diff --git a/docs/autoware-competitions/index.md b/docs/autoware-competitions/index.md
index 93a7a831593..986f5ca1da7 100644
--- a/docs/autoware-competitions/index.md
+++ b/docs/autoware-competitions/index.md
@@ -6,7 +6,7 @@ This page is a collection of the links to the competitions that are related to t
| :-----------------------------------------------------------: | :------: | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| | Ongoing | **[Autoware / TIER IV Challenge 2023](https://autoware.org/autoware-challenge-2023)** **Date:** May 15, 2023 - Nov. 1st, 2023
As one of the main contributors of Autoware, TIER IV has been facing many difficult challenges through development, and TIER IV would like to sponsor a challenge to solve such engineering challenges. Any researchers, students, individuals or organizations are welcome to participate and submit their solution to any of the challenges we propose. |
| | Finished | **[Japan Automotive AI Challenge 2023 (Integration)](https://www.jsae.or.jp/jaaic/2023_summary.php)** **Registration:** June 5, 2023 - July 14, 2023 **Qualifiers:** July 3, 2023 - Aug. 31, 2023 **Finals:** Nov. 12, 2023
In this competition, we focus on challenging tasks posed by autonomous driving in factory environments and aim to develop Autoware-based AD software that can overcome them. The qualifiers use the [digital twin autonomous driving simulator AWSIM](https://tier4.github.io/AWSIM/) to complete specific tasks within a virtual environment. Teams that make it to the finals have the opportunity to run their software on actual vehicles in a test course in Japan. |
-| | Ongoing | **[Japan Automotive AI Challenge 2023 (Simulation)](https://www.jsae.or.jp/jaaic/2023_simulation.php)** **Registration:** Nov 6, 2023 - Dec 28, 2023 **Date:** Dec 4, 2023 - Jan. 31, 2024
This contest is a software development contest with a motorsports theme. Participants will develop autonomous driving software based on [Autoware.Universe](https://github.com/autowarefoundation/autoware.universe), and integrate it into a racing car that runs in the End to End simulation space (AWSIM). The goal is simple, win the race while driving safely! |
+| | Ongoing | **[Japan Automotive AI Challenge 2023 (Simulation)](https://www.jsae.or.jp/jaaic/2023_simulation.php)** **Registration:** Nov 6, 2023 - Dec 28, 2023 **Date:** Dec 4, 2023 - Jan. 31, 2024
- autoware.universe parameter (config) files...
+ autoware_universe parameter (config) files...
diff --git a/docs/how-to-guides/integrating-autoware/launch-autoware/index.md b/docs/how-to-guides/integrating-autoware/launch-autoware/index.md
index 7b8b2c8e674..ff3ffd3ed5a 100644
--- a/docs/how-to-guides/integrating-autoware/launch-autoware/index.md
+++ b/docs/how-to-guides/integrating-autoware/launch-autoware/index.md
@@ -161,7 +161,7 @@ but if you want to use `camera-lidar fusion` you need to change your perception
If you want to use traffic light recognition and visualization,
you can set `traffic_light_recognition/enable_fine_detection` as true (default).
Please check
-[traffic_light_fine_detector](https://autowarefoundation.github.io/autoware.universe/main/perception/autoware_traffic_light_fine_detector/)
+[traffic_light_fine_detector](https://autowarefoundation.github.io/autoware_universe/main/perception/autoware_traffic_light_fine_detector/)
page for more information.
If you don't want to use traffic light classifier, then you can disable it:
@@ -191,7 +191,7 @@ ros2 launch autoware_launch autoware_launch.launch.xml map_path:=
```
After launching Autoware, we need to initialize our vehicle on our map.
-If you set [gnss_poser](https://autowarefoundation.github.io/autoware.universe/main/sensing/autoware_gnss_poser/) for your GNSS/INS sensor at `gnss.launch.xml`,
+If you set [gnss_poser](https://autowarefoundation.github.io/autoware_universe/main/sensing/autoware_gnss_poser/) for your GNSS/INS sensor at `gnss.launch.xml`,
then gnss_poser will send pose for initialization.
