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README.md

AIRobot Docker Instructions

Dependencies

System dependencies:

  • Linux OS (tested on Ubuntu 16.04 and 18.04)
  • Nvidia GPU
  • Nvidia driver version >= 418.39

Local Docker engine setup

Install Docker (you may want to configure your user permissions so you don't have to use sudo with every docker command -- see here)

sudo apt-get remove docker docker-engine docker.io containerd runc
sudo apt-get update
sudo apt-get install \
    apt-transport-https \
    ca-certificates \
    curl \
    gnupg-agent \
    software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository \
   "deb [arch=amd64] https://download.docker.com/linux/ubuntu \
   $(lsb_release -cs) \
   stable"
sudo apt-get update
sudo apt-get install docker-ce docker-ce-cli containerd.io

Install nvidia-container-runtime (main instructions from the link shown below)

curl -s -L https://nvidia.github.io/nvidia-container-runtime/gpgkey | \
  sudo apt-key add -
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-container-runtime/$distribution/nvidia-container-runtime.list | \
  sudo tee /etc/apt/sources.list.d/nvidia-container-runtime.list
sudo apt-get update
sudo apt-get install nvidia-container-runtime

Follow the steps for creating a drop in file to register the runtime with docker

sudo mkdir -p /etc/systemd/system/docker.service.d
sudo tee /etc/systemd/system/docker.service.d/override.conf <<EOF
[Service]
ExecStart=
ExecStart=/usr/bin/dockerd --host=fd:// --add-runtime=nvidia=/usr/bin/nvidia-container-runtime
EOF
sudo systemctl daemon-reload
sudo systemctl restart docker

Pulling the Pre-Built Images

The image is set up with CUDA 10.1, cuDNN 7.6, and PyTorch 1.3 installed (airobot-cuda-dev)

docker pull anthonysimeonov/airobot-cuda-dev:latest

Usage

Running the container

Open two terminals

Terminal 1

In the first terminal, from within this directory (/path/to/airobot/docker/), run the run_image.bash script to launch the container. You will enter a terminal session from within the container after launching.

./run_image.bash

Termainal 2

From the second terminal, run the following bash script to allow the container access to your local X server for visualization (there are better ways to do this, but we keep this relatively secure by only providing access to xhost to the specific system we want)

./visualize_access.bash

You can now run programs from within the container that are GUI-based, and have the GUI appear on your host screen (i.e. Gazebo, RViz, PyBullet)

First, enter the container by starting a new interactive terminal session ($CONTAINER_ID can usually be found by tab completing the below command, or viewing the information about the running containers by running docker ps) and source the catkin workspace that has been built with the following commands

docker exec -it $CONTAINER_ID bash

Run the simulated UR robot in Gazebo

Then, for instance, you can launch a simulated UR5e in Gazebo, and start MoveIt! with it, with the following command

roslaunch ur5e_bringup ur5e_start.launch sim:=true

Or you can launch a simulated UR5e in PyBullet with airobot with the following commands

cd /home/improbable/airobot/examples/ur5e/sim/
python joint_position_control.py

Run the real UR robot

You can also connect to the real robot and control it via the airobot API functions (<robot_ip> can be viewed from the PolyScope interface on the real robot's teach pendant. First bringup the connection to the robot with the following command, after connecting to the local network via ethernet cable (more instructions avaiable here).

roslaunch ur5e_bringup ur5e_start.launch robot_ip:=<robot_ip>

Then run the following command to run the joint_position_control example (from a new terminal, either using tmux or by entering the container from a new local terminal with the same docker exec command above)

cd /home/improbable/airobot/examples/ur5e/real/
python joint_position_control.py

Build the Image Locally

From within this directory (/path/to/airobot/docker/), run the following command to build the image. This will take quite a bit of time if you have not done it locally before. Please see the docker_build.py script for additional arguments that can be passed to the build command (i.e. image name, which file to use, dry run, etc.)

python docker_build.py

If you want to use a different dockerfile than the specified default, run

python docker_build.py -f /path/to/dockerfile.dockerfile

(if you are building the image locally you will need to set up your machine with public keys linked to your github account for cloning private repositories required during building)