forked from autowarefoundation/autoware
-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
[Hotfix] Revise README.md (autowarefoundation#1326)
- Loading branch information
Showing
2 changed files
with
45 additions
and
220 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,259 +1,84 @@ | ||
| <div align="center"><img src="docs/images/autoware_logo_1.png" width="400"/></div> | ||
|
|
||
| |Branch | Status | | ||
| |-------|--------| | ||
| |Master |[](https://travis-ci.org/CPFL/Autoware) | | ||
| |Develop|[](https://travis-ci.org/CPFL/Autoware)| | ||
|
|
||
| # Autoware | ||
| Open-source software for urban autonomous driving, maintained by [Tier IV](http://www.tier4.jp). 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 the BSD License. Please use it at your own discretion. For safe use, we provide a ROSBAG-based simulation method for those who do not own real autonomous vehicles. If you plan to use Autoware with real autonomous vehicles, **please formulate safety measures and assessment of risk before field testing.** | ||
|
|
||
| ## Manuals and Documents | ||
|
|
||
| Free manuals can be found at [https://github.com/CPFL/Autoware-Manuals](https://github.com/CPFL/Autoware-Manuals). You are encouraged to contribute to the maintenance of these manuals. Thank you for your cooperation! | ||
|
|
||
| If you have a question please check the [Wiki](https://github.com/CPFL/Autoware/wiki), and the [FAQ](https://github.com/CPFL/Autoware/wiki/FAQ), [FAQ (JP)](https://github.com/CPFL/Autoware/wiki/FAQ(JP)). | ||
|
|
||
| ## License | ||
|
|
||
| * New BSD License | ||
| * See LICENSE | ||
|
|
||
| ## Recommended Minimum System Specifications | ||
|
|
||
| - Number of CPU cores: 8 | ||
| - RAM size: 32GB | ||
| - Storage size: 30GB | ||
|
|
||
| ## Requirements | ||
|
|
||
| - ROS indigo (Ubuntu 14.04) or ROS jade (Ubuntu 15.04) or ROS kinetic (Ubuntu 16.04) | ||
| - OpenCV 2.4.10 or higher | ||
| - Qt 5.2.1 or higher | ||
| - CUDA (optional) | ||
| - FlyCapture2 (optional) | ||
| - Armadillo (optional) | ||
|
|
||
| **Please use checkout a revision before 2015/OCT/21 if you want to use Autoware on ROS Hydro or Ubuntu 13.04, 13.10.** | ||
| [](https://www.autoware.ai) | ||
|
|
||
| ### Install system dependencies for Ubuntu 14.04 Indigo | ||
| | *master* | *develop* | | ||
| |----------|-----------| | ||
| |[](https://travis-ci.org/CPFL/Autoware)|[](https://travis-ci.org/CPFL/Autoware)| | ||
|
|
||
| ``` | ||
| % sudo apt-get install -y python-catkin-pkg python-rosdep python-wstool ros-$ROS_DISTRO-catkin | ||
| % sudo add-apt-repository ppa:mosquitto-dev/mosquitto-ppa | ||
| % sudo apt-get update | ||
| % sudo apt-get install libmosquitto-dev | ||
| ``` | ||
| [Autoware](https://www.autoware.ai) is the world's first "all-in-one" open-source software for self-driving vehicles. The capabilities of Autoware are primarily well-suited for urban cities, but highways, freeways, mesomountaineous regions, and geofenced areas can be also covered. The code base of Autoware is protected by the BSD License. Please use it at your own discretion. For safe use, we provide a ROSBAG-based simulation environment for those who do not own real autonomous vehicles. If you plan to use Autoware with real autonomous vehicles, **please formulate safety measures and assessment of risk before field testing.** | ||
|
|
||
| **NOTE: Please do not install ros-indigo-velodyne-pointcloud package. If it is already installed, please uninstall.** | ||
