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How to succeed with robot automation using human-like 3D vision

Performing random bin-picking with color 3D vision

Most articles and literature you'll find describes random 3D bin-picking using machine vision as the ultimate challenge for industrial- and robot automation. Detecting and recognizing objects, then correctly picking and placing them might seem trivial for humans with both functional brain, eyes, and hands.

However, for most automation tasks, strict control of the operation is required for successful and repetitive operation. With random objects in trays, bins, or on pallets, 3D cameras become a very important piece of the automation system, and here we'll show you why human-like 3D vision is essential.

Challenge #1

Separate objects with similar shape

Zivid One 3D cameras output a full color point cloud, with pixel-wise XYZ + RGB data. This helps you separate similar objects.

Greyscale separate 3D bin-picking objects Separate 3D bin-picking objects

Challenge #2 

Recognize, inspect and categorize

Zivid One provides 2.3 Mpixel output so there's no question about what objects you are looking at.

Recognize 3D bin-picking objects Recognize 3D bin-picking objects in color

Challenge #3

Separate objects for proper handling

Zivid One 3D cameras with HD color RGB point clouds provide you the details and information needed for robots to work with humans, as humans.

Low quality TOF 3D bin-picking objects High quality color 3D bin-picking objects
Greyscale scanner 3D bin-picking objects High definition color 3D bin-picking objects

Challenge #4

Don’t miss the details

Don't miss details by using monochrome 3D scanners or TOF sensors. Zivid provides high-definition, high dynamic range point clouds. Including full RGB color.

Monocrome 3D bin-picking objects Color, hi-resolution 3D bin-picking objects
Low resolution 3D bin-picking objects High resolution 3D vision bin-picking objects

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