Merge branch 'main' into jturco/env_debian_frontend

.github/templates/docker_context/docker_context.sh

@@ -24,6 +24,11 @@ while read -r module; do
     services=$(docker-compose -f "$module" config --services)
     module_out=$(echo "$module" | sed -n 's/modules\/docker-compose\.\(.*\)\.yaml/\1/p')
 
+    # Skip simulation module
+    if [[ 'simulation' = $module_out ]]; then
+        continue
+    fi
+
     # Only work with modules that are modified
     if [[ $MODIFIED_MODULES != *$module_out* && $TEST_ALL = "false" ]]; then
         continue

.github/workflows/build_and_unitest.yml

@@ -10,7 +10,7 @@ on:
 
 jobs:
   setup-environment:
-    name: Setup environment
+    name: Setup Environment
     runs-on: ubuntu-latest
 
     outputs:
@@ -29,7 +29,9 @@ jobs:
         uses: "./.github/templates/check_src_changes"
 
       - name: Setup Watod Environment
-        run: ./watod_scripts/watod-setup-env.sh
+        run: |
+          MODULES_DIR="$GITHUB_WORKSPACE/modules"
+          . ./watod_scripts/watod-setup-env.sh
         shell: bash
 
       - name: Generate Docker Environment
@@ -43,7 +45,7 @@ jobs:
         uses: "./.github/templates/github_context"
 
   build-and-unittest:
-    name: Build Image and Run Unit Testing Suite
+    name: Build/Test
     runs-on: ubuntu-latest
     needs: setup-environment
 
@@ -124,9 +126,7 @@ jobs:
             ${{ steps.construct-registry-url.outputs.url }}:${{ env.SOURCE_BRANCH }}
           cache-from: |
             ${{ steps.construct-registry-url.outputs.url }}:build_${{ env.SOURCE_BRANCH }}
-            ${{ steps.construct-registry-url.outputs.url }}:${{ env.SOURCE_BRANCH }}
-            ${{ steps.construct-registry-url.outputs.url }}:${{ env.TARGET_BRANCH }}
-          cache-to: type=inline
+            ${{ steps.construct-registry-url.outputs.url }}:build_${{ env.TARGET_BRANCH }}
           builder: ${{ steps.buildx.outputs.name }}
           target: deploy
 

.gitignore

@@ -6,3 +6,5 @@ code_server_config/*/start_code_server.sh
 .env
 .vscode/
 ssh_config/
+
+watod-config.local.sh

docker/perception/camera_object_detection/camera_object_detection.Dockerfile

@@ -31,7 +31,7 @@ RUN rm requirements.txt
 
 # Install Rosdep requirements
 COPY --from=source /tmp/colcon_install_list /tmp/colcon_install_list
-RUN apt-fast install -qq -y --no-install-recommends $(cat /tmp/colcon_install_list)
+RUN apt-get update && apt-fast install -qq -y --no-install-recommends $(cat /tmp/colcon_install_list)
 
 # Copy in source code from source stage
 WORKDIR ${AMENT_WS}

docker/simulation/carla_notebooks/carla_notebooks.Dockerfile

@@ -0,0 +1,23 @@
+ARG CARLA_VERSION=0.9.13
+FROM carlasim/carla:${CARLA_VERSION} AS wato_carla_api
+
+FROM python:3.8.16-slim-bullseye
+ARG CARLA_VERSION=0.9.13
+
+RUN pip3 install carla==${CARLA_VERSION} jupyter tensorflow-probability
+RUN apt-get update && apt-get install -y curl git wget unzip && apt remove python3-networkx
+
+COPY --from=wato_carla_api --chown=root /home/carla/PythonAPI/carla/agents /usr/local/lib/python3.8/site-packages/agents
+
+WORKDIR /home/bolty/carla_notebooks
+COPY src/simulation/carla_notebooks /home/bolty/carla_notebooks
+
+WORKDIR /home/bolty
+# Setup CARLA Scenario Runner
+# The last sed command replaces hero (default ego vehicle name) with another ego vehicle name
+RUN git clone https://github.com/carla-simulator/scenario_runner.git && \
+    cd scenario_runner && pip3 install -r requirements.txt && \
+    sed -i s/hero/ego/g /home/bolty/scenario_runner/srunner/tools/scenario_parser.py
+WORKDIR /home/bolty
+
+WORKDIR /home/bolty/carla_notebooks

