Use Camera to Get Point Cloud, Generate Target Object Model, and Configure Pick Point Manually

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In scenarios where there is no STL model or poor consistency between the acquired point cloud and the STL model file, you can use the point cloud acquired by the camera to generate a point cloud model and configure the pick point(s) manually.

Adjust Camera Parameters

To ensure that the camera can acquire qualified point cloud, you need to adjust camera parameters.

Preparations

  1. Lighting conditions: Ensure that the lighting around the target object is even and not too dark or too bright.

  2. Target object placement: Place the target object within the camera’s field of view and ensure that its positioning highlights the key features of the target object.

  3. Background selection: Ensure that the target object is easily distinguishable from the background.

Adjust Camera Parameters

  1. Open Mech-Eye Viewer and connect the camera.

  2. Click model cloud generate camera get to acquire data once.

  3. Click point cloud to check the effect.

    model cloud generate camera 1

    ×

    model cloud generate camera 2

    The target object is outside the camera’s field of view. At this time, it is necessary to place the target object within the camera’s field of view.

    ×

    model cloud generate camera 3

    The exposure time parameter is set too low. At this point, you need to increase the exposure time in the 3D parameters.

    ×

    model cloud generate camera 4

    The exposure time parameter is set too high. At this point, you need to decrease the exposure time in the 3D parameters.

    ×

    model cloud generate camera 5

    The point cloud information of the target object is incomplete. Try to slightly adjust the exposure time in the 3D parameters.

  4. Keep capturing until you acquire point clouds with relatively high quality.

After the preparations are ready, on the homepage of the target object editor, click Select under the Get point cloud by camera workflow, and set the target object name to enter the configuration process. The overall configuration process is shown in the figure below.

overview
  1. Acquire the point cloud: Use the current project to acquire the point cloud. Then adjust the parameters and set the 3D ROI to generate a point cloud model.

  2. Edit model: Edit the generated point cloud model, including the configurations for the point cloud display and calibration of the object center point, to ensure better performance of the subsequent matching task.

  3. Set pick point: Add pick points or the pick point array on the point cloud model which is already edited.

  4. Set collision model (optional): Generate the collision model for collision detection during path planning.

The following sections provide detailed instructions on the configuration.

Acquire Point Cloud

Set Project Information

Select the “Capture Images from Camera” Step in the current project to acquire the point cloud. Click Acquire point cloud, and then the result can be viewed in the visualization area.

Configure Point Cloud Display Settings

By configuring Point cloud display settings, you can view different types of point cloud models, i.e., the models of all point clouds, surface point cloud only, and edge point cloud only, for the current target object and edit the point cloud model according to actual requirements. You can also change the display color of the point cloud model and view relevant reference information, such as the pseudo-textured point cloud.

Preprocess Parameters

For detailed explanations of the parameters, refer to Preprocessing Parameters.

If the “3D Target Object Recognition” Step is used in the project, you can enable Use parameters of Step “3D Target Object Recognition”, and then the parameter values in the “3D Target Object Recognition” Step will be synchronized.

Set ROI and Background

By selecting a 3D ROI or capturing an image of the background, you can quickly remove irrelevant point clouds from the scene, enabling rapid extraction of the target object’ point cloud.

If you need to remove the background by capturing the image of the background, you must move the target object out of the camera’s view after acquiring the point cloud. Then click Capture and remove background, and the tool will automatically capture an image of the background and remove the point cloud of the background.

Now the point cloud acquisition is completed. You can click Next to start editing the generated point cloud model.

Edit Point Cloud Model

The generated point cloud model should be edited for better performance in the subsequent matching task.

Configure Point Cloud Display Settings

By configuring Point cloud display settings, you can view different types of point cloud models, i.e., the models of all point clouds, surface point cloud only, and edge point cloud only, for the current target object and edit the point cloud model according to actual requirements. You can also change the display color of the point cloud model and view relevant reference information, such as that of the pseudo-textured point cloud.

Calibrate Object Center Point

The tool can automatically calculate the object center point. If you need to calibrate the object center point, select the calculating method under Calibrate center point by application, and click Start calculating.

Method Introduction Operation

Re-calculate by using original center point

The default calculation method. Calculate the object center point according to the original object center point and features of the target object.

Calibrate to center of symmetry

Calculate the object center point according to the object’s symmetry.
After calculating the symmetry of the current model, the object center point will be set to the center of symmetry. There may be deviations in the calculation. If deviations occur, please adjust manually.

Calibrate to center of feature

Calculate the object center point according to the selected Feature type and the set 3D ROI.

  1. Select the Feature type according to the geometric features of the object, and the tool will calculate the object center point according to the feature type.

  2. (Optional) Enable Use 3D ROI. After the 3D ROI is set for the target object, the tool will automatically calculate the object center point according to the features of the target object in the 3D ROI.

Configure Point Cloud Model

To better use the point cloud model in the subsequent matching task and enhance matching accuracy, the tool provides the following two options for configuring the point cloud model. You can enable the Configure point cloud model switch as needed.

Avoid False Matches

Once Avoid false matches is enabled, more matching attempts will be made based on the settings to obtain matching results with higher confidence. However, more matching attempts will lead to longer processing time.

Two methods to avoid false matches are offered, i.e., Auto-calculate unlikely poses and Configure symmetry manually. See the table below for more information.

