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Autoware Documentation

Interface

Autoware Documentation

Introduction
Installation
Installation
- Autoware
  Autoware
  - Docker installation
  - Source installation
- Related tools
  Related tools
- Additional settings for developers
  Additional settings for developers
Tutorials
Tutorials
- Ad hoc simulation
  Ad hoc simulation
  - Planning simulation
  - Rosbag replay simulation
  - Digital twin simulation
    Digital twin simulation
    
    AWSIM simulator
    
    MORAI Sim: Drive
- Scenario simulation
  Scenario simulation
  - Planning simulation
    Planning simulation
    
    Installation
    
    Scenario test simulation
    
    Random test simulation
  - Rosbag replay simulation
    Rosbag replay simulation
    
    Driving Log Replayer
How to guides
How to guides
- Integrating Autoware
  Integrating Autoware
  - Overview
  - 1. Creating your Autoware repositories
    1. Creating your Autoware repositories
    
    Creating Autoware repositories
  - 2. Creating vehicle and sensor model
    
    2. Creating vehicle and sensor model
    
    Creating sensor model
    
    Creating sensor model
    
    Creating individual params
    
    Creating individual params
    
    Creating vehicle model
    
    Creating vehicle model
    
    Calibrating sensors
    
    Calibrating sensors
    
    Starting with TIER IV's CalibrationTools
    
    Starting with TIER IV's CalibrationTools
    
    Extrinsic manual calibration
    
    Extrinsic manual calibration
    
    Lidar-lidar calibration
    
    Lidar-lidar calibration
    
    Ground plane-lidar calibration
    
    Ground plane-lidar calibration
    
    Intrinsic camera calibration
    
    Intrinsic camera calibration
    
    Lidar-camera calibration
    
    Lidar-camera calibration
  - 3. Creating vehicle interface
    3. Creating vehicle interface
    
    Vehicle interface overview
    
    Creating vehicle interface
    
    Ackermann kinematic model
    
    Customizing for differential drive vehicle
  - 4. Creating maps
    
    4. Creating maps
    
    Open-source SLAM algorithms
    
    Open-source SLAM algorithms
    
    FAST-LIO-LC
    
    FAST-LIO-LC
    
    FAST_LIO_SLAM
    
    FAST_LIO_SLAM
    
    FD-SLAM
    
    FD-SLAM
    
    hdl_graph_slam
    
    hdl_graph_slam
    
    IA_LIO_SAM
    
    IA_LIO_SAM
    
    iscloam
    
    iscloam
    
    LeGO-LOAM-BOR
    
    LeGO-LOAM-BOR
    
    LIO-SAM
    
    LIO-SAM
    
    Optimized-SC-F-LOAM
    
    Optimized-SC-F-LOAM
    
    SC-A-LOAM
    
    SC-A-LOAM
    
    SC-LeGO-LOAM
    
    SC-LeGO-LOAM
    
    Converting UTM map to MGRS map
    
    Converting UTM map to MGRS map
    
    Pointcloud map preprocessing
    
    Pointcloud map preprocessing
    
    Creating a vector map
    
    Creating a vector map
    
    Lanelet2
    
    Lanelet2
    
    Crosswalk
    
    Crosswalk
    
    Stop line
    
    Stop line
    
    Traffic light
    
    Traffic light
    
    Speed bump
    
    Speed bump
    
    Detection area
    
    Detection area
  - 5. Launch Autoware
    
    5. Launch Autoware
    
    Localization methods
    
    Localization methods
    
    Eagleye
    
    Perception mode
  - 6. Tuning parameters and performance
    6. Tuning parameters and performance
    
    Evaluating the controller performance
    
    Evaluating real-time performance
- Training Machine Learning Models
  Training Machine Learning Models
  - Training and Deploying Models
- Others
  Others
Design
Design
- Autoware concepts
  Autoware concepts
  - How is Autoware Core/Universe different from Autoware.AI and Autoware.Auto?
- Autoware architecture
  Autoware architecture
  - Sensing
    
    Sensing
    
    Data types
    Data types
    
    GNSS/INS data pre-processing design
    
    Image pre-processing design
    
    Point cloud pre-processing design
    
    Radar data pre-processing design
    
    Ultrasonics data pre-processing design
  - Map
    
    Map
  - Localization
    
    Localization
  - Perception
    
    Perception
  - Planning
    
    Planning
  - Control
    
    Control
  - Vehicle
    
    Vehicle
  - Node diagram
    
    Node diagram
- Autoware interfaces
  Autoware interfaces
  - AD API
    
    AD API
    
    Features
    Features
    
    Cooperation
    
    Fail-safe
    
    Interface Interface
    Table of contents
    
    Related API
    
    Description
    
    Localization
    
    Motion
    
    Operation mode
    
    Perception
    
    Planning factors
    
    Routing
    
    Vehicle doors
    
    Vehicle status
    
    List
    
    List
    
    Types
    
    Types
  - Components
    
    Components
    
    Planning
    
    Control
    
    Localization
    
    Map
    
    Sensing
    
    Perception
    
    Vehicle Interface
    
    Vehicle dimensions
- Configuration management
  Configuration management
Reference HW
Reference HW
Contributing
Contributing
- License
- Coding guidelines
  Coding guidelines
  - Language-specific guidelines
    Language-specific guidelines
    
    C++
    
    Python
    
    Shell scripts
    
    Markdown
    
    CMake
    
    package.xml
    
    Docker
    
    GitHub Actions
  - ROS nodes guidelines
    ROS nodes guidelines
    
    Class design
    
    Console logging
    
    Coordinate system
    
    Directory structure
    
    Launch files
    
    Message guidelines
    
    Parameters
    
    Task scheduling
    
    Topic namespaces
- Testing guidelines
  Testing guidelines
  - Unit testing
  - Integration testing
- Documentation guidelines
  Documentation guidelines
- Pull request guidelines
  Pull request guidelines
- Discussion guidelines
  Discussion guidelines
Datasets
Datasets
Models
Models
Support
Support
- Support guidelines
- Troubleshooting
  Troubleshooting
  - Performance Troubleshooting
- Docs guide
Competitions
Competitions

Interface#

/api/interface/version

Description#

This API provides the interface version of the set of AD APIs. It follows Semantic Versioning in order to provide an intuitive understanding of the changes between versions.