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Get the hardware required, your engineering notebook, and open VEXcode V5.

Materials Required:
Quantity Materials Needed
1

VEX V5 Classroom Starter Kit
1

VEXcode V5 (latest version, Windows, MacOS)
1

Engineering Notebook
1

Configuring a Vision Sensor (VEX Library)
1

Tuning the Vision Sensor (VEX Library)
1

Detecting Objects (Vision) example project

This activity will give you the tools to use the Vision Sensor.

You can use the Help (C++) information inside of VEXcode V5 to learn about the instructions.

VEXcode V5 is shown with the Toolbox open on the far left, and the Help for the Drive for command open on the far right. The Help shows the definition of the command and information about how it is used.

 

Step 1: Open an Example Project

VEXcode V5 contains many different example projects. You'll use one of them in this exploration.

Open the Detecting Objects (Vision) example project by completing the following steps:

  • Open the File menu.
  • Select Open Examples.

VEXcode V5 Toolbar with the File menu open and Open Examples highlighted in a red box. Open Examples is the fourth menu item beneath New Blocks Project, New Text Project, and Open.

  • Use the filter bar at the top of the application and select "Sensing."

VEXcode V5 Example Project selection window with the Sensing filter selected at the top, and highlighted in a red box. Below there are six example project icons showing.

Select and open the Detecting Objects (Vision) example project.

Example project icon reads Detecting Objects Vision at the bottom and shows a blue diagram of a robot with a sensor indicating object detection above.

Save your project as Detecting Objects.

  • Check to make sure the project name Detecting Objects is now in the window in the center of the toolbar.

Project name dialog box in the VEXcode V5 Toolbar reads Detecting Objects and shows that slot 1 is selected to the left, and reads Saved to the right.

Step 2: Configuring and Using the Vision Sensor

Vision Sensor configuration window shows an image of a hand holding a red cube to the left, with an overlay on the cube and the words REDBOX and W142 H142 above it. To the right, 3 Color signatures are set for BlueBox, Redbox, and Greenbox.

Open the previously saved Detecting Objects (Vision) example project.

How is the Vision Sensor being used in this project? Predict what will happen when the project is run and write down the predictions in your engineering notebook.

The image shows a VEXcode program written in C++ for a robot that uses events to check for the presence of blue, red, and green objects using a vision sensor. The code imports the necessary VEX library and sets up three events: checkBlue, checkRed, and checkGreen. Three callback functions are defined: hasBlueCallback, hasRedCallback, and hasGreenCallback. Each function checks for the presence of its respective color by taking a snapshot using the vision sensor and then displaying the result on the V5 Brain's screen. The results are printed on different lines, with blue on line 1, red on line 3, and green on line 5. If an object of the respective color is found, the message

  • Download and run the project. Place different colored objects in front of the Vision Sensor and observe the robot's behavior. Record in your engineering notebook how your prediction was different or correct compared to what you actually observed from the project.

Step 3: Tuning the Vision Sensor

Often times an object is configured to be recognized by the Vision Sensor in one environment, for example, in a classroom. When the Vision Sensor is then taken into a different environment, such as a competition setting, the object may not be recognized by the Vision Sensor. This is often due to a change in lighting after the Vision Sensor has already been configured. To solve this problem, you may have to tune your Vision Sensor.

Vision Sensor configuration window with a hand holding a red cube with an overlay over the cube and text reading redbox and x84 y 28 then w 158 h 166. To the right Bluebox, Redbox, and Greenbox color signatures are set with a slider highlighted in a red box with the dial set to 4.4.

Open the previously saved Detecting Objects (Vision) example project.

How will tuning the Vision Sensor affect how well it can detect objects? Take the Clawbot to a different part of the room with more or less light.

V5 Clawbot on a Field with the arm down and the claw open and around a purple cube object.

  • Download and run the project. Place different colored objects in front of the Vision Sensor and observe the robot's behavior. Document in your engineering notebook how well the Vision Sensor detects objects. Does the Vision Sensor need tuned after it changed locations?
  • Tune the Vision Sensor as necessary. Test the Vision Sensor after it has been tuned to determine if it can detect objects better and make adjustments as needed.
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