docker/simulation/carla_ros_bridge/carla_ros_bridge.Dockerfile

@@ -0,0 +1,109 @@
+ARG BASE_IMAGE=ghcr.io/watonomous/wato_monorepo/base:foxy-ubuntu20.04
+
+ARG CARLA_VERSION=0.9.13
+FROM carlasim/carla:${CARLA_VERSION} AS wato_carla_api
+
+################################ Source ################################
+FROM ${BASE_IMAGE} as source
+
+WORKDIR ${AMENT_WS}/src
+
+# Download ROS Bridge
+RUN git clone --depth 1 --branch master --recurse-submodules https://github.com/carla-simulator/ros-bridge.git && \
+    cd ros-bridge && \
+    git checkout e9063d97ff5a724f76adbb1b852dc71da1dcfeec && \
+    cd ..
+
+# Fix an error in the ackermann_control node 
+RUN sed -i s/simple_pid.PID/simple_pid.pid/g ./ros-bridge/carla_ackermann_control/src/carla_ackermann_control/carla_ackermann_control_node.py
+
+# Copy in source code 
+COPY src/simulation/carla_config carla_config
+COPY src/wato_msgs/simulation ros_msgs
+
+# Scan for rosdeps
+RUN apt-get -qq update && rosdep update --rosdistro foxy && \
+    rosdep install --from-paths . -r -s \
+        | grep 'apt-get install' \
+        | awk '{print $3}' \
+        | sort  > /tmp/colcon_install_list
+
+################################# Dependencies ################################
+FROM ${BASE_IMAGE} as dependencies
+
+# Install dependencies
+RUN apt-get update && \
+      apt-fast install -qq -y --no-install-recommends lsb-release \
+      libglu1-mesa-dev xorg-dev \
+      software-properties-common \
+      build-essential \
+      python3-rosdep \
+      python3-rospkg \
+      python3-colcon-common-extensions \
+      python3-pygame \
+      ros-$ROS_DISTRO-tf2-geometry-msgs \
+      ros-$ROS_DISTRO-tf2-eigen \
+      ros-$ROS_DISTRO-ackermann-msgs \
+      ros-$ROS_DISTRO-derived-object-msgs \
+      ros-$ROS_DISTRO-cv-bridge \
+      ros-$ROS_DISTRO-vision-opencv \
+      ros-$ROS_DISTRO-rqt-image-view \
+      ros-$ROS_DISTRO-rqt-gui-py \
+      qt5-default \
+      ros-$ROS_DISTRO-pcl-conversions \
+      ros-$ROS_DISTRO-resource-retriever \
+      ros-$ROS_DISTRO-yaml-cpp-vendor \
+      ros-$ROS_DISTRO-urdf \
+      ros-$ROS_DISTRO-map-msgs \
+      ros-$ROS_DISTRO-laser-geometry \
+      ros-$ROS_DISTRO-interactive-markers \
+      ros-$ROS_DISTRO-rviz2
+
+# Install Rosdep requirements
+COPY --from=source /tmp/colcon_install_list /tmp/colcon_install_list
+RUN apt-fast install -qq -y --no-install-recommends $(cat /tmp/colcon_install_list)
+
+# Copy in source code from source stage
+WORKDIR ${AMENT_WS}
+COPY --from=source ${AMENT_WS}/src src
+
+# Dependency Cleanup
+WORKDIR /
+RUN apt-get -qq autoremove -y && apt-get -qq autoclean && apt-get -qq clean && \
+    rm -rf /root/* /root/.ros /tmp/* /var/lib/apt/lists/* /usr/share/doc/*
+
+################################ Build ################################
+FROM dependencies as build
+
+ARG CARLA_VERSION
+
+#Install Python Carla API
+COPY --from=wato_carla_api --chown=root /home/carla/PythonAPI/carla /opt/carla/PythonAPI
+WORKDIR /opt/carla/PythonAPI
+RUN python3.8 -m easy_install pip && \
+      pip3 install carla==${CARLA_VERSION} && \
+      pip install simple-pid==2.0.0 && \
+      pip install transforms3d==0.4.1 && \
+      pip install pexpect==4.9.0 && \
+      pip install networkx==3.1
+
+WORKDIR ${AMENT_WS}/src
+
+# Build ROS2 packages
+WORKDIR ${AMENT_WS}
+RUN . /opt/ros/$ROS_DISTRO/setup.sh && \
+    colcon build \
+        --cmake-args -DCMAKE_BUILD_TYPE=Release
+
+# Entrypoint will run before any CMD on launch. Sources ~/opt/<ROS_DISTRO>/setup.bash and ~/ament_ws/install/setup.bash
+COPY docker/wato_ros_entrypoint.sh ${AMENT_WS}/wato_ros_entrypoint.sh
+ENTRYPOINT ["./wato_ros_entrypoint.sh"]
+
+################################ Prod ################################
+FROM build as deploy
+
+# Source Cleanup and Security Setup
+RUN chown -R $USER:$USER ${AMENT_WS}
+RUN rm -rf src/*
+
+USER ${USER}

