Vision-Guided Loading Neatly Arranged Target Objects
This tutorial introduces how to deploy a 3D vision–guided structured bin picking application, using the application template case “Loading Neatly Arranged Target Objects” in the Solution Library.
Application Scenario: The 3D vision system guides the robot to pick and place neatly arranged parts from the pallet onto the conveyor line/secondary positioning platform.
Application Overview
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Target object: target objects that are orderly placed. The application uses housings as an example.
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This application sets the pick point by teaching, and then uses the camera to acquire the point cloud of the real object to make the target object model.
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This application uses a real camera to capture images of the housings for target object recognition. If you want to use a virtual camera, please click here to download image data of the housings.
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Camera: Mech-Eye PRO M camera, mounted in eye to hand (ETH) mode.
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Calibration board: When the working distance is 1000 to 1500 mm, it is recommended to use the calibration board CGB-035; when the working distance is 1500 to 2000mm, it is recommended to use the calibration board CGB-050.
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Robot: a six-axis robot. This application uses KUKA_KR_10_R1100_2_HO as an example.
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IPC: Mech-Mind IPC STD
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Software: Mech-Vision 2.0.0, Mech-Eye Viewer 2.4.0
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Communication solution: Standard Interface communication, in which the vision system outputs the path planned by the Mech-Vision software.
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End tool: gripper
For this application, you are required to prepare a model file in .obj format for the gripper, which will be used for collision detection during path planning. You can download it by clicking here.
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Scene object: scene object model
This application requires a scene model file in .stl format, which is used to simulate a real scene and is used for collision detection in path planning. You can download it by clicking here.
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If you are using a different camera model, robot brand, or target object than in this example, please refer to the reference information provided in the corresponding steps to make adjustments. |
Deploy a Vision-Guided Robotic Application
The deployment of the vision-guided robotic application can be divided into six phases, as shown in the figure below:
The following table describes the six phases of deploying a vision-guided robotic application.
| No. | Phase | Description |
|---|---|---|
1 |
Vision Solution Design |
Select the hardware model according to the project requirements, determine the mounting mode, vision processing method, etc. (This tutorial has a corresponding vision solution, and you do not need to design it yourself.) |
2 |
Install and connect hardware of the Mech-Mind Vision System. |
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3 |
Load the robot master-control program and the configuration files to the robot system and set up the communication between the vision system and the robot, thus helping the Mech-Mind Vision System obtain control over the robot. |
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4 |
Perform the automatic hand-eye calibration in the eye-to-hand setup, to establish the transformation relationship between the camera reference frame and the robot reference frame. |
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5 |
Use the application template “Loading Neatly Arranged Target Objects” in Mech-Vision Solution Library and plan the robot path with the advanced component of path planning. |
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6 |
Based on the robot example program MM_S3_Vis_Path, write a pick-and-place program suitable for on-site applications. |
Next, follow subsequent sections to complete the application deployment.