Hi Why don't you use the SVL simulator instead of LGSVL? This is an old version...also you should use the simulator externally, not inside the docker image (you can use but is not good to develop). Then later you could just connect with ROS/Autoware using the ros2-web-bridge or lgsvlbridge.....
But I believe the issue is regarding the need to install the libvulkan. For me at least it worked. Take a look on this link: https://zoomadmin.com/HowToInstall/Ub...
The cmds in this link should solve your issue. I have also used Autoware.Auto with LGSVL internally and had lot of problems. I needed to work around their .aderc file and customize the image to be built properly.
You can open your .aderc-amd64-foxy-lgsvl file inside adehome/AutowareAuto folder (HINT: Use Ctrl+h to enable visualization of the hidden files in this folder) ERASE all the lines and then copy and paste the lines below:
export ADE_DOCKER_RUN_ARGS="--cap-add=SYS_PTRACE --net=host --privileged --add-host ade:127.0.0.1 -e RMW_IMPLEMENTATION=rmw_cyclonedds_cpp"
export ADE_GITLAB=gitlab.com
export ADE_REGISTRY=registry.gitlab.com
export ADE_IMAGES="
registry.gitlab.com/autowarefoundation/autoware.auto/autowareauto/amd64/ade-foxy:master
registry.gitlab.com/autowarefoundation/autoware.auto/autowareauto/amd64/binary-foxy:master
registry.gitlab.com/autowarefoundation/autoware.auto/ade-lgsvl/foxy:2020.06
"
Afterwards just start and enter the image again.
You must be aware that you need to ALWAYS remove the line that enable the Nvidia is set to True (Take a look if you have this line in your .aderc file) and enable to false or remove (as I always do):
export ADE_DOCKER_RUN_ARGS="--cap-add=SYS_PTRACE --net=host --privileged --add-host ade:127.0.0.1 -e RMW_IMPLEMENTATION=rmw_cyclonedds_cpp --runtime=nvidia -ti --rm -e DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix \
-e NVIDIA_VISIBLE_DEVICES=all \
-e NVIDIA_DRIVER_CAPABILITIES=compute,utility,display"
export ADE_GITLAB=gitlab.com
export ADE_REGISTRY=registry.gitlab.com
export ADE_DISABLE_NVIDIA_DOCKER=false
export ADE_IMAGES="
registry.gitlab.com/autowarefoundation/autoware.auto/autowareauto/amd64/ade-foxy:master registry.gitlab.com/autowarefoundation/autoware.auto/autowareauto/amd64/binary-foxy:master
registry.gitlab.com/autowarefoundation/autoware.auto/ade-lgsvl/foxy:2020.06
nvidia/cuda:11.0-base
"
You can take a look here too for more deeper understanding of Nvidia driver issues: https://gitlab.com/autowarefoundation...
Finally if the lgsvl was still not enabled you should clean your Autoware.Auto system and re-compile, rebuild...It is quicker just follow the "CLEANUP" topic here: https://autowarefoundation.gitlab.io/...
Or better follow "Start from clean State" topic here: https://autowarefoundation.gitlab.io/...
I hope you can enable the lgsvl inside docker :)
What kind of GPU does your host machine have? What OS/kernel is it running? The one thing I didn't see you mention installing is the Nvidia proprietary graphics driver. Can you run
nvidia-smion your host and post the output?I have the following setup: - Ubuntu 18.04 - kernel 5.4.0-67-generic - nvidia driver 450.102.04 - cuda 11.0 - gpu is Quadro P4000 - nvidia-smi gives this output from host: https://gitlab.com/-/snippets/2095278 - result is similar from ade except no Processes are detected
This one may need help from LG. Can you please create a new snippet with the contents of the file
.config/unity3d/LG Silicon Valley Lab/LGSVL Simulator/player.login youradehomefolder? This is the log from the simulator and may help with troubleshooting.https://gitlab.com/-/snippets/2097364 According to the logs it seems it is just the vulkan drivers that dont work
vulkaninfo also give me an error: WARNING: [Loader Message] Code 0 : loader_icd_scan: Can not find 'ICD' object in ICD JSON file /usr/share/vulkan/icd.d/nvidia_layers.json. Skipping ICD JSON /build/vulkan-tools-136mCR/vulkan-tools-1.1.126.0+dfsg1/vulkaninfo/vulkaninfo.h:399: failed with ERROR_INITIALIZATION_FAILED
The first warning line is explained here: https://vulkan.lunarg.com/issue/home?... Moving the file /usr/share/vulkan/icd.d/nvidia_layers.json away does not fix the issue
As for the ERROR_INITIALIZATION_FAILED error, people usually face this issue when their GPU is too old and cannot support vulkan. According to this page: https://developer.nvidia.com/vulkan-d..., the Quadro P4000 is supposed to be supported
But after some more digging I realized some people had similar vulkan issues when using X forwarding. Nowadays I am working remotely using chrome-remote-desktop and it seems vulkan does not support such use case: https://askubuntu.com/questions/12311...
However the comment provides some workaround. I will try it out later