Autoware.AI 1.12.0 with LGSVL Simulator

The software and source code in this repository are intended only for use with LG Automotive Simulator and should not be used in a real vehicle.

Table of Contents

General top#

This guide goes through how to run Autoware.AI with the LG SVL Simulator.

In order to run Autoware with the LGSVL simulator, it is easiest to pull an official Autoware docker image (see official guide), but it is also possible to build autoware from source.

Autoware communicates with the simulator using the rosbridge_suite, which provides JSON interfacing with ROS publishers/subscribers. The official autoware docker containers have rosbridge_suite included.

Setup top#

Requirements top#

  • Linux operating system
  • Nvidia graphics card

Installing Docker CE top

To install Docker CE please refer to theĀ official documentation. We also suggest following through with theĀ post installation steps.

Installing Nvidia Docker top

Before installing nvidia-docker make sure that you have an appropriate Nvidia driver installed. To test if nvidia drivers are properly installed enter nvidia-smi in a terminal. If the drivers are installed properly an output similar to the following should appear.

    +-----------------------------------------------------------------------------+
    | NVIDIA-SMI 390.87                 Driver Version: 390.87                    |
    |-------------------------------+----------------------+----------------------+
    | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
    | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
    |===============================+======================+======================|
    |   0  GeForce GTX 108...  Off  | 00000000:65:00.0  On |                  N/A |
    |  0%   59C    P5    22W / 250W |   1490MiB / 11175MiB |      4%      Default |
    +-------------------------------+----------------------+----------------------+

    +-----------------------------------------------------------------------------+
    | Processes:                                                       GPU Memory |
    |  GPU       PID   Type   Process name                             Usage      |
    |=============================================================================|
    |    0      1187      G   /usr/lib/xorg/Xorg                           863MiB |
    |    0      3816      G   /usr/bin/gnome-shell                         305MiB |
    |    0      4161      G   ...-token=7171B24E50C2F2C595566F55F1E4D257    68MiB |
    |    0      4480      G   ...quest-channel-token=3330599186510203656   147MiB |
    |    0     17936      G   ...-token=5299D28BAAD9F3087B25687A764851BB   103MiB |
    +-----------------------------------------------------------------------------+

Simulator installation top#

Follow the instructions on our simulator Github page here.

Launching Autoware alongside LGSVL Simulator top#

Before launching, you need to create a directory called shared_dir in the home directory to hold maps and launch files for the simulator. The autoware docker container will mount this folder:

$ mkdir ~/shared_dir
$ cd ~/shared_dir
$ git clone https://github.com/lgsvl/autoware-data.git

To launch Autoware, first bring up the Docker container following these steps (see official guide for more details):

  • Clone the docker repository from autoware.ai:
$ git clone https://gitlab.com/autowarefoundation/autoware.ai/docker.git
  • Navigate to:
$ cd docker/generic

NOTE With the latest Docker and Nvidia-docker versions, the docker option --runtime=nvidia has been deprecated. If you have Docker CE version 19.03 and Nvidia-docker release v2.2.2 please run the following to check if docker containers will have access to your GPU.

  • In a terminal run type nvidia-docker .

    1. If you get the ouput similar to this: nvidia-docker is /usr/bin/nvidia-docker, the run script will work fine.
    2. If you get the following output bash: type: nvidia-docker: not found, you need to modify the run script as shown below.
  • In run.sh find the following at line 139:

    if [ $CUDA == "on" ]; then
        SUFFIX=$SUFFIX"-cuda"
        RUNTIME="--runtime=nvidia"
    fi
    

    Replace them with:

    if [ $CUDA == "on" ]; then
        SUFFIX=$SUFFIX"-cuda"
        if [[ $DOCKER_VERSION -ge "19" ]] && ! type nvidia-docker; then
            RUNTIME="--gpus all"
        else
            RUNTIME="--runtime=nvidia"
        fi
    fi
    
  • Pull the image and run (for release 1.12.0):

$ ./run.sh -t 1.12.0

Once inside the container, launch the runtime manager:

autoware@[MY_DESKTOP]:~$ roslaunch runtime_manager runtime_manager.launch

A few terminals will open, as well as a GUI for the runtime manager. In the runtime manager, click on the 'Quick Start' tab and load the following launch files from ~/shared_dir/autoware-data/BorregasAve/ by clicking "Ref" to the right of each text box:

  • my_map.launch
  • my_sensing_simulator.launch
  • my_localization.launch
  • my_detection.launch
  • my_mission_planning.launch

Click "Map" to load the launch file pertaining to the HD maps. An "Ok" should appear to the right of the "Ref" button when successfully loaded. Then click "Sensing" which also launches rosbridge.

  • Run the LG SVL simulator
  • Create a Simulation choosing BorregasAve map and Jaguar2015XE (Autoware) or another Autoware compatible vehicle.
  • Enter localhost:9090 for the Bridge Connection String.
  • Run the created Simulation

A vehicle should appear in Borregas Ave in Sunnyvale, CA.

In the Autoware Runtime Manager, continue loading the other launch files - click "Localization" and wait for the time to display to the right of "Ref".

Then click "Rviz" to launch Rviz - the vector map and location of the vehicle in the map should show.

The vehicle may be mis-localized as the initial pose is important for NDT matching. To fix this, click "2D Pose Estimate" in Rviz, then click an approximate position for the vehicle on the map and drag in the direction it is facing before releasing the mouse button. This should allow NDT matching to find the vehicle pose (it may take a few tries). Note that the point cloud will not show up in rviz until ndt matching starts publishing a pose.

An alternative would be to use GNSS for an inital pose or for localization but the current Autoware release (1.12.0) does not support GNSS coordinates outside of Japan. Fix for this is available in following pull requests: utilities#27, common#20, core_perception#26 These are not yet merged in Autoware master.

Driving by following vector map:#

To drive following the HD map follow these steps: - in rviz, mark a destination by clicking '2D Nav Goal' and clicking at the destination and dragging along the road direction. Make sure to only choose a route that looks valid along the lane centerlines that are marked with orange lines in rviz. If an invalid destination is selected nothing will change in rviz, and you will need to relaunch the Mission Planning launch file in the Quick Launch tab to try another destination. After choosing a valid destination the route will be highlighted in blue in rviz.

To follow the selected route launch these nodes: - Enable lane_rule, lane_stop, and lane_select to follow traffic rules based on the vector map. - Enable astar_avoid and velocity_set. - Enable pure_pursuit and twist_filter to start driving.

Driving by following prerecorded waypoints:#

A basic functionality of Autoware is to follow a prerecorded map while obeying traffic rules. To do this you will need to record a route first. Switch to the Computing tab and check the box for waypoint_saver. Make sure to select an appropriate location and file name by clicking on the app button.

Now you can drive around the map using the keyboard. Once you are satisfied with your route, uncheck the box for waypoint_saver to end the route.

To drive the route using autoware:

  • Enable waypoint_loader while making sure the correct route file is selected in the app settings.
  • Enable lane_rule, lane_stop, and lane_select to follow traffic rules based on the vector map.
  • Enable astar_avoid and velocity_set.
  • Enable pure_pursuit and twist_filter to start driving.

The ego vehicle should try to follow the waypoints at the velocity which they were originally recorded at. You can modify this velocity by manually editing the values csv file.

Adding a Vehicle top#

The default vehicles have the calibration files included in the LGSVL Autoware Data Github repository.

Adding an HD Map top#

The default maps have the Vector map files included in the LGSVL Autoware Data Github repository.

Copyright (c) 2019 LG Electronics, Inc.

This software contains code licensed as described in LICENSE.