Eurobot-2026-Vision

This repository contains the vision system for the Eurobot 2026 competition.

Start with Docker

Build image and container

On x86 computer:

cd docker/
docker compose up -d

On nvidia jetson computer:

cd docker/
docker compose -f compose.jetson.yaml up -d 

Build workspace

Attach to the running container:

docker exec -it vision-ws bash

Inside the container, build the workspace:

source /opt/ros/humble/setup.bash
colcon build
source install/setup.bash

Realsense

Check device info

rs-enumerate-devices

Launch realsense node

Make sure the RealSense camera is connected via USB to your computer, then run:

ros2 launch realsense2_camera rs_launch.py

Check launched camera info

After launch the camera node in ros, you can check the camera info using following command:

ros2 topic echo /<your_camera_name>/<color or depth>/camera_info

If you want to launch three camera at the same time, please run:

ros2 launch realsense2_camera rs_triple_camera_launch.py

Aruco

Launch Robot detect node

ros2 launch aruco_robot robot_launch.py

Description: This launch will start three detector_node (each responsible for one of the three cameras) and one localizer_node to process and publish the detection data.

Launch Sima detect node

ros2 launch aruco_sima sima_launch.py

Description: This launch will start three detector_node (each responsible for one of the three cameras) and one localizer_node to process and publish the detection data.

GUI

Run rivz

Open RViz to visualize camera images and TF frames:

rviz2

Yolo

Run hazelnut detection

Open RViz too

ros2 launch yolo hazelnut_detect_launch.py

Set team

team:['blue', 'yellow']

ros2 param set /yolo_node_right team "blue"

Set input color mode

color_modes:['gray', 'rgb']

ros2 param set /yolo_node_right color_mode "rgb"

Set mode

modes:['region_status', 'score_predict', 'both']

ros2 param set /yolo_node_right mode "score_predict"

Set localization mode

locate_modes:["bb", "obb_dep", "obb_pnp", "obb_mix"]

ros2 param set /yolo_node_old locate_mode "obb_mix"

Set coefficients

ros2 param set /yolo_node_old co_dep_x 0.5
ros2 param set /yolo_node_old co_dep_y 0.5

Save Picture

Save RGB pictures for yolo training datasets

ros2 run yolo save_color_training_data.py

Save Depth pictures for yolo training datasets

ros2 run yolo save_depth_training_data.py