Checkpoint 4

Last Updated: Nov 13, 2025

The MBot is equipped with a camera that can be used for vision-based tasks, such as identifying AprilTags and detecting obstacles in the environment.

Computer Vision

Find a checkerboard in the lab.

The checkerboard size is defined by the number of intersections, not the number of squares.

For example, size 8x6 means the board has 8 intersections along one dimension and 6 along the other, corresponding to a grid of 9×7 squares. You’ll need this information for calibration.

Run the camera node in the VSCode Terminal:

 ros2 run camera_ros camera_node --ros-args \
 -p orientation:=180 \
 -p width:=640 -p height:=480 \
 -p format:=BGR888

On NoMachine, run the following command, the GUI will pop up.
```
 ros2 run camera_calibration cameracalibrator \
 --size 6x8 --square 0.025 --ros-args -r image:=/camera/image_raw -p camera:=/camera
```
- --size specifies the number of intersections (as noted in Step 1).
- --square defines the size of each checkerboard square in meters.
- Adjust the values based on your checkerboard. 0.025 means each square is 25 mm.
How to use the calibrator GUI? Refer to the ROS2 Camera Calibration Tutorial
- Start reading from: Tutorial Steps → Step 5: Start the camera calibration node.
Once calibration is complete, move the results to your MBot workspace by running the following commands:
```
 cp /tmp/calibrationdata.tar.gz ~/mbot_ws/src/mbot_vision
 cd ~/mbot_ws/src/mbot_vision
 tar -xvf calibrationdata.tar.gz -C calibration/
```
- This will unzip the calibration results to ~/mbot_ws/src/mbot_vision/calibration.
Rebuild the packages so the calibration file is accessible system-wide:
```
 cd ~/mbot_ws
 colcon build
 source install/setup.bash
```

To save time on ros2 run all the node individually, you can use the provided launch files.

To launch camera node only, run the following in the VSCode Terminal:
```
  ros2 launch mbot_vision camera.launch.py
```
- This will publish topics /camera/image_raw and /camera/camera_info
- You can view the camera feed in rqt on NoMachine or Foxglove after launching this node.
To launch the camera with image rectification using the calibration results (camera node + rectification node), run the following in the VSCode Terminal:
```
  ros2 launch mbot_vision camera_rectify.launch.py
```
- You need to do camera calibration first to run the rectification node. It needs the camera info.
- This will also publish the topic /image_rect
- You can view the camera feed in both raw and rectified in rqt after launching these 2 nodes.
To launch full vision pipeline (camera + rectification + AprilTag detection), run the following in the VSCode Terminal:
```
  ros2 launch mbot_vision apriltag.launch.py
```
- This will also publish AprilTag detection results on /detections

No submission is required for this checkpoint.

However, ensure your camera can successfully detect AprilTags, you’ll need this for the competition.