Smart Vacuum Picking Skill
Surface interpretation for vacuum picking.
Last updated
Surface interpretation for vacuum picking.
Last updated
A vacuum gripper belongs to the group of astringent grippers in which a continuous holding force is applied without compressive stress. By creating a vacuum inside the gripping system, objects are attracted and held onto the gripper accordingly if the vacuum is maintained sufficiently. The Smart Vacuum Picking Skill is designed for single-suction vacuum grippers.
Depending on the setting of the skill, a certain number of possible pick points is displayed in the camera image. The color coding provides information on the interpretation of the pick points. Points marked in yellow represent potential pick points that also meet the quality requirements of the system. The blue point, on the other hand, defines the best pick point selection, which best meets the requirements. The selection and sorting of the pick points can be set via the parameters in the skill. The pick point position and the quality value are also displayed in the Graphical User Interface.
A classic use case for this skill is, for example, singulation in a department store, since this skill can grab a large number of unknown parts. It does not focus on specific parts, but on an optimal grasping point on any object. This means that numerous items, such as pens, packaging, plates and even bags, can be singled out and placed in the shipping carton with just one skill.
The skill is already pre-configured in a way that enables it to handle a wide variety of parts. To test the skill, go to "Option" - "Test". There you have the possibility to run the skill and view the predictions of the grip points.
If the skill is to be optimized for the parts, this can also be implemented in the test area. After the skill has been selected, the parameters can be optimized in the lower right corner. After saving the new parameters, the skill can be executed again immediately. The image on the left shows the new prediction of the skill. With the "Parameter Download" button, the parameters can easily be downloaded, so that they can be restored at a later time.
The different recordings of the skill are stored in the "Capture" area.
If a configuration from the capture area is needed, this data can be sent in an encrypted file to our support.
Position
Position of the grasp point relative to the robot’s coordinate system (in m)
Orientation
Rotation of the grasp point relative to the robot’s coordinate system (in m)
Quality
Quality value for the evaluation of a gripper
Conditions
Camera mount:
Dynamic
Static
Camera distance:
35 – 45 cm
Parts dimensions:
2 – 6 cm
Parts material:
matt - low reflection
Specs
Avg. recognition time:
< 0.5 seconds
Supported grippers:
Vacuum
Magnet
Single contact point
Features
Single pick-point recognition
Generalized to a variety of object types
Picking from bulk
To ensure accurate identification of various types of objects, the skill parameters can be easily adjusted to fit your specific needs. Here are some recommendations to help you find the perfect parameters for your application. For your convenience, we've only included descriptions of parameters that differ from the default settings.
Used objects: boxes of varying sizes, matt and shiny surfaces
Camera distance: 550mm
Camera mount: 30° angled
Parameters:
Min Quality: 0.32
other parameters: default values
Maximum deviation to z axis
deviation_to_z_axis
float
Maximum angle in degrees of the pick pose's z-axis to the camera's z-axis.
Shuffle range
shuffle_range
float
Maximum number of pick points that can be returned. Ignored if < 1.
Margin
margin
float
Minimum distance of pick points to the image edges. It is a percentage of image size and the same along all edges.
Z range
z_range
float
Maximum allowed distance (in the z direction) between any pick points and the one closest to the camera.
Min quality
min_score
float
Minimum quality for pick points, as reported by the AI model. Setting it too high may prevent pick points from being detected.
pose (Transformation)
Pick pose for the gripper
pixel (list)
Coordinates of the pick point in the image frame
quality (float)
Quality of the original detection, as reported by the AI model.
optimization_angle (float)
Only present if the parameter optimization_orientation is set to true. The parameter represents the rotation angle in radians that was applied to the original pick pose during the orientation-optimization step.