| You may refer to [Autoware Wiki](https://github.com/CPFL/Autoware/wiki) for **Users Guide** and **Developers Guide**. | ||
|
|
||
| ### Install system dependencies for Ubuntu 16.04 Kinetic | ||
| ``` | ||
| % sudo apt-get update | ||
| % sudo apt-get install -y python-catkin-pkg python-rosdep python-wstool ros-$ROS_DISTRO-catkin libmosquitto-dev | ||
| ``` | ||
| ## What Is Autoware | ||
|
|
||
| **NOTE: Following packages are not supported in ROS Kinetic.** | ||
| - gazebo | ||
| - orb slam | ||
| - dpm ocv | ||
| [](https://github.com/CPFL/Autoware/wiki/Overview) | ||
|
|
||
| ## How to Build | ||
| Autoware provides a rich set of self-driving modules composed of sensing, computing, and actuation capabilities. An overview of those capabilities is described [here](https://github.com/CPFL/Autoware/wiki/Overview). Keywords include *Localization, Mapping, Object Detection & Tracking, Traffic Light Recognition, Mission & Motion Planning, Trajectory Generation, Lane Detection & Selection, Vehicle Control, Sensor Fusion, Cameras, LiDARs, RADARs, Deep Learning, Rule-based System, Connected Navigation, Logging, Virtual Reality, and so on*. | ||
|
|
||
| 1. Clone the repository | ||
| Free manuals can be also found at [Autoware-Manuals](https://github.com/CPFL/Autoware-Manuals). You are encouraged to contribute to the maintenance of these manuals. Thank you for your cooperation! | ||
|
|
||
| ``` | ||
| $ cd $HOME | ||
| $ git clone https://github.com/CPFL/Autoware.git --recurse-submodules | ||
| ``` | ||
| or if you already have a copy of the repo, run `$ git submodule update --init --recursive`. | ||
| ## Getting Started | ||
|
|
||
| 2. Initialize the workspace, let rosdep to install the missing dependencies and compile. | ||
|
|
||
| ``` | ||
| $ cd ~/Autoware/ros/src | ||
| $ catkin_init_workspace | ||
| $ cd ../ | ||
| $ rosdep install -y --from-paths src --ignore-src --rosdistro $ROS_DISTRO | ||
| $ ./catkin_make_release | ||
| ``` | ||
| [](https://github.com/CPFL/Autoware/wiki/Demo) | ||
|
|
||
| ###Caffe based object detectors | ||
| CV based detectors RCNN and SSD nodes are not automatically built. | ||
| ### Recommended System Specifications | ||
|
|
||
| To build these nodes please follow the respective node's README | ||
| [SSD](ros/src/computing/perception/detection/packages/cv_tracker/nodes/ssd/README.md) | ||
| [RCNN](ros/src/computing/perception/detection/lib/image/librcnn/README.md) | ||
| [Yolo2](ros/src/computing/perception/detection/packages/cv_tracker/nodes/yolo2/README.md) | ||
| [Yolo3](ros/src/computing/perception/detection/packages/yolo3_detector/README.md) | ||
|
|
||
|
|
||
| ## How to Start | ||
|
|
||
| ``` | ||
| $ cd $HOME/Autoware/ros | ||
| $ ./run | ||
| ``` | ||
|
|
||
| ## For Developers | ||
|
|
||
| Be careful when changing files under `ros/src/sensing/drivers/lidar/packages/velodyne`. There is **subtree**. | ||
| The original repository is [here](https://github.com/CPFL/velodyne). 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, the git branching model, is used in the Autoware repository. | ||
| - When adding new features, you can branch off your feature branch from `develop`. | ||
| You can use the following command. | ||
| `$ git checkout -b feature/[your_branch_name] develop` | ||
| - When you find bugs in `master`, you can branch off your hotfix branch from `master`. | ||
| You can use the following command. | ||
| `$ git checkout -b hotfix/[your_branch_name] master` | ||
|
|
||
| See also [branching_model](https://github.com/CPFL/Autoware/blob/master/docs/en/branching_model.md) for tips on Autoware development, including the coding style and branching model. | ||
