Hand-Eye Calibration-related Concepts

It refers to how the robot communicates with the vision system. Mech-MindVision System provides three communication modes, namely, Standard Interface, Adapter and Master-control. For details, refer to the section Communication Overview.

It refers to the way that the camera is mounted in the working unit. Commonly seen mounting modes are Eye to Hand (ETH) and Eye in Hand (EIH).

It refers whether the calibration board images and poses are collected automatically. It can be divided into automatic calibration and manual calibration. The operations of manual calibration are relatively complicated. Therefore, automatic calibration is recommended whenever possible.

During calibration, the robot will be connected, and Mech-Vision automatically plans the calibration path, and controls the robot to move along the planned path. It collects calibration board images and robot flange poses at each waypoint.

During calibration, the robot is not connected, and you need to control the robot manually, move the robot along the path you planned or to touch the calibration circles, enter the robot flange poses, and trigger the software to capture calibration board images.

It refers to how the calibration data is collected. Mech-Vision can only use the multiple random calibration board poses method for calibration data acquisition.

It lets the robot move along the waypoints on the robot path automatically generated or you planned. This method captures images of calibration boards, detects calibration circles and collects robot flange poses at each waypoint on the paths in order to calculate the correct relationship between the calibration board, camera, and robot. It is easy to perform and has a high accuracy. It is recommended for 6-axis or 4-axis robots.

Intrinsic parameters are internal to a camera, including the focal length, the lens distortion, etc. These parameters are usually calibrated and stored in the camera before the camera leaves the factory.

Extrinsic parameters describe the pose transformation between the robot reference frame and the camera reference frame. The calibration of extrinsic parameters is also called the hand-eye calibration, where the camera is considered as the eye, and the robot the hand. As the spatial relationship between the robot and the camera changes from application to application, the hand-eye calibration needs to be conducted on-site to guarantee its accuracy.

A marker refers to an object used in place of the calibration board during hand-eye calibration. The marker should have clearly visible feature points, and the feature points should be evenly distributed.

It refers to the robot pose when the camera captures images of the calibration board during calibration. When the multiple random calibration board poses method is used to collect calibration data, the calibration points are the waypoints on the calibration path.

It refers to the circle-shaped feature point on the calibration board. During calibration, the software calculates the pixel coordinates of the center points of the calibration circles based on the 2D image of the calibration board, and the coordinates of the center points relative to the camera frame based on the depth image. It then calculate camera extrinsic parameters based on collected calibration circle data.