A Docker image for the SVO Pro (visual inertial odomotery/SLAM) package, for Nvidia Jetson boards.
This is tested on Jetson Xavier NX with Jetpack 4.4 [L4T 32.4.3]
To enable access to the CUDA compiler (nvcc) during docker build
operations, add "default-runtime": "nvidia"
to your /etc/docker/daemon.json
configuration file before attempting to build the containers:
{
"runtimes": {
"nvidia": {
"path": "nvidia-container-runtime",
"runtimeArgs": []
}
},
"default-runtime": "nvidia"
}
You will then want to restart the Docker service or reboot your system before proceeding.
In Jetson, open a terminal , and execute the following commands
# Create a directory to clone this package into
mkdir -p $HOME/src && cd $HOME/src/
# Clone this package
git clone https://github.com/mzahana/jetson_svo_docker.git
Build the mzahana:jetson_svo
Docker image
cd $HOME/src/jetson_svo_docker
./scripts/setup_jetson.sh
You may need to provide passowrd for sudo
when asked
Once the image is built, you can verify that by listing Docker images docker images
. You should see mzahana:jetson_svo
availble in the listed images
An alias will be added in the ~/.bashrc
for convenience. The alias is called svo_container
. You can simply run the SVO container by executing svo_container
in a terminal window
Once the container is running, an interactive terminal inside the container can be used.
NOTE The docker image includes installations of Realsense SDK
and realsense-ros
in case the D435i cameras is to be used with VINS. Make sure to download the installRealSenseROS package on the Jetson board, and run the disableAutosuspend.sh
to turn off the USB autosuspend setting on the Jetson so that the camera is always available. Then reboot for the changes to take effect.
Description will be added soon.