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.

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.

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.

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.