1. hivecore_robot_os1

使用教程

编译

cd /home/demo/hivecore_robot_os1
# 编译指定的包
colcon build --packages-select <pkg_name>

运行

1. 启动节点

   # 启动 launch.conf 中配置的所有节点
   ./launch_robot.sh all
   
   # 仅启动特定节点（支持多个，名称对应 launch.conf 中的 pkg 或 target）
   ./launch_robot.sh <node_name1> <node_name2> ...
   # 例如: ./launch_robot.sh robot_control
   

2. 控制终端

   打开浏览器，输入 http://192.168.0.39:8080/ 启动web服务，ip地址为运行设备的ip地址
   

3. 杀掉节点

   # 杀掉所有相关节点进程
   ./kill_robot.sh all
   
   # 仅杀掉特定节点进程
   ./kill_robot.sh <node_name1> <node_name2> ...
   # 例如: ./kill_robot.sh vision_detect
   

4. 查看日志

   如果通过launch_robot.sh启动节点，日志存放在 /home/demo/hivecore_robot_os1/logs目录
   如果命令行运行节点，日志存放在 /home/demo/.ros/log目录
   

2. hivecore_robot_vision

安装教程

1. Gemini SDK:

   安装 deb 依赖项:

   # ssume you have sourced ROS environment, same blow
   sudo apt install libgflags-dev nlohmann-json3-dev  \
   ros-$ROS_DISTRO-image-transport ros-${ROS_DISTRO}-image-transport-plugins ros-${ROS_DISTRO}-compressed-image-transport \
   ros-$ROS_DISTRO-image-publisher ros-$ROS_DISTRO-camera-info-manager \
   ros-$ROS_DISTRO-diagnostic-updater ros-$ROS_DISTRO-diagnostic-msgs ros-$ROS_DISTRO-statistics-msgs \
   ros-$ROS_DISTRO-backward-ros libdw-dev
   

   安装 udev 规则

   cd  ~/workspace/src/orbbec_camera/scripts
   sudo bash install_udev_rules.sh
   sudo udevadm control --reload-rules && sudo udevadm trigger
   

2. RealSense SDK:

   sudo apt install ros-humble-librealsense2*
   

3. Dependency:

   "idge=3.2.1"
   "numpy>=1.23.0, <2.0.0",
   "matplotlib>=3.3.0",
   "opencv-python>=4.6.0",
   "pillow>=7.1.2",
   "pyyaml>=5.3.1",
   "requests>=2.23.0",
   "scipy>=1.4.1",
   "torch>=2.7.1",
   "torch>=1.8.0,!=2.4.0; sys_platform == 'win32'",
   "torchvision>=0.9.0",
   "tqdm>=4.64.0",
   "psutil",
   "py-cpuinfo",
   "pandas>=1.1.4",
   "open3d",
   

使用说明

1. 启动相机和检测节点:

    ros2 launch detect_part camera_detect.launch.py
   

   camera_detect.launch.py 中可以修改部分参数:set_confidence, output_boxes, output_masks, checkpoint_name

   坐标系设置为：Z为图像深度，XY平面为图像成象平面

2. 接收位置话题节点:

    ros2 run detect_part sub_pose_node
   

3. 位置话题接口:

    interface/msg/PoseWithID.msg, PoseWithIDArray.msg
   

4. 话题名称:

    /pose/cv_detect_pose # 位置
    /image/detect_image  # 目标识别图片
   

5. PoseWithID.msg：

    string class_name
    int32 class_id
    geometry_msgs/Pose[] pose_list
   

6. PoseWithIDArray.msg：

    PoseWithID[] objects