If you don't have a GNSS sensor, then you need to set initial pose manually.
diff --git a/docs/how-to-guides/integrating-autoware/launch-autoware/localization/index.md b/docs/how-to-guides/integrating-autoware/launch-autoware/localization/index.md
index 1daa54f11f1..f17f1943e28 100644
--- a/docs/how-to-guides/integrating-autoware/launch-autoware/localization/index.md
+++ b/docs/how-to-guides/integrating-autoware/launch-autoware/localization/index.md
@@ -6,7 +6,7 @@ The Autoware localization stacks start
launching at `autoware_launch.xml` as we mentioned at [Launch Autoware](../index.md) page.
The `autoware_launch` package includes `tier4_localization_component.launch.xml`
for starting localization launch files invocation from `autoware_launch.xml`.
-This diagram describes some of the Autoware localization launch files flow at `autoware_launch` and `autoware.universe` packages.
+This diagram describes some of the Autoware localization launch files flow at `autoware_launch` and `autoware_universe` packages.
{ align=center }
@@ -29,17 +29,17 @@ This diagram describes some of the Autoware localization launch files flow at `a
## tier4_localization_component.launch.xml
The `tier4_localization_component.launch.xml` launch file is the main localization component launch at the `autoware_launch` package.
-This launch file calls `localization.launch.xml` at [tier4_localization_launch](https://github.com/autowarefoundation/autoware.universe/tree/main/launch/tier4_localization_launch) package from `autoware.universe` repository.
+This launch file calls `localization.launch.xml` at [tier4_localization_launch](https://github.com/autowarefoundation/autoware_universe/tree/main/launch/tier4_localization_launch) package from `autoware_universe` repository.
We can modify localization launch arguments at tier4_localization_component.launch.xml.
The current localization launcher implemented by TIER IV supports multiple localization methods, both pose estimators and twist estimators.
`tier4_localization_component.launch.xml` has two arguments to select which estimators to launch:
- **`pose_source:`** This argument specifies the pose_estimator, currently supporting `ndt` (default), `yabloc`, `artag` and `eagleye` for localization.
- By default, Autoware launches [ndt_scan_matcher](https://github.com/autowarefoundation/autoware.universe/tree/main/localization/autoware_ndt_scan_matcher) for pose estimator.
+ By default, Autoware launches [ndt_scan_matcher](https://github.com/autowarefoundation/autoware_universe/tree/main/localization/autoware_ndt_scan_matcher) for pose estimator.
You can use YabLoc as a camera-based localization method.
For more details on YabLoc,
- please refer to the [README of YabLoc](https://github.com/autowarefoundation/autoware.universe/blob/main/localization/yabloc/README.md) in autoware.universe.
+ please refer to the [README of YabLoc](https://github.com/autowarefoundation/autoware_universe/blob/main/localization/yabloc/README.md) in autoware_universe.
Also, you can use Eagleye as a GNSS & IMU & wheel odometry-based localization method. For more details on Eagleye, please refer to the [Eagleye](./eagleye/index.md).
You can set `pose_source` argument on `tier4_localization_component.launch.xml`,
@@ -59,7 +59,7 @@ The current localization launcher implemented by TIER IV supports multiple local
- **`twist_source:`** This argument specifies the twist_estimator, currently supporting `gyro_odom` (default), and `eagleye`.
By default,
- Autoware launches [gyro_odometer](https://github.com/autowarefoundation/autoware.universe/tree/main/localization/autoware_gyro_odometer) for twist estimator.
+ Autoware launches [gyro_odometer](https://github.com/autowarefoundation/autoware_universe/tree/main/localization/autoware_gyro_odometer) for twist estimator.
Also, you can use eagleye for the twist source, please refer to the [Eagleye](./eagleye/index.md).
If you want to change your twist source to eagleye, you can update `tier4_localization_component.launch.xml` like:
@@ -76,7 +76,7 @@ The current localization launcher implemented by TIER IV supports multiple local
- **`input_pointcloud:`** This argument specifies the input pointcloud of the localization pointcloud pipeline. The default value is
`/sensing/lidar/top/outlier_filtered/pointcloud` which
- is output of the [pointcloud pre-processing](https://autowarefoundation.github.io/autoware.universe/main/sensing/autoware_pointcloud_preprocessor/) pipeline from sensing.
+ is output of the [pointcloud pre-processing](https://autowarefoundation.github.io/autoware_universe/main/sensing/autoware_pointcloud_preprocessor/) pipeline from sensing.