Method Introduction Operation

Auto-calculate unlikely poses

Poses that may cause false matches will be calculated automatically. In subsequent matches, poses that successfully match these poses will be considered unqualified and filtered out.

  1. ClickCalculate unlikely poses to calculate potentially mismatched poses.

  2. If you think a pose in the list will not cause a false match, you can click the × icon to remove it from the list.

Configure symmetry manually

For rotationally symmetric target objects, configuring the rotational symmetry of the point cloud model can prevent the robot’s end tool from unnecessary rotations when it is holding the target object. This increases the success rate of path planning and reduces the time required for path planning, allowing the robot to move more smoothly and swiftly.

Select the symmetry axis by referring to Rotational Symmetry of Target Objects, and then set the Order of symmetry and Angle range.

When Auto-calculate unlikely poses is selected, for the option to take effect in the subsequent matching, you need to configure the relevant parameters in the used matching Steps. See the following for details.

  • If the “3D Matching” Step is used, go to Avoid False Matches  Adjust Poses, and select Filter out unlikely poses in the drop-down menu. This parameter will appear when the parameter tuning level is set to Advanced or Expert.

  • If the “3D Target Object Recognition” Step is used, go to Avoid false matches  Adjust poses in the “Target object selection and recognition” process, and select Filter out unlikely poses. This parameter will appear when the Advanced mode switch is turned on.

Set Weight Template

In the target object recognition process, setting a weight template can enhance the accuracy of matching results by emphasizing the selected features for recognition. Weight templates are typically used to distinguish the orientation of the target object, and the set weight template will affect the matching results. The procedures to set a weight template are as follows.

A weight template can only be set when the Point cloud display settings is set to Display surface point cloud only.

  1. Click Edit template.

  2. In the visualization area, hold and press the right mouse button to select a part of the features on the target object. The selected part, i.e., the weight template, will be assigned more weight in the matching process.

    By holding Shift and the right mouse button together, you can set multiple weighted areas in a single point cloud model.

    set weight template
  3. Click Apply to complete setting the weight template.

For the configured weight template to take effect in the subsequent matching, go to the “Model Settings” parameter of the “3D Matching” Step, and select the model with properly set weight template. Then, go to “Pose Filtering” and turn on the switch Consider Weight in Result Verification. The “Consider Weight in Result Verification” parameter will appear after the “Parameter Tuning Level” is set to Expert.

Now the editing of the point cloud model is completed. You can click Next to set the pick point for the point cloud model.

Set Pick Point

Adjust Pick Point

By default, the pick point list displays the added pick points, the origin of which is the object center point. Changing the object center point will influence the pick points.

If you need to adjust the pick point, for example, delete and hide it, you can hover the cursor over the ? icon to the right of Pick point list to view the instructions. You can also set relevant values under Pick point settings, or drag the pick point to an appropriate position in the visualization area on the left.

Set Pick Point Array

When the target object is symmetrical, you can set the pick point array based on the object center point according to actual needs. Setting the pick point array can prevent the robot’s end tool from unnecessary rotations during picking. This increases the success rate of path planning and reduces the time required for path planning, allowing the robot to move more smoothly and swiftly. The procedures for setting are as follows.

  1. Under “Pick point settings,” click Generate next to Pick point array.

  2. Refer to Rotational Symmetry of Target Objects to select the axis of symmetry, and then set the Order of symmetry and Angle range.

Add Picking Configuration

If a tool has been configured in the “Path Planning” Step or Mech-Viz, you can enable it in the target object editor. Once the tool is enabled, you can preview the relative position between the tool and the pick point, helping to determine if the pick point is set appropriately.

If you have modified the tool configurations in the “Path Planning” Step or Mech-Viz, save the changes to update the tool list.

Click Save to save the configurations for the target object. To set the collision model, click Next.

Set Collision Model (Optional)

The collision model is a 3D virtual object used in collision detection for path planning. You can configure the following settings on the collision model according to the actual situation.

Select Method for Generating Collision Model

The tool automatically recommends the collision model generating method based on the current configuration workflow. The recommended method for this case is Use STL model to generate point cloud cube. This tool will generate the point cloud cube based on the imported STL model and conduct collision detection. The collision model generated in this method features high accuracy, while the collision detection speed is lower.

Select STL Model

Click Select STL model and then select the STL model used to generate the point cloud cube.

Configure Point Cloud Cubes

Point cloud cubes are the cubes centered at each point in the point cloud. If these cubes collide with other objects, the point cloud is considered to have collided with these objects.

To perform collision detection, the point cloud is filled with cubes with an edge length of 2 mm. When the target object is too small and its dimensions are close to the edge length of the point cloud cube, the accuracy of the collision model will decrease. When the target object is too large and the collision model includes too many point cloud cubes, the collision detection speed will slow down.

Align Models

Aligning the collision model with the point cloud model of the target object ensures effective collision detection. You can click Auto-align point cloud model and collision model or manually adjust the pose of the collision model to achieve the alignment with the point cloud model of the target object.

Configure Symmetry of Held Target Object

Refer to Rotational Symmetry of Target Objects to select the axis of symmetry, and then set the Order of symmetry and Angle range.

Now, the collision model settings are completed. Click Save to save the target object to Solution folder\resource\workobject_library. Then the target object can be used in subsequent matching Steps.

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