docker/simulation/carla_sim/carla_sim.Dockerfile → docker/simulation/carla_sample_node/carla_sample_node.Dockerfile

@@ -6,8 +6,17 @@ FROM ${BASE_IMAGE} as source
 WORKDIR ${AMENT_WS}/src
 
 # Copy in source code 
-COPY src/simulation/carla_sim carla_sim
-COPY src/wato_msgs/sample_msgs sample_msgs
+COPY src/simulation/carla_sample_node carla_sample_node
+COPY src/wato_msgs/simulation/embedded_msgs embedded_msgs
+COPY src/wato_msgs/simulation/path_planning_msgs path_planning_msgs
+
+# Carla specific messages
+
+RUN git clone --depth 1 https://github.com/ros-drivers/ackermann_msgs.git --branch 2.0.2
+
+RUN git clone --depth 1 https://github.com/ros-perception/image_common.git --branch 3.1.8
+
+RUN git clone --depth 1 https://github.com/carla-simulator/ros-carla-msgs.git --branch 1.3.0
 
 # Scan for rosdeps
 RUN apt-get -qq update && rosdep update && \

docker/simulation/carla_viz/carla_viz.Dockerfile

@@ -0,0 +1,14 @@
+FROM mjxu96/carlaviz:0.9.13
+
+ENV CARLAVIZ_BACKEND_HOST localhost
+ENV CARLAVIZ_BACKEND_PORT 8081
+ENV CARLA_SERVER_HOST localhost
+ENV CARLA_SERVER_PORT 2000
+
+WORKDIR /home/carla/carlaviz
+
+COPY docker/simulation/carla_viz/carlaviz_entrypoint.sh /home/carla/carlaviz/docker/carlaviz_entrypoint.sh
+
+RUN chmod +x ./docker/carlaviz_entrypoint.sh
+
+ENTRYPOINT ["/bin/bash", "-c", "./docker/carlaviz_entrypoint.sh > /dev/null 2>&1"]

docker/simulation/carla_viz/carlaviz_entrypoint.sh

@@ -0,0 +1,53 @@
+
+is_backend_up=""
+
+function wait_for_backend_up() {
+    max_wait_time=5
+    for ((i=0; i<=$max_wait_time; ++i)) do
+        cat output.txt | grep -q "Connected to Carla Server"
+        if [ $? == 0 ]; then
+            is_backend_up="1"
+            break
+        fi
+        sleep 1
+    done
+}
+
+function cleanup_backend() {
+    backend_pid=$(pidof backend)
+    kill -9 $backend_pid
+    echo "Killed Backend process $backend_pid"
+}
+
+echo -e "CARLAVIZ_BACKEND_HOST=${CARLAVIZ_BACKEND_HOST}" >> /home/carla/.env
+echo -e "CARLAVIZ_BACKEND_PORT=${CARLAVIZ_BACKEND_PORT}" >> /home/carla/.env
+
+echo "Make sure you have launched the Carla server."
+echo "Launching backend."
+./backend/bin/backend ${CARLA_SERVER_HOST} ${CARLA_SERVER_PORT} |& tee output.txt &
+wait_for_backend_up
+if [[ -z "$is_backend_up" ]]; then
+    echo "Backend is not launched. Please check if you have already started the Carla server."
+    cleanup_backend
+    exit 1
+fi
+
+echo "Backend launched."
+
+echo "Launching frontend"
+# enable nginx
+service nginx restart
+echo "Frontend launched. Please open your browser"
+sleep 10
+sed -i s/:8081/:$CARLAVIZ_BACKEND_PORT/g /var/www/carlaviz/bundle.js
+
+while [ "$is_backend_up" = "1" ]
+do
+    cat output.txt | grep -q "time-out of"
+    if [ $? == 0 ]; then
+        is_backend_up=""
+        cleanup_backend
+        exit 1
+    fi
+    sleep 5
+done