You can change this value according to your LiDAR topic name,
or you can choose to use concatenated point cloud:
@@ -95,7 +95,7 @@ you can add this argument on `tier4_localization_component.launch.xml` launch fi
```
**Note:** Gyro odometer input topic provided from velocity converter package. This package will be launched at sensor_kit. For more information,
-please check [velocity converter package](https://github.com/autowarefoundation/autoware.universe/tree/main/sensing/autoware_vehicle_velocity_converter).
+please check [velocity converter package](https://github.com/autowarefoundation/autoware_universe/tree/main/sensing/autoware_vehicle_velocity_converter).
## Note when using non NDT pose estimator
@@ -106,6 +106,6 @@ please check [velocity converter package](https://github.com/autowarefoundation/
Depending on the parameters of emergencies, this could escalate to a full emergency, preventing autonomous driving.
To work around this, please modify the configuration file of the system_error_monitor.
-In the [system_error_monitor.param.yaml](https://github.com/autowarefoundation/autoware.universe/blob/main/system/system_error_monitor/config/system_error_monitor.param.yaml) file, `/autoware/localization/performance_monitoring/matching_score` represents the aggregated diagnostics for NDT.
+In the [system_error_monitor.param.yaml](https://github.com/autowarefoundation/autoware_universe/blob/main/system/system_error_monitor/config/system_error_monitor.param.yaml) file, `/autoware/localization/performance_monitoring/matching_score` represents the aggregated diagnostics for NDT.
To prevent emergencies even when NDT is not launched, remove this entry from the configuration.
-Note that the module name `/performance_monitoring/matching_score` is specified in [diagnostics_aggregator/localization.param.yaml](https://github.com/autowarefoundation/autoware.universe/blob/main/system/system_error_monitor/config/diagnostic_aggregator/localization.param.yaml).
+Note that the module name `/performance_monitoring/matching_score` is specified in [diagnostics_aggregator/localization.param.yaml](https://github.com/autowarefoundation/autoware_universe/blob/main/system/system_error_monitor/config/diagnostic_aggregator/localization.param.yaml).
diff --git a/docs/how-to-guides/integrating-autoware/launch-autoware/map/index.md b/docs/how-to-guides/integrating-autoware/launch-autoware/map/index.md
index 9c0c842b1db..cc2544e6400 100644
--- a/docs/how-to-guides/integrating-autoware/launch-autoware/map/index.md
+++ b/docs/how-to-guides/integrating-autoware/launch-autoware/map/index.md
@@ -7,7 +7,7 @@ launching at `autoware_launch.xml` as we mentioned at [Launch Autoware](../index
The `autoware_launch` package includes `tier4_map_component.launch.xml`
for starting map launch files invocation from `autoware_launch.xml`.
This diagram describes some of the Autoware map launch files flow at `autoware_launch`
-and `autoware.universe` packages.
+and `autoware_universe` packages.
{ align=center }
diff --git a/docs/how-to-guides/integrating-autoware/launch-autoware/perception/index.md b/docs/how-to-guides/integrating-autoware/launch-autoware/perception/index.md
index 3052f04b783..98c322aad43 100644
--- a/docs/how-to-guides/integrating-autoware/launch-autoware/perception/index.md
+++ b/docs/how-to-guides/integrating-autoware/launch-autoware/perception/index.md
@@ -6,7 +6,7 @@ The Autoware perception stacks start
launching at `autoware_launch.xml` as we mentioned at [Launch Autoware](../index.md) page.
The `autoware_launch` package includes `tier4_perception_component.launch.xml`
for starting perception launch files invocation from `autoware_launch.xml`.
-This diagram describes some of the Autoware perception launch files flow at `autoware_launch` and `autoware.universe` packages.
+This diagram describes some of the Autoware perception launch files flow at `autoware_launch` and `autoware_universe` packages.
{ align=center }
@@ -29,7 +29,7 @@ This diagram describes some of the Autoware perception launch files flow at `aut
## tier4_perception_component.launch.xml
The `tier4_perception_component.launch.xml` launch file is the main perception component launch at the `autoware_launch` package.
-This launch file calls `perception.launch.xml` at [tier4_perception_launch](https://github.com/autowarefoundation/autoware.universe/tree/main/launch/tier4_perception_launch) package from `autoware.universe` repository.
+This launch file calls `perception.launch.xml` at [tier4_perception_launch](https://github.com/autowarefoundation/autoware_universe/tree/main/launch/tier4_perception_launch) package from `autoware_universe` repository.
