Train Robot Poses for Aligment

This guide provides a step-by-step walkthrough for training robot poses for alignment in a VGR Vision-Guided Robotics is an In-Sight Spreadsheet feature that uses machine vision to guide robot motion through Robotics String Functions and VGR commands. application. For more information, see Pose Training and Run-Time Alignment.

Prerequisites

Before training robot poses for alignment, ensure the following:

• The vision system is properly mounted, connected, and discovered in In-Sight.

• A spreadsheet VGR job A job is a user-configured program in In-Sight Spreadsheet consisting of functions and designed for specific applications. You can create and edit jobs using the In-Sight Spreadsheet interface, and load them on a vision system for deployment in a live environment. has been created and configured, containing:

  • Image acquisition Acquisition is the process or result of the vision system acquiring a new image. logic

  • The required Robotics String Functions (VGRProcessCommand, VGRDefinePart, and VGRHandEyeCalibration)

  • A Feature Finder tool is configured and reliably detectable, as it serves as the alignment target.

  For more information, see Building a VGR Job.

• Robot communication is established and verified.

• Hand Eye Calibration has been completed successfully with the vision system mounting configuration correctly specified in the VGRHandEyeCalibration function Functions are tools that are available in Spreadsheet for processing and analyzing acquisitions or other results. You can add functions to your Spreadsheet job to create tool chains and produce results for specific applications.. For more information, see Hand-Eye Calibration.

Program Sequence

The program sequence for training robot poses is as follows:

1. Move the robot to the desired pick or place pose for the part. Ensure that the part is correctly gripped, positioned, and clearly visible in the vision system field of view.

2. The robot controller sends a Train Robot Pose (TTR) command to the vision system, including the current robot position. This trains the pick or place robot pose.

3. The vision system stores the current robot pose as the desired pick or place pose, and returns a TTR response with the execution status to the robot controller.

4. Release the part and move the robot to the image acquisition pose. Ensure that the part is correctly positioned, and clearly visible in the vision system field of view.

5. The robot controller sends a Train Part Pose (TT) command to the vision system, including the current robot position. This trains the robot pose during image acquisition.

6. The vision system acquires the image and locates the features of the part. It also stores the found feature position as the desired position of the part, and returns a TT response with the execution status to the robot controller.

Once the TTR and TT commands have been successfully executed, the training for robot poses is complete.