|
|
||
| More details [here](http://nvie.com/posts/a-successful-git-branching-model/) | ||
|
|
||
| ## Main Packages | ||
| - Number of CPU cores: 8 | ||
| - RAM size: 32GB | ||
| - Storage size: 64GB+ | ||
|
|
||
| ### Localization | ||
| - ndt_localizer | ||
| - icp_localizer | ||
| ### Users Guide | ||
|
|
||
| ### Detection | ||
| - lidar_tracker | ||
| - cv_tracker | ||
| - trafficlight_recognizer | ||
| 1. [Installation](https://github.com/CPFL/Autoware/wiki/Installation) | ||
| 1. [Docker](https://github.com/CPFL/Autoware/wiki/Docker) | ||
| 1. [Source](https://github.com/CPFL/Autoware/wiki/Source-Build) | ||
| 1. [Demo](https://github.com/CPFL/Autoware/wiki/Demo) | ||
| 1. [Field Test](https://github.com/CPFL/Autoware/wiki/Field-Test) | ||
| 1. [Videos](https://github.com/CPFL/Autoware/wiki/videos) | ||
|
|
||
| ### Mission (Global) Planning | ||
| - lane_planner | ||
| - way_planner | ||
| - freespace_planner | ||
| ### Developers Guide | ||
|
|
||
| ### Motion (Local) Planning | ||
| - astar_planner | ||
| - lattice_planner | ||
| - dp_planner | ||
| 1. [Contribution Rules](https://github.com/CPFL/Autoware/wiki/Contribution-Rules) (**Must Read**) | ||
| 1. [Overview](https://github.com/CPFL/Autoware/wiki/Overview) | ||
| 1. [Specification](https://github.com/CPFL/Autoware/wiki/Specification) | ||
|
|
||
| ### Vehicle Control | ||
| - waypoint_follower | ||
| - waypoint_maker | ||
|
|
||
| ## Research Papers for Citation | ||
|
|
||
| 1. S. Kato, S. Tokunaga, Y. Maruyama, S. Maeda, M. Hirabayashi, Y. Kitsukawa, A. Monrroy, T. Ando, Y. Fujii, and T. Azumi,``Autoware on Board: Enabling Autonomous Vehicles with Embedded Systems,'' In Proceedings of the 9th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS2018), Porto (aka Oporto), Portugal, Apr. 2018. | ||
|
|
||
| 2. 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. [](http://online.qmags.com/MIC1115/default.aspx?sessionID=7CF18C36BF00A40746B87387B&cid=3230522&eid=19656&pg=62&mode=2#pg62&mode2) | ||
| 1. S. Kato, S. Tokunaga, Y. Maruyama, S. Maeda, M. Hirabayashi, Y. Kitsukawa, A. Monrroy, T. Ando, Y. Fujii, and T. Azumi,``Autoware on Board: Enabling Autonomous Vehicles with Embedded Systems,'' In Proceedings of the 9th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS2018), pp. 287-296, 2018. [Link](https://dl.acm.org/citation.cfm?id=3207930) | ||
|
|
||
| ## Demo Videos | ||
| 2. 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. [Link](https://ieeexplore.ieee.org/document/7368032/) | ||
|
|
||
| ### Public Road Demonstration | ||
| [](https://www.youtube.com/watch?v=5DaQBZvZwAI) | ||
| ## Cloud Services | ||
|
|
||
| ### Test Field Demonstration | ||
| [](https://www.youtube.com/watch?v=zujGfJcZCpQ) | ||
| ### Autoware Online | ||
|
|
||
| ## Instructional Videos | ||
| You may test Autoware at [Autoware Online](http://autoware.online/). No need to install the Autoware repository to your local environment. | ||
|
|
||
| ### Quick Start | ||
| [](https://www.youtube.com/watch?v=NDNcy0C-Has) | ||
| ### Automan | ||
|
|
||
| ### Loading Map Data | ||
| [](https://www.youtube.com/watch?v=OpvTeTaiXo4) | ||
| You may annotate and train your ROSBAG data using your web browser through [Automan](https://www.automan.ai). The trained models can be used for deep neural network algorithms in Autoware, such as SSD and Yolo. | ||
|
|
||
| ### Localization with GNSS | ||
| [](https://www.youtube.com/watch?v=sul-osvg42A) | ||
| ### ROSBAG STORE | ||