We can modify perception launch arguments at tier4_perception_component.launch.xml.
Also,
we can add any other necessary arguments
@@ -37,7 +37,7 @@ that we want
to change it since `tier4_perception_component.launch.xml` is the top-level launch file of other perception launch files.
Here are some predefined perception launch arguments:
-- **`occupancy_grid_map_method:`** This argument determines the occupancy grid map method for perception stack. Please check [probabilistic_occupancy_grid_map](https://autowarefoundation.github.io/autoware.universe/main/perception/autoware_probabilistic_occupancy_grid_map/) package for detailed information.
+- **`occupancy_grid_map_method:`** This argument determines the occupancy grid map method for perception stack. Please check [probabilistic_occupancy_grid_map](https://autowarefoundation.github.io/autoware_universe/main/perception/autoware_probabilistic_occupancy_grid_map/) package for detailed information.
The default probabilistic occupancy grid map method is `pointcloud_based_occupancy_grid_map`.
If you want to change it to the `laserscan_based_occupancy_grid_map`, you can change it here:
@@ -47,7 +47,7 @@ Here are some predefined perception launch arguments:
```
- **`detected_objects_filter_method:`** This argument determines the filter method for detected objects.
- Please check [detected_object_validation](https://autowarefoundation.github.io/autoware.universe/main/perception/autoware_detected_object_validation/) package for detailed information about lanelet and position filter.
+ Please check [detected_object_validation](https://autowarefoundation.github.io/autoware_universe/main/perception/autoware_detected_object_validation/) package for detailed information about lanelet and position filter.
The default detected object filter method is `lanelet_filter`.
If you want to change it to the `position_filter`, you can change it here:
@@ -57,7 +57,7 @@ Here are some predefined perception launch arguments:
```
- **`detected_objects_validation_method:`** This argument determines the validation method for detected objects.
- Please check [detected_object_validation](https://autowarefoundation.github.io/autoware.universe/main/perception/autoware_detected_object_validation/) package for detailed information about validation methods.
+ Please check [detected_object_validation](https://autowarefoundation.github.io/autoware_universe/main/perception/autoware_detected_object_validation/) package for detailed information about validation methods.
The default detected object filter method is `obstacle_pointcloud`.
If you want to change it to the `occupancy_grid`, you can change it here,
but remember it requires `laserscan_based_occupancy_grid_map` method as `occupancy_grid_map_method`:
@@ -82,14 +82,14 @@ Here are some predefined perception launch arguments:
The predefined `tier4_perception_component.launch.xml` arguments explained above,
but there is the lot of perception arguments
-included in `perception.launch.xml` launch file at [tier4_perception_launch](https://github.com/autowarefoundation/autoware.universe/tree/main/launch/tier4_perception_launch).
-Since we didn't fork `autoware.universe` repository,
+included in `perception.launch.xml` launch file at [tier4_perception_launch](https://github.com/autowarefoundation/autoware_universe/tree/main/launch/tier4_perception_launch).
+Since we didn't fork `autoware_universe` repository,
we can add the necessary launch argument to tier4_perception_component.launch.xml file.
Please follow the guidelines for some examples.
## perception.launch.xml
-The `perception.launch.xml` launch file is the main perception launch at the `autoware.universe`.
+The `perception.launch.xml` launch file is the main perception launch at the `autoware_universe`.
This launch file calls necessary perception launch files
as we mentioned [`Autoware perception launch flow diagram`](#overview) above.
The top-level launch file of `perception.launch.xml` is `tier4_perception_component.launch.xml`,
@@ -99,7 +99,7 @@ we will apply these changes `tier4_perception_component.launch.xml` instead of `
Here are some example changes for the perception pipeline:
- **`remove_unknown:`** This parameter determines the remove unknown objects at camera-lidar fusion.
- Please check [roi_cluster_fusion](https://github.com/autowarefoundation/autoware.universe/blob/main/perception/autoware_image_projection_based_fusion/docs/roi-cluster-fusion.md) node for detailed information.
+ Please check [roi_cluster_fusion](https://github.com/autowarefoundation/autoware_universe/blob/main/perception/autoware_image_projection_based_fusion/docs/roi-cluster-fusion.md) node for detailed information.
The default value is `true`.
