10620110Vision for Robotics in Industrial Automation
Course Information
Description
This course prepares the learner to program a vision systems as a stand-alone solution and integrate into robotic systems. The student will receive instruction on general vision concepts, including camera setup, lighting, lensing, 2D Single and  2D Multiple View Process and perform hands-on programming with industrial vision systems.
Total Credits
2
Course Competencies
  1. Develop a camera setup for a robot
    Assessment Strategies
    Skill Demonstration
    Criteria
    Configure the computer to run iRVision software
    Calculate the focal distance, field of view, and measurement accuracy for a vision setup
    Select an appropriate lens based on the inspection parameters
    Mount a camera and align it
    Adjust the lighting location and types
    Adjust the exposure and focus
    Successfully adapt a vision system to capture features of at least 3 different parts
    Use manufacturer specific software

  2. Create a user and tool frame for vision applications
    Assessment Strategies
    Skill Demonstration
    Criteria
    Calibrate a 6 pt tool frame
    Teach an application user frame and an offset user frame
    Use a calibration grid to calibrate an offset user frame and perform camera calibration
    Use the application user frame and offset user frame in iRVision
    Select appropriate frame locations, numbers, and teaching types
    Use manufacturer specific software

  3. Calibrate for a vision process
    Assessment Strategies
    Skill Demonstration
    Criteria
    Create an iRVision Camera Setup
    Calibrate a camera to make a physical measurement
    Create an iRVision Camera Calibration
    Determine the accuracy of your calibration
    Use manufacturer specific software

  4. Setup a single-view inspection vision process
    Assessment Strategies
    Skill Demonstration
    Criteria
    Setup an iRVision single-view inspection vision process
    Describe when to use feature identifiers such as GPM, BLOB, and edge detection
    Setup error handling if the vision system cannot identify a part
    Select appropriate degrees of freedom for part detection
    Determine if a part passes or fails based on vision inspection
    Demonstrate changing the cell behavior based on the inspection result
    Use manufacturer specific software

  5. Setup a 2D single-view vision offset process
    Assessment Strategies
    Skill Demonstration
    Criteria
    Setup an iRVision 2D single-view vision offset process
    Troubleshoot frame alignment and offset errors
    Utilize PRij offsets
    Use Conditional Execution Tools to send part information to the robot program
    Demonstrate changing the robot behavior based on part information
    Successfully direct robot motions to pick a part based on vision offsets

  6. Troubleshoot common vision inaccuracies
    Assessment Strategies
    Skill Demonstration
    Criteria
    Correct lighting issues such as glare, shadows, and blurriness
    Describe lighting solutions such as filters, diffusion, and back lighting
    Use search area limits to remove distracting background elements
    Use masks to limit the software to the desired part features
    Gather troubleshooting information using Vision Runtime on the Teach Pendant
    Use manufacturer specific software

  7. Manage implementing a vision project using the automated cell
    Assessment Strategies
    Skill Demonstration
    Written Product (Project Documentation)
    Criteria
    Project proposal for a vision system is professionally written according to specifications
    Project includes a program plan, created before beginning work
    Identify work holding or fixturing for adding a vision inspection to the automated cell
    Adapt camera setup and lighting to suit the conditions and limitations of the automated cell
    Setup a vision inspection for parts in different locations, such as on a conveyor, held by a robot, or in a fixture

  8. Develop an awareness of how vision systems can be vulnerable to bias
    Assessment Strategies
    Skill Demonstration
    Written Product
    Criteria
    Identify natural variation that the vision system may encounter
    Describe physical differences (including race for human vision systems) that may affect a vision system and why they must be considered
    Select appropriate and unbiased models for training the vision system
    Propose good programming practices to accommodate natural variation