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Agriculture has always had a focus on optimization and productivity - just think about the journey this industry has taken from hard manual labor 200 years ago to the hypermodern way autonomous vehicles are used today e.g. plowing and seeding. What we now see is a new wave of automation taking place, with buzzwords such as "vertical farming", "indoor farming" and "autonomous harvesting" - and its fair to assume that the future of agriculture most likely will be very different from what we see today.
Automating the full growing process from seed to harvest is the key to business growth and sustainable success. The Zivid 3D cameras are specialized in enabling AI-based vision systems for agricultural robots to pick and place crops more accurately and efficiently.
Measure the finest crop details such as dimensions, imperfections, and color with a high-precision machine vision camera.
Detect, classify, and analyze crops to catch early signs of disease and estimate real-time yields remotely with 3D vision.
Ensure the quality and quantity of products 24/7 by automating back-breaking manual labor with vision-guided pick and place robots.
With the Zivid 3D cameras, robots can see the world in color and 3D with comparable visual acuity to human vision. The color data is essential for automated robotic farming as it augments XYZ position and dimension data with RGB data for precise object recognition. It enables robots to separate similar fruits or plants for accurate pick and place handling.
Learn more about how color 3D vision helps you to succeed with pick and place robotics →The Zivid 3D cameras support both stationary and robot-mounting. This unique flexibility enables the camera to have unlimited capture scope and view target objects from multiple angles and positions. The robot-mounting option is especially beneficial for vertical farms where a single camera typically mounted on an automated guided vehicle (AGV) needs to navigate between large numbers of racks in a confined space.
Learn more about the benefits of robot-mounted 3D vision →For automated fruit picking, it is essential to locate target objects accurately so that the robot end effector can gently handle them without causing any damage or mispick. With the minimal dimension trueness error (< 0.2%), the camera can reliably capture the size, rotation, and absolute position of the objects as the eyes of farmers, every time.
Why Trueness is the secret to reliable picking? Find out in this blog post →Zivid brings
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