View source for Advantech Robotic Suite/Robotic System/AFE-R360 AFE-R760/Quick Start

= Introduction =
This page provides a Quick Start guide and practical tutorials specifically designed for the Autonomous Mobile Robot (AMR) domain. Whether you are new to ROS2 or an experienced developer, you can follow the clear step-by-step instructions to quickly get started and experience the rich features of the AMR software platform. Equipped with the Advantech Robotic Suite, the system is specially designed for AMR applications based on the ROS2 architecture, offering optimal solutions for smart logistics, automated warehousing, and related fields.

= Tutorials 1: Explore Installed Robotic Node =
== Summary ==
In this tutorial, we will introduce how to use the Web UI to quickly access detailed hardware and software information in the system, including device info and ROS2 node list.
== Step ==
* Step 1: Open your browser and go to <code>127.0.0.1:8081</code>
* Step 2: Enter the default Password <code>P@ssw0rd</code> then login
[[File:Robotic-suite-quickstart-tutorials1_01.png|none|Robotic-suite-quickstart-tutorials1_01.png]]
* Step 3: Recommended to change the password first
[[File:Robotic-suite-quickstart-tutorials1_04.png|1000px|none|Robotic-suite-quickstart-tutorials1_04.png]]<br>
[[File:Robotic-suite-quickstart-tutorials1_05.png|1000px|none|Robotic-suite-quickstart-tutorials1_05.png]]
* Step 4: This page will display some system information
[[File:Robotic-suite-quickstart-tutorials1_02.png|1000px|none|Robotic-suite-quickstart-tutorials1_02.png]]
* Step 5: Next, select "ROS Nodes" from the list on the left
The <code>vertical</code> page will show open-source ROS2 nodes focused on the AMR field, for more information please refer to [[Advantech_Robotic_Suite/Robotic_System/AMR_SDK|AMR SDK]]
[[File:Robotic-suite-quickstart-tutorials1_03.png|1000px|none|Robotic-suite-quickstart-tutorials1_03.png]]
The <code>vendor</code> page will show a list of nodes from the Intel Robotics SDK, for more information please refer to [https://amrdocs.intel.com/docs/2.2/index.html Intel Robotic SDK 2.2]
[[File:Robotic-suite-quickstart-tutorials1_06.png|1000px|none|Robotic-suite-quickstart-tutorials1_06.png]]

= Tutorials 2: Use Muilt Sensors on Time Sync Viewer =
== Summary ==
In this tutorial, We will publish fake sensor data, including camera, IMU, and LiDAR(you can also use actual sensors). Then display the timestamps in rqt and observe the time synchronization status of the multiple sensors.

For detailed instructions, please refer to [[Advantech_Robotic_Suite/Time_Sync_Viewer|Time Sync Viewer]]
[[File:Robotic-suite-quickstart-tutorials2_06.png|1000px|none|Robotic-suite-quickstart-tutorials2_06.png]]

= Tutorials 3: Show Camera and 3D Lidar Data on Rviz =
== Summary ==
In this tutorial, we will first download a sample rosbag that contains camera and 3D LiDAR data. Then, we will read and display these data in RViz, allowing users to visualize the contents of the sensor data.
== Step ==
* Step 1: Download example bagfile (About 1.4GB)
<pre>
wget https://iedgeblob.blob.core.windows.net/iedge-public/rosbag-dataset/2011_09_26_drive_0039.tar.gz
tar zxvf 2011_09_26_drive_0039.tar.gz
</pre>
* Step 2: Play example bagfile in terminal
<pre>
ros2 bag play 2011_09_26_drive_0039/ -l
</pre>
* Step 3: Run rviz2 in another terminal
<pre>
rviz2
</pre>
* Step 4: Add image topic on Rviz
[[File:Robotic-suite-quickstart-tutorials3_01.png|1000px|none|Robotic-suite-quickstart-tutorials3_01.png]]
* Step 5: Add lidar topic on Rviz
[[File:Robotic-suite-quickstart-tutorials3_02.png|1000px|none|Robotic-suite-quickstart-tutorials3_02.png]]
* Step 6: Set parameters for correct display of pointcloud data
: 1. Set <code>Fixed Frame</code> to <code>velodyne</code>
: 2. Set <code>Style</code> to <code>Points</code>
: 3. Set <code>Size (Pixels)</code> to <code>2</code>
* Result:
[[File:Robotic-suite-quickstart-tutorials3_03.png|1000px|none|Robotic-suite-quickstart-tutorials3_03.png]]

= Tutorials 4: Create a 2D Map using SLAM =
== Summary ==
In this tutorial, we will demonstrate how to quickly use Cartographer to build a 2D map. We will first download a sample rosbag that contains Laser LiDAR data, and then show how to configure Cartographer’s parameters and start the mapping process. Finally, we will use RViz to observe the mapping progress and results in real time, allowing users to quickly get started with the 2D SLAM process and create their own maps.

