1. 感知系统架构

为满足天空端主控制器的诸如RGB-D图像处理等大容量数据吞吐、高速并行计算、实时运动控制以及通信和可视化任务的计算算力需求，同时优化功耗表现，采用了结构紧凑、功耗表现优异的边缘计算硬件NVIDA IJetson AGXOrin 。该开发者套件包含高性能、高能效的 Jetson AGX Orin 模组，算力高达 275 TOPS是上一代多个并发 AI 推理管道性能的 8 倍，运行于 NVIDIA AI 软件堆栈，广泛应用于图像处理、嵌入式控制、并行计算等场景，可以为机器人、制造、控制和电力等行业打造先进的机器人和边缘 AI 应用。系统架构如图所示。

2. Realsense2 D435i & USB Monocular

1. librealsense & realsense2_camera ROS package

• 安装SDK库：

librealsense: V2.50.0 + https://github.com/IntelRealSense/librealsense/releases/tag/v2.50.0

在/home下进入librealsense,并安装依赖项

cd librealsense
sudo apt-get install libudev-dev pkg-config libgtk-3-dev
sudo apt-get install libusb-1.0-0-dev pkg-config
sudo apt-get install libglfw3-dev
sudo apt-get install libssl-dev

• 安装依赖：

安装依赖项和编译

sudo cp config/99-realsense-libusb.rules /etc/udev/rules.d/
sudo udevadm control --reload-rules && udevadm trigger 
mkdir build
cd build
cmake ../ -DBUILD_EXAMPLES=true
make
sudo make install

测试安装结果

这时候可以连接摄像头了，输入以下命令查看结果

realsense-viewer 

如果成功，可以看到点云图像

• 编译ROS PKG:

在工作空间src下克隆项目：

cd ~/catkin_ws/src
git clone https://github.com/IntelRealSense/realsense-ros.git
git clone https://github.com/pal-robotics/ddynamic_reconfigure.git
cd ~/catkin_ws && catkin_make

ROS中测试

roslaunch realsense2_camera rs_camera.launch 

• ERROR：undefined symbol: _ZN2cv3MatC1Ev【librealsense2_camera.so: undefined symbol: _ZN2cv3MatC1Ev】

https://github.com/IntelRealSense/realsense-ros/issues/2467

• 解决方法：

Now im testing this solution but it looks promising. (even work with -DFORCE_RSUSB_BACKEND:=false):find_package( OpenCV REQUIRED )
include_directories(
include
${realsense2_INCLUDE_DIR}
${catkin_INCLUDE_DIRS}
${OpenCV_INCLUDE_DIRS}
)
target_link_libraries(${PROJECT_NAME}
${realsense2_LIBRARY}
${catkin_LIBRARIES}
${CMAKE_THREAD_LIBS_INIT}
${OpenCV_LIBRARIES}
)

修改后重新编译，加参数 -DFORCE_RSUSB_BACKEND:=false

catkin_make  install -DFORCE_RSUSB_BACKEND:=false

2. usb_cam ROS package

• ROS.org usb_cam介绍http://wiki.ros.org/usb_cam

• 安装usb 相机驱动程序ROS功能包：

sudo apt-get install ros-melodic-usb-cam
或sudo apt-get install ros-noetic-usb-cam

• 参数表：

• launch文件

<launch>
<!--Launch Usb Camera via usb_cam package --><node name="usb_cam" pkg="usb_cam" type="usb_cam_node" output="screen" ><param name="video_device" value="/dev/Monocular" /><param name="image_width" value="640" /><param name="image_height" value="480" /><param name="pixel_format" value="yuyv" /><param name="camera_frame_id" value="usb_cam" /><param name="io_method" value="mmap"/></node><node name="image_view" pkg="image_view" type="image_view" respawn="false" output="screen"><remap from="image" to="/usb_cam/image_raw"/><param name="autosize" value="true" /></node>
</launch>

3. RVIZ

• 数据及图像可视化节点，实时显示目标检测结果和视觉传感器图像

<launch>
<!-- Launch Multi-sensor drivers and filters, with Lidar range sensor and Usb Camera  --><!-- Loading param files  --><rosparam file="$(find multisensor_fusion)/cfg/sensor_cfg.yaml" command="load" /><!--<rosparam file="$(find multisensor_fusion)/cfg/ros_pkg_info.yaml" command="load" />--><!--Launch USB 2.0 Camera launch file --><include file="$(find contact_force)/launch/contact_force_launch.launch"></include><include file="$(find multisensor_fusion)/launch/usb_camera_launch.launch"></include><!-- Launch network state monitor and publisher node --><nodename="pub_range_sensor"pkg="multisensor_fusion"type="pub_range_sensor_pub.py" /><nodename="pub_actuator_power"pkg="multisensor_fusion"type="pub_actuator_effort.py" /><nodename="sensor_status"pkg="multisensor_fusion"type="sensor_status" /><!-- Launch rivz display --><!--<node name="rviz" pkg="rviz" type="rviz" args="-d $(find dual_arm_robot_description)/rviz/dual_arm.rviz" output="screen" />--></launch>

3.GUI &集成控制终端

1. 通信架构

2. 系统功能