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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
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GStreamer* Video Pipeline with an Intel® RealSense™ Camera
Run a GStreamer* video pipeline using the Intel® RealSense™ plugin in a Docker* container in order to use a Intel® RealSense™ video camera as the video source.
Run the Sample Pipeline
Connect an Intel® RealSense™ video camera.
Check if your installation has the amr-gstreamer Docker* image.
docker images |grep amr-gstreamer #if you have it installed, the result is: amr-gstreamer
NOTE:If the image is 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 the image is 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=45 sudo chmod a+rw /dev/video*
Get the stream from the Intel® RealSense™ camera using gstreamer:
CHOOSE_USER=eiforamr docker-compose -f 01_docker_sdk_env/docker_compose/05_tutorials/gstreamer_realsensesrc.tutorial.yml up
Expected output: The stream from the Intel® RealSense™ is displayed.
To close this, do one of the following:
Type Ctrl-c in the terminal where you did the up command.
Run this command in another terminal:
CHOOSE_USER=eiforamr docker-compose -f 01_docker_sdk_env/docker_compose/05_tutorials/gstreamer_realsensesrc.tutorial.yml down
For an explanation of what happened, open the yml file:
The first 23 lines are from the EI for AMR infrastructure.
Line 26 gets the stream from the Intel® RealSense™ app using GStreamer*.
Troubleshooting
In some cases, the stream may not appear due to permission issues on the host. You may see this error message:
ERROR: Pipeline doesn't want to pause.
To fix this, if you did not install the librealsense udev rules when you configured the host, install them now:
git clone https://github.com/IntelRealSense/librealsense # Copy the 99-realsense-libusb.rules files to the rules.d folder cd librealsense sudo cp config/99-realsense-libusb.rules /etc/udev/rules.d/ sudo udevadm control --reload-rules sudo udevadm trigger
Then open the gst-launch command.
If the problem persists, you can try any or all of the following:
Verify that $DISPLAY has the correct value.
Perform a Intel® RealSense™ hardware reset:
# Open realsense docker container docker-compose -f 01_docker_sdk_env/docker_compose/01_amr/amr-sdk.all.yml run realsense bash # While in realsense container, open the realsense-viewer application realsense-viewer # In realsense-viewer menu, go to "More" and then select "Hardware Reset" # Wait for reset to complete and then close the realsense-viewer application.
Reboot the target.
For general robot issues, go to: Troubleshooting for Robot Tutorials.
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