For more information please refer to [https://github.com/cartographer-project/cartographer_ros cartographer_ros]
== Step ==
* Step 1: Download example bagfile
<pre>
mkdir ~/slam_example
cd ~/slam_example
wget https://iedgeblob.blob.core.windows.net/iedge-public/rosbag-dataset/rosbag2_2023_08_04-10_54_23.tar.gz
tar zxvf rosbag2_2023_08_04-10_54_23.tar.gz
</pre>
* Step 2: Download lua file
<pre>
cd ~/slam_example
wget -O 2d_slam_example.lua https://iedgeblob.blob.core.windows.net/iedge-public/robotic_suite_share_folder/2d_slam_example.lua
</pre>
* Step 3: Run SLAM node
<pre>
cd ~/slam_example
ros2 launch cartographer_ros offline_backpack_2d.launch.py bag_filenames:=rosbag2_2023_08_04-10_54_23 configuration_directory:=./ configuration_basenames:=2d_slam_example.lua
</pre>
* Result:
[[File:Robotic-suite-quickstart-tutorials5_01.png|1000px|none|Robotic-suite-quickstart-tutorials5_01.png]]

= Tutorials 5: Run Object Detection with OpenVINO in Intel Robotics SDK =
== Summary ==
In this tutorial, you will learn how to easily run object detection using Intel OpenVINO(Intel OpenVINO is a powerful feature included in the Intel Robotics SDK), we will guide you through downloading a pre-trained model and launching the object detection program. For this tutorial, instead of using live camera data, we will use a rosbag file as the data source. 

For more information please refer to [https://github.com/intel/ros2_openvino_toolkit/tree/ros2 ros2_openvino_toolkit]
== Step ==
* Step 1: Download example bagfile (About 2.2GB)
<pre>
wget https://iedgeblob.blob.core.windows.net/iedge-public/rosbag-dataset/103.tar.gz
tar zxvf 103.tar.gz
</pre>
* Step 2: Play example bagfile in terminal
<pre>
ros2 bag play -l 103 --remap cam_front/raw:=/openvino_toolkit/image_raw
</pre>
* Step 3: Download ssdlite_mobilenet_v2 model
<pre>
mkdir /opt/ros/humble/share/openvino_node/model
cd /opt/ros/humble/share/openvino_node/model
wget https://iedgeblob.blob.core.windows.net/iedge-public/share-folder/ssdlite_mobilenet_v2.tar.gz
tar zxvf ssdlite_mobilenet_v2.tar.gz
</pre>
* Step 4: Download openvino_node param
Download <code>pipeline_object_topic.yaml</code>
<pre>
cd /opt/ros/humble/share/openvino_node/param
wget -O pipeline_object_topic.yaml https://iedgeblob.blob.core.windows.net/iedge-public/robotic_suite_share_folder/pipeline_object_topic.yaml
</pre>
* Step 5: Run openvino_node in another terminal
<pre>
ros2 launch openvino_node pipeline_object_topic.launch.py
</pre>
* Result:
[[File:Robotic-suite-quickstart-tutorials4_01.png|1000px|none|Robotic-suite-quickstart-tutorials4_01.png]]

<!--
= Tutorials 5: Create a 3D Map using 3D SLAM =
== Summary ==
In this tutorial, we will demonstrate how to quickly use LIO-SAM to build a 3D map. We will first download a sample rosbag that contains 3D LiDAR data, and then show how to configure LIO-SAM’s parameters and start the mapping process. Finally, we will use RViz to observe the mapping progress and results in real time, allowing users to quickly get started with the 3D SLAM process and create their own maps.
== Build ==
<pre>
cd /usr/local/Advantech/ros/humble/AMR_extension/LIO-SAM
colcon build --symlink-install
</pre>
== Step ==
* Step 1: Download example bagfile(same bagfile as tutorial 3, you can skip this if you are downloading)
<pre>
wget https://iedgeblob.blob.core.windows.net/iedge-public/rosbag-dataset/2011_09_26_drive_0039.tar.gz
tar zxvf 2011_09_26_drive_0039.tar.gz
</pre>
* Step 2: Play example bagfile in terminal
<pre>
ros2 bag play 2011_09_26_drive_0039/
</pre>
* Step 3: Run SLAM node
<pre>
cd /usr/local/Advantech/ros/humble/AMR_extension/LIO-SAM
source install/setup.bash
ros2 launch lio_sam run.launch.py
</pre>
[[File:Robotic-suite-quickstart-tutorials3_01.png|1000px|none|Robotic-suite-quickstart-tutorials3_01.png]]
* Result:
[[File:Robotic-suite-quickstart-tutorials3_03.png|1000px|none|Robotic-suite-quickstart-tutorials3_03.png]]
-->