Vision-Guided Single-Case Depalletizing

This tutorial introduces how to deploy a 3D vision–guided carton depalletizing application using the application template case of “Single-Case Depalletizing” in the Solution Library.

Application scenario: The 3D vision system guides the robot to pick single-case cartons from the pallet and place them on the conveyor line.

Application Overview

  • Target object: single-case cartons.

    • This application uses a real camera to capture images of cartons for target object recognition. If you want to use a virtual camera, please click here to download image data of the cartons.

    • This application uses deep learning to assist recognition. There is already a built-in deep learning model package in the resource/dl_model directory of this solution.

  • Camera: Mech-Eye DEEP camera, mounted in eye to hand (ETH) mode.

  • Calibration board: It is recommended to use the calibration board CGB-050.

  • Robot: a six-axis robot. This application uses ABB_IRB6700_150_3_20 as an example.

  • IPC: Mech-Mind IPC STD

  • Software: Mech-Vision & Mech-Viz 2.0.0, Mech-Eye Viewer 2.4.0

  • Communication solution: Standard Interface communication, in which the vision system outputs the path planned by the Mech-Viz software.

  • End tool: vacuum gripper

    For this application, you are required to prepare a model file in .obj format for the vacuum gripper, which will be used for collision detection during path planning. You can download it by clicking here.

  • 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.

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:

getting start deployment

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

Vision System Hardware Setup

Install and connect hardware of the Mech-Mind Vision System.

3

Robot Communication Configuration

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.

4

Hand-Eye Calibration

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.

5

Vision Project Configuration

Use the application template “Single-Case Depalletizing” in Mech-Vision Solution Library and plan the robot path with the advanced component of path planning.

6

Picking and Placing

Based on the robot example program MM_S9_Viz_RunInAdvance, write a pick-and-place program suitable for on-site applications.

Next, follow subsequent sections to complete the application deployment.

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