If you want to change it to the `false`,
you can add this argument to `tier4_perception_component.launch.xml`,
diff --git a/docs/how-to-guides/integrating-autoware/launch-autoware/planning/index.md b/docs/how-to-guides/integrating-autoware/launch-autoware/planning/index.md
index fed90b465b4..dd4f14ea205 100644
--- a/docs/how-to-guides/integrating-autoware/launch-autoware/planning/index.md
+++ b/docs/how-to-guides/integrating-autoware/launch-autoware/planning/index.md
@@ -6,7 +6,7 @@ The Autoware planning stacks start
launching at `autoware_launch.xml` as mentioned on the [Launch Autoware](../index.md) page.
The `autoware_launch` package includes `tier4_planning_component.launch.xml`
for initiating planning launch files invocation from `autoware_launch.xml`.
-The diagram below illustrates the flow of Autoware planning launch files within the autoware_launch and autoware.universe packages.
+The diagram below illustrates the flow of Autoware planning launch files within the autoware_launch and autoware_universe packages.
{ align=center }
@@ -29,7 +29,7 @@ The diagram below illustrates the flow of Autoware planning launch files within
## tier4_planning_component.launch.xml
The `tier4_planning_component.launch.xml` launch file is the main planning component launch at the `autoware_launch` package.
-This launch file calls `planning.launch.xml` at [tier4_planning_launch](https://github.com/autowarefoundation/autoware.universe/tree/main/launch/tier4_planning_launch) package from `autoware.universe` repository.
+This launch file calls `planning.launch.xml` at [tier4_planning_launch](https://github.com/autowarefoundation/autoware_universe/tree/main/launch/tier4_planning_launch) package from `autoware_universe` repository.
We can modify planning launch arguments at tier4_planning_component.launch.xml.
Also,
we can add any other necessary arguments
@@ -40,7 +40,7 @@ Here are some predefined planning launch arguments:
- **`use_experimental_lane_change_function:`** This argument enables
`enable_collision_check_at_prepare_phase`, `use_predicted_path_outside_lanelet`,
and `use_all_predicted_path` options for Autoware for experimental lane changing
- (for more information, please refer to [lane_change documentation](https://autowarefoundation.github.io/autoware.universe/main/planning/behavior_path_planner/docs/behavior_path_planner_lane_change_design/)).
+ (for more information, please refer to [lane_change documentation](https://autowarefoundation.github.io/autoware_universe/main/planning/behavior_path_planner/docs/behavior_path_planner_lane_change_design/)).
The default value is True.
To set it to False, make the following change in the `tier4_planning_component.launch.xml` file:
@@ -49,8 +49,8 @@ Here are some predefined planning launch arguments:
+
```
-- **`cruise_planner_type:`** There are two types of cruise planners in Autoware: [obstacle_stop_planner](https://autowarefoundation.github.io/autoware.universe/main/planning/obstacle_stop_planner/)
- and [obstacle_cruise_planner](https://autowarefoundation.github.io/autoware.universe/main/planning/obstacle_cruise_planner/). For specifications on these cruise planner types,
+- **`cruise_planner_type:`** There are two types of cruise planners in Autoware: [obstacle_stop_planner](https://autowarefoundation.github.io/autoware_universe/main/planning/obstacle_stop_planner/)
+ and [obstacle_cruise_planner](https://autowarefoundation.github.io/autoware_universe/main/planning/obstacle_cruise_planner/). For specifications on these cruise planner types,
please refer to the package documentation. The default cruise planner is `obstacle_stop_planner`.