|
|
||
| ### Localization without GNSS | ||
| [](https://www.youtube.com/watch?v=ODlxMzGTJzw) | ||
| You may download a number of test and simulation data sets from Tier IV's [ROSBAG STORE](https://rosbag.tier4.jp). Note that free accounts would not allow you to access image data due to privacy matters. | ||
|
|
||
| ### Mapping | ||
| [](https://www.youtube.com/watch?v=ss6Blrz23h8) | ||
| ### Map Tools | ||
|
|
||
| ### Detection with SSD | ||
| [](https://youtu.be/EjamMJjkjBA) | ||
| You may create 3D map data through Tier IV's [Map Tools](https://maptools.tier4.jp/). The 3D map data used in Autoware are composed of point cloud structure data and vector feature data. | ||
|
|
||
| ### Detection with Yolo2 | ||
| [](https://youtu.be/gG_ojWOmDO0) | ||
|
|
||
| ### Detection with Yolo3 | ||
| [](https://www.youtube.com/watch?v=pO4vM4ehI98) | ||
|
|
||
| ### Detection with DPM | ||
| [](https://youtu.be/P_BFQNbudlg) | ||
|
|
||
| ### Detection with Euclidean Clustering | ||
| [](https://youtu.be/Tma2DKMxt4Y) | ||
|
|
||
| ### Traffic Light Recognition | ||
| [](https://youtu.be/KmOdBms9r2w) | ||
|
|
||
| ### Planning with ROSBAG | ||
| [](https://www.youtube.com/watch?v=B3UUKFM6Hqg) | ||
|
|
||
| ### Planning with wf_simulator | ||
| [](https://www.youtube.com/watch?v=HwB2NKqj2yg) | ||
|
|
||
| ### Planning with Hybrid State A* | ||
| [](https://www.youtube.com/watch?v=1WiqAHZHj8U) | ||
|
|
||
| ### Calibration Toolkit | ||
| [](https://www.youtube.com/watch?v=pfBmfgHf6zg) | ||
|
|
||
| See [https://github.com/CPFL/Autoware/wiki/Calibration(EN)](https://github.com/CPFL/Autoware/wiki/Calibration(EN)) | ||
|
|
||
| ### Camera-LiDAR Calibration | ||
| See [Autoware Camera-LiDAR Calibration](ros/src/sensing/fusion/packages/autoware_camera_lidar_calibrator/README.md) | ||
|
|
||
| ### Multi-LiDAR Calibration | ||
| See [Autoware Multi-LiDAR Calibration](ros/src/sensing/fusion/packages/multi_lidar_calibrator/README.md) | ||
|
|
||
| ### Data Processor for Bag File | ||
| [](https://youtu.be/M38Obmy-3Ko) | ||
|
|
||
| ### Ftrace | ||
| [](https://youtu.be/RoIqKgerDUw) | ||
|
|
||
| ## Sample Data | ||
|
|
||
| [Moriyama demo](https://github.com/CPFL/Autoware/wiki/Demo) | ||
|
|
||
| [ROSBAG data for calibration test](http://db3.ertl.jp/autoware/sample_data/kotacho-calibration-sample_20160621.bag.bz2) | ||
|
|
||
| [ROSBAG data for IROS 2016](http://db3.ertl.jp/autoware/sample_data/iros2016_two_vehicle_data.tar.gz) | ||
|
|
||
| ## ROSBAG STORE | ||
| ## License | ||
|
|
||
| You can download many ROSBAG files for research and development of self-driving technology using Autoware. | ||
| [https://rosbag.tier4.jp](https://rosbag.tier4.jp) | ||
| Autoware is provided under the [New BSD License](https://github.com/CPFL/Autoware/blob/master/LICENSE). | ||
|
|
||
| ## Contact | ||
|
|
||
| Autoware Developers (<autoware@googlegroups.com>) | ||
| Autoware Developers Slack Team (https://autoware-developer.slack.com/) | ||
|
|
||
| Autoware Developers Slack Team (https://autoware.herokuapp.com/) | ||
| Autoware Developers (<autoware@googlegroups.com>) | ||
|
|
||
| To subscribe to the Autoware Developers mailing list, | ||
| - If you have a Google account, go to https://groups.google.com/d/forum/autoware, and click the **Apply to Join Group** button. | ||
| - If you don't have a Google account, send an email to [email protected]. | ||
|
|
||
| *** | ||
| <div align="center"><img src="docs/images/autoware_logo_1.png" width="400"/></div> |
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.