Setting Up the Agipix Simulation Environment

Prerequisites for host PC

Ubuntu 20.04/22.04 Operating System
NVIDIA GPU (RTX 2070 or higher)
NVIDIA GPU Driver (recommended version 525.85)

Cuda and CUDnn

!! Importat: Always use the given liks to get the latest deb package links wt is statud here may be outdated.

Install cuda with the instructions here

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin
sudo mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda-repo-ubuntu2204-12-8-local_12.8.0-570.86.10-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu2204-12-8-local_12.8.0-570.86.10-1_amd64.deb
sudo cp /var/cuda-repo-ubuntu2204-12-8-local/cuda-*-keyring.gpg /usr/share/keyrings/
sudo apt-get update
sudo apt-get -y install cuda-toolkit-12-8

Install Cudnn with the instructions here

wget https://developer.download.nvidia.com/compute/cudnn/9.18.1/local_installers/cudnn-local-repo-ubuntu2204-9.18.1_1.0-1_amd64.deb
sudo dpkg -i cudnn-local-repo-ubuntu2204-9.18.1_1.0-1_amd64.deb
sudo cp /var/cudnn-local-repo-ubuntu2204-9.18.1/cudnn-*-keyring.gpg /usr/share/keyrings/
sudo apt-get update
sudo apt-get -y install cudnn

echo 'export PATH=/usr/local/cuda-12.8/bin:$PATH' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=/usr/local/cuda-12.8/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc

Verify

nvcc -V
cd $HOME/workspace/raicam-ros/src/isaac_ros_common/verify
g++ verify_cuda_cudnn.cpp \
    -I/usr/local/cuda-12.8/targets/x86_64-linux/include \
    -L/usr/local/cuda-12.8/targets/x86_64-linux/lib \
    -lcudart -lcudnn -o verify_cuda_cudnn
./verify_cuda_cudnn

Building Containerised Development platform

The containerised development platform is shared by both sim and real hardware. This improve the deployability from sim to real with minimal code change.

Curent release uses Nvidia Isaac Ros 3.2 as the basis for this platform

Prerequisities

Finish Flasing Hadrware or setting up Sim host.

1) Install Docker + NVIDIA Container Toolkit + Git LFS

Install docker with

Guide from JetsonHacks

cd hacks
git clone https://github.com/jetsonhacks/install-docker.git
cd install-docker
bash ./install_nvidia_docker.sh
bash ./configure_nvidia_docker.sh

Or use

Docker: https://docs.docker.com/engine/install/ubuntu/
NVIDIA Container Toolkit: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html

Git LFS: https://git-lfs.com/

curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash
# Install Git LFS
sudo apt update
sudo apt install git-lfs -y

# Initialize Git LFS for your user
git lfs install

To verify CDI interfaces sudo nvidia-ctk cdi list should output

INFO[0000] Found 2 CDI devices                          
nvidia.com/pva=0
nvidia.com/pva=all

if no CDI devices are found

sudo apt-get install -y nvidia-container-toolkit
sudo systemctl restart docker

2) Setup Workspace

cd $HOME
mkdir workspace && cd workspace
mkdir -p agipix_control/src dds lidar_ws/src raicam-ros/src ui/src logging/bags logging/flogs logging/crashreports
cd raicam-ros/src
git clone https://github.com/SasaKuruppuarachchi/isaac_ros_common.git # TODO

echo "export WORKSPACES_DIR="$HOME/workspace"" >> ~/.bashrc
echo "export ISAAC_ROS_DEV_DIR="$HOME/workspace/raicam-ros"" >> ~/.bashrc
echo "alias agidocker='cd $HOME/workspace/raicam-ros/src/isaac_ros_common/scripts/ && ./run_dev.sh --skip-registry-check'" >> ~/.bashrc
echo "alias killagidocker='docker container kill isaac_ros_dev-x86_64-container'" >> ~/.bashrc
source ~/.bashrc

3) Build Docker

In this step we pull source images and build the docker continer.

To customise the docker configuration edit and append the additional docker configuration layers you need built
```
  code ~/workspace/raicam-ros/src/isaac_ros_common/scripts/.isaac_ros_common-config
```

Change the ROS_DOMAIN_ID to 3 (To mactch the sim environment)

  code ~/workspace/raicam-ros/src/isaac_ros_common/scripts/bashrc

Build the Docker

cd ~/workspace/raicam-ros/src/isaac_ros_common/scripts/ && ./run_dev.sh # this alias builds the container

The build will take more than an hour and if successfull you will see Running isaac_ros_dev-aarch64-container and the container will start running in the background.

Run agidocker to attach to the container interactively.

Verify Pytorch with cuda on dcker

agidocker
# Inside docker
python3 - << 'EOF'
import torch
print("CUDA:", torch.cuda.is_available())
print("Device:", torch.cuda.get_device_name(0))
EOF

(Optional) Installing Portainer CE

Portainer CE is an open-source GUI for creating and managing docker containers. Install it following these instructions

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