To change it to obstacle_cruise_planner, update the argument value in the `tier4_planning_component.launch.xml` file:
@@ -59,7 +59,7 @@ Here are some predefined planning launch arguments:
+
```
-- **`use_surround_obstacle_check:`** This argument enables the [surround_obstacle_checker](https://autowarefoundation.github.io/autoware.universe/main/planning/surround_obstacle_checker/)
+- **`use_surround_obstacle_check:`** This argument enables the [surround_obstacle_checker](https://autowarefoundation.github.io/autoware_universe/main/planning/surround_obstacle_checker/)
for Autoware. If you want to disable it, you can do in the
`tier4_planning_component.launch.xml` file:
@@ -69,7 +69,7 @@ Here are some predefined planning launch arguments:
```
- **`velocity_smoother_type:`** This argument specifies the type of smoother
- for the [motion_velocity_smoother](https://autowarefoundation.github.io/autoware.universe/main/planning/motion_velocity_smoother/) package. Please consult the documentation
+ for the [motion_velocity_smoother](https://autowarefoundation.github.io/autoware_universe/main/planning/motion_velocity_smoother/) package. Please consult the documentation
for detailed information about available smoother types. For instance, if
you wish to change your smoother type from JerkFiltered to L2, you can do
in the tier4_planning_component.launch.xml file.:
diff --git a/docs/how-to-guides/integrating-autoware/launch-autoware/sensing/index.md b/docs/how-to-guides/integrating-autoware/launch-autoware/sensing/index.md
index d512eadda94..403e57fd5d3 100644
--- a/docs/how-to-guides/integrating-autoware/launch-autoware/sensing/index.md
+++ b/docs/how-to-guides/integrating-autoware/launch-autoware/sensing/index.md
@@ -6,7 +6,7 @@ The Autoware sensing stacks start
launching at `autoware_launch.xml` as we mentioned at [Launch Autoware](../index.md) page.
The `autoware_launch` package includes `tier4_sensing_component.launch.xml`
for starting sensing launch files invocation from `autoware_launch.xml`.
-This diagram describes some of the Autoware sensing launch files flow at `autoware_launch` and `autoware.universe` packages.
+This diagram describes some of the Autoware sensing launch files flow at `autoware_launch` and `autoware_universe` packages.
{ align=center }
diff --git a/docs/how-to-guides/integrating-autoware/launch-autoware/system/index.md b/docs/how-to-guides/integrating-autoware/launch-autoware/system/index.md
index 871c15e8ab5..70da66de94f 100644
--- a/docs/how-to-guides/integrating-autoware/launch-autoware/system/index.md
+++ b/docs/how-to-guides/integrating-autoware/launch-autoware/system/index.md
@@ -6,7 +6,7 @@ The Autoware system stacks start
launching at `autoware_launch.xml` as we mentioned at [Launch Autoware](../index.md) page.
The `autoware_launch` package includes `tier4_system_component.launch.xml`
for starting system launch files invocation from `autoware_launch.xml`.
-This diagram describes some of the Autoware system launch files flow at `autoware_launch` and `autoware.universe` packages.
+This diagram describes some of the Autoware system launch files flow at `autoware_launch` and `autoware_universe` packages.
{ align=center }
@@ -29,15 +29,15 @@ This diagram describes some of the Autoware system launch files flow at `autowar
As described in the flow diagram of the system launch pipeline,
the `system.launch.xml` from the `tier4_system_launch` package directly launches the following packages:
-- [system_monitor](https://autowarefoundation.github.io/autoware.universe/main/system/system_monitor/)
-- [component_interface_tools](https://autowarefoundation.github.io/autoware.universe/main/common/component_interface_tools/)
-- [component_state_monitor](https://autowarefoundation.github.io/autoware.universe/main/system/component_state_monitor/)
-- [system_error_monitor](https://autowarefoundation.github.io/autoware.universe/main/system/system_error_monitor/)
-- [emergency_handler](https://autowarefoundation.github.io/autoware.universe/main/system/emergency_handler/)
-- [duplicated_node_checker](https://autowarefoundation.github.io/autoware.universe/main/system/duplicated_node_checker/)
-- [mrm_comfortable_stop_operator](https://autowarefoundation.github.io/autoware.universe/main/system/mrm_comfortable_stop_operator/)
-- [mrm_emergency_stop_operator](https://autowarefoundation.github.io/autoware.universe/main/system/mrm_emergency_stop_operator/)
-- [dummy_diag_publisher](https://autowarefoundation.github.io/autoware.universe/main/system/dummy_diag_publisher/)
+- [system_monitor](https://autowarefoundation.github.io/autoware_universe/main/system/system_monitor/)
+- [component_interface_tools](https://autowarefoundation.github.io/autoware_universe/main/common/component_interface_tools/)
