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UPS 6000 and UP Xtreme i11 Robot Kits
Create Your Own Robot Kit
Perception
Navigation
Simulation
Benchmarking and Profiling
EI for AMR Container on a Virtual Machine
Fibocom’s FM350 5G Module Integration
Change Existing and Add New Docker* Images to the EI for AMR SDK
Troubleshooting for Robot Tutorials
Spatial Partitioning and Search Operations with Octrees
Constructing a Convex Hull Polygon for a 3D Point Cloud
Detecting Specific Models and Their Parameters in 3D Point Clouds
Plane Model Segmentation
Surface Reconstruction with Intel® oneAPI Base Toolkit's Moving Least Squares (MLS)
Intel® oneAPI Base Toolkit's Iterative Closest Point (ICP)
KdTree Search Using Intel® oneAPI Base Toolkit's KdTree FLANN
Downsampling 3D Point Clouds with a Voxelized Grid
Filtering Point Clouds with a Passthrough Filter
PCL Optimizations Outside of Docker* Images
Optimized PCL Known Limitation
Optimized PCL Troubleshooting
Collaborative Visual SLAM
Kudan Visual SLAM
FastMapping Algorithm
ADBSCAN Algorithm
Run the ADBSCAN Algorithm with Slamtec* RPLIDAR Input
Run the ADBSCAN Algorithm with Intel® RealSense™ Camera Input
Troubleshooting
ITS Path Planner ROS 2 Navigation Plugin
ITS Path Planner Plugin Customization
Intel® oneAPI Base Toolkit Sample Application
Robot Teleop Using a Gamepad
Robot Teleop Using a Keyboard
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ADBSCAN Algorithm
This tutorial tells you how to run the ADBSCAN algorithm from EI for AMR using 2D Slamtec* RPLIDAR and Intel® RealSense™ camera input.
It outputs to the obstacle_array topic of type nav2_dynamic_msgs/ObstacleArray.
Prerequisites: You know how to connect and configure a Slamtec* RPLIDAR sensor. For details, see: 2D LIDAR and ROS 2 Cartographer.
Run the ADBSCAN Algorithm with Slamtec* RPLIDAR Input
Check if your installation has the amr-adbscan and amr-rplidar Docker* images.
docker images |grep amr-adbscan #if you have it installed, the result is: amr-adbscan docker images |grep amr-rplidar #if you have it installed, the result is: amr-rplidar
NOTE:If one or both of the images are not installed, continuing with these steps triggers a build that takes longer than an hour (sometimes, a lot longer depending on the system resources and internet connection).If one or both of the images are not installed, Intel recommends installing the Robot Base Kit or the Robot Complete Kit with the Get Started Guide for Robots.
Go to the AMR_containers folder:
cd <edge_insights_for_amr_path>/Edge_Insights_for_Autonomous_Mobile_Robots_*/AMR_containers
Prepare the environment setup:
source ./01_docker_sdk_env/docker_compose/common/docker_compose.source export CONTAINER_BASE_PATH=`pwd` export ROS_DOMAIN_ID=17 # Unzip the ros2 bags if they were not unzipped before unzip 01_docker_sdk_env/docker_compose/06_bags.zip -d 01_docker_sdk_env/docker_compose/ sudo chmod 0777 -R 01_docker_sdk_env/docker_compose/06_bags
Depending on the Slamtec* RPLIDAR availability, you have two possibilities:
Slamtec* RPLIDAR connected
Verify the udev rules that you configured for RPLIDAR in 2D LIDAR and ROS 2 Cartographer.
Get the Slamtec* RPLIDAR serial port:
dmesg | grep cp210x
Check for similar logs:
usb 1-3: SerialNumber: 0001 cp210x 1-3:1.0: cp210x converter detected usb 1-3: cp210x converter now attached to ttyUSB0
Export the port:
export RPLIDAR_SERIAL_PORT=/dev/ttyUSB0 # this value may differ from system to system, use the value returned in the previous step
Start a pre-configured yml file that starts the LIDAR Node and then the ADBSCAN application:
CHOOSE_USER=eiforamr docker-compose -f 01_docker_sdk_env/docker_compose/05_tutorials/adbscan_LIDAR.tutorial.yml up
No Slamtec* RPLIDAR connected
Start a pre-configured yml file that plays a ROS 2 bag containing LIDAR data and then the ADBSCAN application:
CHOOSE_USER=eiforamr docker-compose -f 01_docker_sdk_env/docker_compose/05_tutorials/adbscan_2D.tutorial.yml up
Expected output: ADBSCAN prints logs of its interpretation of the LIDAR data coming from the ROS 2 bag.
Run the ADBSCAN Algorithm with Intel® RealSense™ Camera Input
Check if your installation has the amr-adbscan and amr-realsense Docker* images.
docker images |grep amr-adbscan #if you have it installed, the result is: amr-adbscan docker images |grep amr-realsense #if you have it installed, the result is: amr-realsense
NOTE:If one or both of the images are not installed, continuing with these steps triggers a build that takes longer than an hour (sometimes, a lot longer depending on the system resources and internet connection).If one or both of the images are not installed, Intel recommends installing the Robot Base Kit or Robot Complete Kit with the Get Started Guide for Robots.
Go to the AMR_containers folder:
cd <edge_insights_for_amr_path>/Edge_Insights_for_Autonomous_Mobile_Robots_<version>/AMR_containers
Prepare the environment setup:
source ./01_docker_sdk_env/docker_compose/common/docker_compose.source export CONTAINER_BASE_PATH=`pwd` export ROS_DOMAIN_ID=17 # Unzip the ros2 bags if they were not unzipped before unzip 01_docker_sdk_env/docker_compose/06_bags.zip -d 01_docker_sdk_env/docker_compose/ sudo chmod 0777 -R 01_docker_sdk_env/docker_compose/06_bags
Depending on the Intel® RealSense™ camera availability, you have two possibilities:
Intel® RealSense™ camera connected
Start a pre-configured yml file that starts the Intel® RealSense™ node and then the ADBSCAN application:
CHOOSE_USER=eiforamr docker-compose -f 01_docker_sdk_env/docker_compose/05_tutorials/adbscan_RealSense.tutorial.yml up
No Intel® RealSense™ camera connected
Start a pre-configured yml file that plays a ROS 2 bag containing Intel® RealSense™ data and then the ADBSCAN application:
CHOOSE_USER=eiforamr docker-compose -f 01_docker_sdk_env/docker_compose/05_tutorials/adbscan_RS.tutorial.yml up
Expected result: rviz2 starts, and you see how ADBSCAN interprets Intel® RealSense™ data coming from the ROS 2 bag:
Troubleshooting
For general robot issues, go to: Troubleshooting for Robot Tutorials.
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