Integrated open-source software for urban autonomous driving, maintained by Tier IV. The following functions are supported:
- 3D Localization
- 3D Mapping
- Path Planning
- Path Following
- Accel/Brake/Steering Control
- Data Logging
- Car/Pedestrian/Object Detection
- Traffic Signal Detection
- Traffic Light Recognition
- Lane Detection
- Object Tracking
- Sensor Calibration
- Sensor Fusion
- Cloud-oriented Maps
- Connected Automation
- Smartphone Navigation
- Software Simulation
- Virtual Reality
Autoware is protected by BSD License. Please use it on your own responsibility. For safe use, we provide a ROSBAG-based simulation method for those who do not own real autonomous vehicles. In case that you use Autoware with real autonomous vehicles, please formulate safety measures and assessment of risk before field testing.
- New BSD License
- See LICENSE
- # of CPU cores: 8
- RAM size: 32GB
- Storage size: 30GB
- ROS indigo(Ubuntu 14.04) or ROS jade(Ubuntu 15.04)
- OpenCV 2.4.10 or higher NOTE: As of Octber 2016, Autoware does not support OpenCV 3 or higher. Please use OpenCV 2
- Qt 5.2.1 or higher
Please use checkout revision before 2015/OCT/21 if you use Autoware on ROS hydro or Ubuntu 13.04, 13.10.
Install dependencies for Ubuntu 14.04 indigo
% sudo apt-get install ros-indigo-desktop-full ros-indigo-nmea-msgs ros-indigo-nmea-navsat-driver ros-indigo-sound-play ros-indigo-jsk-visualization ros-indigo-grid-map % sudo apt-get install ros-indigo-controller-manager ros-indigo-ros-control ros-indigo-ros-controllers ros-indigo-gazebo-ros-control ros-indigo-sicktoolbox ros-indigo-sicktoolbox-wrapper ros-indigo-joystick-drivers ros-indigo-novatel-span-driver % sudo apt-get install libnlopt-dev freeglut3-dev qtbase5-dev libqt5opengl5-dev libssh2-1-dev libarmadillo-dev libpcap-dev gksu libgl1-mesa-dev
NOTE: Please do not install ros-indigo-velodyne-pointcloud package. Please uninstall it if you already installed.
Install dependencies for Ubuntu 15.04 jade
% sudo apt-get install ros-jade-desktop-full ros-jade-nmea-msgs ros-jade-nmea-navsat-driver ros-jade-sound-play % sudo apt-get install ros-jade-controller-manager ros-jade-ros-control ros-jade-ros-controllers ros-jade-gazebo-ros-control ros-jade-sicktoolbox ros-jade-sicktoolbox-wrapper ros-jade-joystick-drivers ros-jade-novatel-span-driver % sudo apt-get install libnlopt-dev freeglut3-dev qt5-default libqt5opengl5-dev libssh2-1-dev libarmadillo-dev libpcap-dev gksu libgl1-mesa-dev
NOTE: jsk_visualization and grid_map is not provided in Ubuntu15.04 Jade. Please download it from the following repository and build it by yourself. https://github.com/jsk-ros-pkg/jsk_visualization https://github.com/ethz-asl/grid_map
How to Build
$ cd $HOME $ git clone https://github.com/CPFL/Autoware.git $ cd ~/Autoware/ros/src $ catkin_init_workspace $ cd ../ $ ./catkin_make_release
Caffe based object detectors
CV based detectors RCNN and SSD nodes are not automatically built.
How to Start
$ cd $HOME/Autoware/ros $ ./run
Be careful for changing files under
ros/src/sensing/drivers/lidar/packages/velodyne. There is subtree.
Original repository is here. If you change those files from this
repository, you must use git subtree push. (Please never change and push code if you don't understand
git subtree well).
GitFlow, git branching model, is introduced in Autoware repository.
- When you adding new features, you can branch off your feature branch from
you can use the following command.
$ git checkout -b feature/[your_branch_name] develop
- When you find bugs in
masterbranch, you can branch off your hotfix branch from
you can use the following command.
$ git checkout -b hotfix/[your_branch_name] master
More Details here
See Autoware/docs. As of Aug 2015, we provide only Japanese documents. English documents will be added shortly.
Mission (Global) Planning
Motion (Local) Planning
Research Papers for Citation
- S. Kato, E. Takeuchi, Y. Ishiguro, Y. Ninomiya, K. Takeda, and T. Hamada. "An Open Approach to Autonomous Vehicles", IEEE Micro, Vol. 35, No. 6, pp. 60-69, 2015.
Public Road Testing
Loading Map Data
Localization with GNSS
Localization without GNSS
Detection with SSD
Detection with DPM
Detection with Euclidean Clustering
Traffic Light Recognition
Planning with ROSBAG
Planning with wf_simulator
Planning with Hybrid State A*
IROS 2016 Data
Autoware Developers (email@example.com)
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