge industrial solution offering real-time, precise 3D imaging for a wide range of applications. Leveraging Sony's DepthSense™ sensor technology and onboard depth image processing, it captures comprehensive data, including a 3D point cloud, intensity image, range map, and confidence map, ensuring a thorough understanding of complex environments. With its NIR laser diodes operating in the 940 nm range, it generates 2D and 3D data in one shot, making it highly efficient for industrial automation and logistics.Standout features of the Basler blaze camera include VGA resolution, delivering high precision and accuracy in 3D imaging. Its Dual Exposure HDR capability enables exceptional imaging performance even in high contrast scenes, while the IP67 rating ensures resilience in demanding industrial environments, offering resistance to dust and water. Moreover, the hardware trigger feature allows for precise triggering with minimal latency, crucial for real-time 3D image acquisition, making it an ideal option for time-sensitive industrial automation processes. These specialized specifications and features make the Basler blaze an attractive choice for industries seeking reliable and versatile 3D imaging solutions.
Sick TriSpectorP1000
Monochrome | Near-infrared | Working distance 1091mm
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The Sick TriSpectorP1000 is a programmable 3D camera designed for Industry 4.0 applications. Operating independently, it combines imaging, lighting, and analysis in a rugged housing, offering versatility for tailored solutions in quality control, robot handling, and profile verification. Using laser triangulation, it provides color and contrast-independent data, making it ideal for flexible and cost-efficient in-line automation. With capabilities for 3D, 2D, and profile inspections, along with integration with SICK AppSpace and HALCON, the TriSpectorP1000 is a potent tool for modern industrial automation.
Basler RGB-D Solution
Color | Monochrome
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The RGB-D solution merges Basler blaze 3D and color camera data for colored point clouds. It enhances object detection, classification, and scene understanding by combining depth and color information. This combination aids accurate recognition, particularly for similar shapes, and supports tasks like depalletizing and mobile robot navigation. The RGB-D approach offers advanced perception and improved accuracy for industrial automation applications.Advantages of RGB-D: When does the combined use make sense?Robust object detection and classification with increased accuracy of correct matches, especially for similarly shaped objectsExample: Can you tell in the left part of the point cloud whether it is an apple or an orange? This is only possible in RGB color. Conversely, a 2D camera would not be able to tell the difference between the photo of an apple and the real apple. Color information helps improve scene details where depth information is lackingExample: During depalletizing, two cartons are so close together on the pallet that they are recognized as one by the 3D camera. In the higher-resolution RGB data, however, a gap can be detected. Reliable scene segmentation, if necessary enhanced by the use of deep learning (here: integration of prior scene knowledge), for example for the use of mobile robotsExample: Finding the floor in 3D is supported by color: asphalt gray probably belongs to road (floor)
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