Hand-Eye Calibration

Introduction 

Hand-eye calibration is used to relate what the camera (“eye”) sees to where the robot arm (“hand”) moves.

Eye-in-hand calibration is a process for determining the relative position and orientation of a robot-mounted camera with respect to the robot’s end-effector. It is usually done by capturing a set of images of a static object of known geometry with the robot arm located in a set of different positions and orientations.

Eye-to-hand calibration is a process for determining the position and orientation of a statically mounted camera with respect to the robot’s base frame. It is usually done by placing an object of known geometry in the robot’s gripper. Followed by taking a series of images of it in a set of different positions and orientations.

Further Reading 

For a detailed description of the topic, please read the following pages:

Version History 

SDK	Changes
2.6.0	Improved robustness of the checkerboard detection with regards to Blooming - Bright Spots in the Point Cloud.
2.4.0	The hand-eye calibration method is updated to improve accuracy, leading to roughly 50% improvement in translational residuals at a cost of slightly increased rotational residual.
2.3.0	Improved robustness of the checkerboard detection.
2.2.0	Support is added for the new line of official Zivid calibration boards, the first of which is the ZVD-CB01 (7x8 30 mm).
2.0.0	Hand-eye API is changed, part of the `Calibration` namespace.
1.6.0	Hand-eye calibration API is added.