docs/carla.md

@@ -0,0 +1,67 @@
+# CARLA Setup in Monorepo
+CARLA is an open-source autonomous driving simulator based on Unreal Engine 4. The primary ways of interacting with the CARLA setup are through the Python API or with ROS2 (via the CARLA ROS Bridge). Both of these methods are explained in greater detail further down in this document. 
+
+The goal of the  CARLA setup is to provide an easy way for WATonomous members to interact with the simulator without having to setup anything themselves. So, if you have any questions or suggestions regarding any part of the CARLA setup (or questions about CARLA in general) please bring them up in Discord in #simulation-general or contact Vishal Jayakumar (masteroooogway on Discord or at [[email protected]](mailto:[email protected])).
+
+- [CARLA WATonomous Documentation](#using-carla-setup-in-monorepo)
+    - [Initial Setup](#initial-setup) 
+    - [Interacting with CARLA using the Python API](#interacting-with-carla-using-the-python-api)
+    - [Using a ROS Node to interact with CARLA](#using-a-ros-node-to-interact-with-carla)
+    - [CARLA Visualization using Foxglove Studio](#carla-visualization-using-foxglove-studio)
+    - [CARLA Visualization using CarlaViz](#carla-visualization-using-carlaviz)
+    - [FAQ](#faq)
+        - [CARLA is running very slow (approx. 3 fps)](#carla-is-running-very-slow-approx-3-fps)
+
+**Make sure you are confortable with navigating the monorepo before reading**
+
+## Initial Setup
+
+To run CARLA and all associated containers first add `simulation` as an `ACTIVE_MODULE` in `watod-config.sh`. This will cause the following containers to launch when `watod up` is run: `carla_server`, `carla_viz`, `carla_ros_bridge`, `carla_notebooks`, `carla_sample_node`.
+
+## Interacting with CARLA using the Python API
+
+This is the simplest way of interacting with CARLA and most importantly does not require the usage or knowledge of ROS. The documentation below will only show the setup procedure for using the CARLA Python API in the WATOnomous server (via Jupyter Notebook). The full CARLA Python API documentation can be found here ([CARLA Python API Documentation](https://carla.readthedocs.io/en/0.9.13/python_api/)). 
+
+**On the WATOnomous Server**
+
+Forward the port specified by the variable `CARLA_NOTEBOOKS_PORT` (which can be found in the `.env` file in the `modules` folder once `watod up` is run) using either the `ports` section of VS Code or by running the command `ssh -L 8888:localhost:8888 <username>@<machine>-ubuntu1.watocluster.local` on your local machine (replace 8888 with the port specified in the `CARLA_NOTEBOOKS_PORT` variable). If the port is auto-forwarded by VS Code then you do not need to add it manually.
+
+**On your local machine (your personal laptop/pc)**
+
+Open any web browser (Chrome, Firefox, Edge etc.) and type `localhost:8888` (replace 8888 with the port specified in the `CARLA_NOTEBOOKS_PORT` variable) and click enter. You should be automatically redirected to the Jupyter Notebook home screen where you should see the file `carla_notebooks.ipynb`. Open that file and follow the instructions in it. Either edit the `carla_notebooks.ipynb` file directly or create a new file and copy the first code block in `carla_notebooks.ipynb`.
+
+## Using a ROS Node to interact with CARLA
+
+**Ensure that you have a good understanding of ROS and writing ROS nodes before proceeding**
+
+Currently there is a CARLA sample node setup (written in Python) shows how to publish a message to enable (and keep enabled) autopilot, subsribe to the GNSS sensor topic and output the data to the console. What is probably most helpful from the sample node is the Dockerfile located in `wato_monorepo_v2/docker/simulation/carla_sample_node/carla_sample_node.Dockerfile`, where you can find all the CARLA related messages that should be installed when building your own ROS nodes that interact with CARLA.
+
+## CARLA Visualization using Foxglove Studio
