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Autoware Documentation

autoware_adapi_v1_msgs/msg/ManualControlModeStatus

Autoware Documentation

Introduction
Installation
Installation
- Autoware
  Autoware
  - Open AD Kit: containerized workloads for Autoware
  - Source installation
- Related tools
  Related tools
- Additional settings for developers
  Additional settings for developers
  - Console settings for ROS 2
  - Network configuration
    
    Network configuration
    
    DDS settings for ROS 2 and Autoware
    
    Enable `multicast` on `lo`
    
    Communicating across multiple computers with CycloneDDS
Tutorials
Tutorials
- Ad hoc simulation
  Ad hoc simulation
  - Planning simulation
  - Rosbag replay simulation
  - Digital twin simulation
    Digital twin simulation
    
    AWSIM simulator
    
    MORAI Sim: Drive
    
    CARLA simulator
- Scenario simulation
  Scenario simulation
  - Planning simulation
    Planning simulation
    
    Installation
    
    Scenario test simulation
    
    Random test simulation
  - Rosbag replay simulation
    Rosbag replay simulation
    
    Driving Log Replayer
- Components evaluation
  Components evaluation
  - Localization evaluation
    Localization evaluation
    
    Urban environment evaluation
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
    
    Lidar-IMU calibration
    
    Lidar-IMU 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 downsampling
    
    Pointcloud map downsampling
    
    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
    
    Launch vehicle
    
    Launch vehicle
    
    Launch system
    
    Launch system
    
    Launch map
    
    Launch map
    
    Launch sensing
    
    Launch sensing
    
    Launch localization
    
    Launch localization
    
    Eagleye
    
    Eagleye
    
    Launch perception
    
    Launch perception
    
    Launch planning
    
    Launch planning
    
    Launch control
    
    Launch control
  - 6. Tuning parameters and performance
    6. Tuning parameters and performance
    
    Evaluating the controller performance
    
    Evaluating real-time performance
  - 7. AWSIM Integration
    
    7. AWSIM Integration
- 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
    
    Ultrasonics data pre-processing design
    
    Radar data
    Radar data
    
    Radar objects data pre-processing design
    
    Radar pointcloud data pre-processing design
    
    Reference implementations
    Reference implementations
    
    Data message for radars
    
    Device driver for radars
  - Map
    
    Map
    
    Map requirements
    Map requirements
    
    Vector map requirements overview
    
    Vector map requirements overview
    
    Category area
    
    Category crosswalk
    
    Category intersection
    
    Category lane
    
    Category others
    
    Category stop line
    
    Category traffic light
  - Localization
    
    Localization
  - Perception
    
    Perception
    
    Perception Component Reference Implementation Design
    
    Reference implementations
    Reference implementations
    
    Radar based 3d detector
    Radar based 3d detector
    
    Radar faraway dynamic objects detection with radar objects
    
    Radar based 3D detector
  - Planning
    
    Planning
  - Control
    
    Control
  - Vehicle
    
    Vehicle
  - Node diagram
    
    Node diagram
- Autoware interfaces
  Autoware interfaces
  - AD API
    
    AD API
    
    Release notes
    
    List
    
    List
    
    Types
    
    Types
    
    Features
    Features
    
    Cooperation
    
    Diagnostics
    
    Fail-safe
    
    Heartbeat
    
    Interface
    
    Localization
    
    Manual control
    
    Motion
    
    Operation mode
    
    Perception
    
    Planning factors
    
    Routing
    
    Vehicle doors
    
    Vehicle status
  - 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
    
    Topic message handling
    
    Topic message handling
    
    [supplement] Obtain a received message through intra-process communication
    
    [supplement] Use rclcpp::WaitSet
- Testing guidelines
  Testing guidelines
  - Unit testing
  - Integration testing
- Documentation guidelines
  Documentation guidelines
- Pull request guidelines
  Pull request guidelines
- Discussion guidelines
  Discussion guidelines
Datasets
Datasets
- Data Anonymization
  Data Anonymization
Models
Models
Support
Support
- Support guidelines
- Troubleshooting
  Troubleshooting
  - Performance Troubleshooting
- Docs guide
Competitions
Competitions

autoware_adapi_v1_msgs/msg/ManualControlModeStatus#

Definition#

builtin_interfaces/Time stamp
autoware_adapi_v1_msgs/ManualControlMode mode

This type uses#

autoware_adapi_v1_msgs/msg/ManualControlMode

This type is used by#

None