- How it works
At Zivid we are committed to continued advancements of the Zivid One+ 3D camera family through regular software updates.
For the release of version 1.6 of the Zivid SDK, our primary focus is to make it easier to increase the performance of our 3D cameras.
Hand-eye calibration describes the transformation required to make a 3D camera and a robot work together successfully in one common coordinate system.
The following two graphs show typical rotational- and translation errors as a function of the number of images used per calibration.
We believe using the calibration patterns and hand-eye calibration provided by the Zivid SDK drastically simplifies the process, and will significantly improve the transformation between the vision component and the robot arm's end-effector.
Provided with SDK 1.6 you will find
Visit the Zivid Knowledge Base for the in-depth resources.
We have added new functionality for directly capturing 2D images from Zivid One+ 3D cameras.
Note: Zivid One+ uses the same 2.3 MP (megapixel) sensor to capture 2D images and 3D data. This means that you always get a 1:1, pixel-by-pixel, correspondence between 2D and point cloud (3D).
Using this function makes it possible to capture a single 2D image without capturing and processing additional 3D data. This can be used to reduce cycle times when using 2D data in your application.
You can now save (export) each frame's capture settings from Zivid Studio.
Zivid's implementation of GenICam for HALCON is now supported in both Windows and Linux environments.
In addition to new hand-eye calibration methods and 2D api, we made some under the hood SDK enhancements like improved Open CL diagnostics.