+
+Foxglove Studio is a tool to visualize and interact with ROS messages. Using Foxglove Studio, data such as Camera, LiDAR, Radar etc. can be visualized. Foxglove Studio also allows for messages to be published to topics, for example to enable autopilot or set vehicle speed. The documentation below will only show the setup procedure for using Foxglove Studio with the WATOnomous server. Further documentation regarding how to use Foxglove Studio and all its features can be found here ([Foxglove Studio Documentation](https://foxglove.dev/docs/studio))
+
+**On the WATOnomous Server**
+
+Add `vis_tools` as an `ACTIVE_PROFILE`. This will launch the `foxglove.Dockerfile` container with an open port when `watod up` is ran. 
+
+It exposes the port specified by the `FOXGLOVE_BRIDGE_PORT` variable, which will be defined in the `.env` file in the `profiles` folder (the `.env` file is populated after `watod up` is run). This port may be auto-forwarded by VS Code automatically but if not the port will need to be forwarded manually to your local machine. This can either be done in the `ports` section of VS Code or by running the command `ssh -L 8765:localhost:8765 <username>@<machine>-ubuntu1.watocluster.local` on your local machine (replace 8765 with the port specified in the `FOXGLOVE_BRIDGE_PORT` variable).
+
+**On your local machine (your personal laptop/pc)**
+
+Open Foxglove Studio on your local machine using either the desktop app ([Download Here](https://foxglove.dev/studio)) or the [Web Application](https://studio.foxglove.dev/) (only supported on Chrome). Click on Open Connection then replace the default port (8765) with the port you specified in the `FOXGLOVE_BRIDGE_PORT` variable. Then click the Open button and after a few seconds Foxglove Studio should connect. You should now be able to access any of the topic being published or subscribed by the CARLA ROS Bridge.
+
+## CARLA Visualization using CarlaViz
+
+**On the WATOnomous Server**
+
+CarlaViz is a visualization tool that is useful when you are only using the CARLA Python API through a Jupyter Notebook and you don't want the overhead that comes with the ROS Bridge + Foxglove method of visualization. To use CarlaViz forward the ports specified by the variables `CARLAVIZ_PORT` and `CARLAVIZ_PORT_2` defined in the `.env` file in the `profiles` folder (make sure you forward **both** ports). If you want to stop the ROS Bridge from running (for the reasons I mentioned in the previous sentences) then make sure to comment out the `carla_ros_bridge` service in the `docker-compose.carla.yaml` file in the `profiles` folder.
+
+**On your local machine (your personal laptop/pc)**
+
+In any browser go to `localhost:8081` (replace 8081 with the port specified in the `CARLAVIZ_PORT` variable) and after waiting 10 seconds or so CarlaViz should appear.  
+
+## FAQ
+
+### CARLA is running very slow (approx. 3 fps)
+
+This is expected. The ROS bridge causes CARLA to render all the sensor data which slows down the simulation considerably. While this may be annoying when viewing real-time camera output or trying to control the car manual, the simulation is still running accurately. If you wish to replay scenes with a configurable playback speed, check out the docs on [CARLA's recorder](https://carla.readthedocs.io/en/0.9.13/adv_recorder/) functionality.

docs/dev/how_to_dev.md

@@ -92,7 +92,7 @@ services:
         - "${SAMPLES_CPP_AGGREGATOR_IMAGE:?}-${CACHE_FROM_TAG}"
         - "${SAMPLES_CPP_AGGREGATOR_IMAGE:?}-develop"
     # name of the image made by the dockerfile (boilerplate, but with name change)
-    image: "${SAMPLES_CPP_AGGREGATOR_IMAGE:?}-${TAG}"
+    image: "${SAMPLES_CPP_AGGREGATOR_IMAGE:?}-build_${TAG}"
     # deals with permission and ownership in the container (boilerplate)
     user: ${FIXUID:?}:${FIXGID:?}
     # IMPORTANT: mounts your ROS2 node into the container so that changes in the dockerfile are reflected in your