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Robots with 3D vision pick and place objects from bins automatically

Bin picking 

Random bin picking is typically at the input stage of a manufacturing process. Instead of traditional static fixtures or pre-filled stacking patterns, a robot is instead emptying a bin bulk-filled with parts for placing on, for example, a feeder, conveyor, or sorter for further processing in the plant. The choice of the vision system and, in particular, the 3D camera impacts the robot’s ability to successfully detect, pick, and place all types of parts. Learn how to increase the number of pickable parts using our Zivid Two machine vision camera - without compromising on speed.



Zivid Two delivers high resolution and extreme precision native color 3D point clouds with minimal occlusion, and excellent artifact suppression. Significantly improving object recognition and increasing the number of
detectable parts.



Zivid Two enables more reliable detection of object boundaries for material handling and a true-to-reality representation of object size, rotation, and absolute position in relation to the robot coordinate system. Essential for accurate picking, avoiding mispicks, and crashes.



Zivid Two, with its groundbreaking trueness, enables more demanding place operations for any pick and place robot. Placing or inserting more accurately for further processing, with known position and orientation, without colliding or damaging the parts.

Zivid Two Datasheet

Work faster. Zivid Two delivers significantly higher quality at faster speeds than typical laser scanners used in bin picking today. With capture speeds less than 300 ms, Zivid Two covers high dynamic range scenes including shiny and reflective objects

Challenges & Solutions

Bin picking is still a challenge for robots and collaborative robots. Even at large manufacturers, adoption of bin picking stations is low, and at SMEs the number is still close to zero. Unpickable objects are typically complex-shaped, hard to manipulate, entangled, and/or highly reflective machined or polished metals. The difficulty stems from the inherent uncertainty in physics, perception, and control.

See tiny and detailed objects, densely stacked or randomly arranged.

Zivid Two provides high resolution and precision point clouds with minimal occlusion, capturing a variety of shapes and sizes with all the fine details.

  • Very small, thin sheets, highly detailed, and irregular objects.
  • Densely stacked with a little gap or randomly arranged and piled on top of each other.
  • Distinguish features smaller than 5mm for reliable object recognition and separation of boundaries for picking.
Image shows metal parts and cylinders in a bin captured by Zivid for picking applications

Point cloud example with Zivid Two - Various metallic objects in a bin, typical for industrial bin-picking scenarios. View in 3D HERE 

See shiny, reflective, machined, and polished parts

3D HDR and Artifact Reduction Technology (ART) ensures excellent suppression of imaging artifacts from reflections, inter-reflections, specular highlights, and high contrast transitions.

  • Shiny and reflective, sheet metal, cylinders, washers, molded, machined, polished, and chrome-plated parts.
  • Capture speeds <300 ms for high dynamic range scenes such as shiny and reflective
Zivid 3D camera captures high quality point clouds of reflective and shiny metal parts

Point cloud example with Zivid Two - Highly shiny and reflective, chrome plated, machined and polished parts. View in 3D HERE. 

Experience fewer occlusion outliers 

Zivid Two is ultra-compact with a small baseline and more optimal occlusion performance than larger baseline cameras and scanners. A large baseline gives excessive projector/camera shadowing and loss of scene details, creating holes, and missing data affecting the detection. There's also a risk of missing smaller objects hidden by shadows in the bin, for example, close to corners and edges, especially when picking from smaller boxes.

Learn more about occlusion here.

To avoid occlusion from e.g. laser sensor, Zivid sensors have a small baseline to secure full bin point cloud

Occlusion by bin edges; left image captured with laser system (large baseline), right image is with Zivid Two. View in 3D HERE. 

Get started with 3D development today!

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