Robotic Machine Tending with 3D vision
Automate machine tending with millimeter accuracy. Reliable 3D vision for reflective metals, fewer errors, faster setup, and stable production performance.
Automating the Toughest
Robotic Machine Tending Challenges
From manual loading to fully automated laser marking - developed by Gasbarre and Pickit 3D, powered by a Zivid 3D camera.
Robotic machine tending automates part loading and unloading using industrial or collaborative robots to increase machine utilization and reduce manual intervention. The robot must position raw or finished parts within tight tolerances while interacting reliably with CNC machines, presses, or other equipment.
Insertion and placement tasks typically require millimeter-level accuracy. Minor deviations can cause misloads, collisions, scrap, or unplanned downtime. Robust 3D vision is therefore a critical subsystem in modern machine tending cells. The camera must deliver accurate, low-noise, and repeatable 3D data across varying materials and lighting conditions to ensure deterministic pick-and-place performance.
Precise Placement & Orientation
Robots must detect fine orientation details and separate parts reliably in varying lighting conditions.
Reflective and Dark Materials
Shiny or dark parts create distorted or incomplete 3D data for conventional vision systems.
Millimeter-level precision
Tight tolerances require precise alignment without constant jig adjustments or rework.
Achieve machine tending quality
with Zivid 3D sensing
Point cloud examples of machine tending captured with Zivid 3D cameras. Click the image to explore in 3D.
Enable Reliable Pick and Place
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Clearly separates parts and captures detailed orientation features
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Handles ordered and unordered parts without pre-sorting
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High-quality 2D color and stable 3D data in changing light
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Low noise and minimal distortion for first-time-right grasping
One-motion hook placement powered by Innodura and a Zivid 3D camera.
Expand What Your Cell Can Handle
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Covers metals, plastics, and composite materials
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Complete point clouds — even on highly reflective surfaces
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Wide dynamic range (HDR) for extreme contrast scenes in a single capture
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Fast capture times (~500 ms) on challenging parts
Reduce Setup Time and Manual Adjustments
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Stationary or robot-mounted configurations for optimal viewing geometry
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Accurate grasping in a single shot, eliminating the need for realignment jigs.
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Strong ambient light robustness for reliable factory-floor deployments
- Zivid presets and infield correction tools to minimize parameter tuning and commissioning time
Kolektor Digital's KoCo robot, equipped with a Zivid 3D camera.
Detecting stacked, reflective sheet metal parts under varying light conditions was a major challenge — Zivid 2+ delivered the best price-performance ratio, with stable, high-resolution 3D data that works even with mirroring.
Matthias Frey, Head of Robotics at J. Schmalz GmbH | Powered by a Zivid camera
Why traditional approaches fail
in real production
Typical Limitations
❌ Inconsistent results across varying part geometries and sizes.
❌ Data loss or artifacts on reflective or dark surfaces.
❌ Unstable boundary detection affecting grasp and insertion accuracy.
❌ Fixed mounting reduces flexibility in viewing angle optimization.
❌ Sensitivity to ambient light and long-term drift.
Zivid solutions
✅ High-accuracy 3D data enabling millimeter-level placement. Learn more →
✅ Reliable capture of specular and low-reflectivity materials. Learn more →
✅ Stable pose estimation without costly realignment jigs. Learn more →
✅ Flexible mounting strategies for optimal imaging geometry. Learn more →
✅ Proven stability in industrial production environments. Learn more →
Machine tending automation
in the real world
Circu Li-ion | Automated battery upcycling solution
Circu Li-ion's automated solution enables companies to significantly reduce CO2 emissions and increase the true value of each battery.
Innodura | Complex parts hanging solution for assembly lines
Hanging parts for processing is a task that has been primarily carried out manually, and automating it has proven to be a real challenge.
Kolektor | Envisioning robot workers
Kolektor Digital needed a 3D machine vision camera with human-like capability.
Start automating machine tending
with Zivid 3D vision
Explore machine tending point clouds
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