+- [component_state_monitor](https://autowarefoundation.github.io/autoware_universe/main/system/component_state_monitor/)
+- [system_error_monitor](https://autowarefoundation.github.io/autoware_universe/main/system/system_error_monitor/)
+- [emergency_handler](https://autowarefoundation.github.io/autoware_universe/main/system/emergency_handler/)
+- [duplicated_node_checker](https://autowarefoundation.github.io/autoware_universe/main/system/duplicated_node_checker/)
+- [mrm_comfortable_stop_operator](https://autowarefoundation.github.io/autoware_universe/main/system/mrm_comfortable_stop_operator/)
+- [mrm_emergency_stop_operator](https://autowarefoundation.github.io/autoware_universe/main/system/mrm_emergency_stop_operator/)
+- [dummy_diag_publisher](https://autowarefoundation.github.io/autoware_universe/main/system/dummy_diag_publisher/)
We don't have many modification options in the system launching files
(as the parameters are included in config files),
diff --git a/docs/how-to-guides/integrating-autoware/launch-autoware/vehicle/index.md b/docs/how-to-guides/integrating-autoware/launch-autoware/vehicle/index.md
index 468cf7948a1..39df0b7dd7c 100644
--- a/docs/how-to-guides/integrating-autoware/launch-autoware/vehicle/index.md
+++ b/docs/how-to-guides/integrating-autoware/launch-autoware/vehicle/index.md
@@ -5,7 +5,7 @@
The Autoware vehicle stacks begin launching with autoware_launch.xml as mentioned on the
[Launch Autoware](../index.md) page,
and the tier4_vehicle.launch.xml is called in this context. The following diagram describes some of
-the Autoware vehicle launch file flow within the `autoware_launch` and `autoware.universe` packages.
+the Autoware vehicle launch file flow within the `autoware_launch` and `autoware_universe` packages.
{ align=center width=720}
diff --git a/docs/how-to-guides/integrating-autoware/tuning-parameters-and-performance/evaluating-controller-performance.md b/docs/how-to-guides/integrating-autoware/tuning-parameters-and-performance/evaluating-controller-performance.md
index 7f6d202269a..d41fa011350 100644
--- a/docs/how-to-guides/integrating-autoware/tuning-parameters-and-performance/evaluating-controller-performance.md
+++ b/docs/how-to-guides/integrating-autoware/tuning-parameters-and-performance/evaluating-controller-performance.md
@@ -5,7 +5,7 @@ This page shows how to use `control_performance_analysis` package to evaluate th
`control_performance_analysis` is the package to analyze the tracking performance of a control module
and monitor the driving status of the vehicle.
-If you need more detailed information about package, refer to the [control_performance_analysis](https://github.com/autowarefoundation/autoware.universe/tree/main/control/control_performance_analysis).
+If you need more detailed information about package, refer to the [control_performance_analysis](https://github.com/autowarefoundation/autoware_universe/tree/main/control/control_performance_analysis).
## How to use
@@ -37,7 +37,7 @@ ros2 run plotjuggler plotjuggler
- If you do not have PlotJuggler in your computer, please refer [here](https://github.com/facontidavide/PlotJuggler#installation) for installation guideline.
-#### 5. Increase the buffer size (maximum is 100), and import the layout from `/autoware.universe/control/control_performance_analysis/config/controller_monitor.xml`
+#### 5. Increase the buffer size (maximum is 100), and import the layout from `/autoware_universe/control/control_performance_analysis/config/controller_monitor.xml`
- After import the layout, please specify the topics that are listed below.
@@ -72,4 +72,4 @@ ros2 run plotjuggler plotjuggler
-- If you see too much noised curve in plots, you can adjust the `odom_interval` and `low_pass_filter_gain` from [here](https://github.com/autowarefoundation/autoware.universe/blob/main/control/control_performance_analysis/config/control_performance_analysis.param.yaml) to avoid noised data.
+- If you see too much noised curve in plots, you can adjust the `odom_interval` and `low_pass_filter_gain` from [here](https://github.com/autowarefoundation/autoware_universe/blob/main/control/control_performance_analysis/config/control_performance_analysis.param.yaml) to avoid noised data.
diff --git a/docs/how-to-guides/integrating-autoware/tuning-parameters-and-performance/evaluating-real-time-performance.md b/docs/how-to-guides/integrating-autoware/tuning-parameters-and-performance/evaluating-real-time-performance.md
index 5005973432f..5b09ebcbfe7 100644
--- a/docs/how-to-guides/integrating-autoware/tuning-parameters-and-performance/evaluating-real-time-performance.md
+++ b/docs/how-to-guides/integrating-autoware/tuning-parameters-and-performance/evaluating-real-time-performance.md
@@ -114,7 +114,7 @@ In this section, we will present several case studies that demonstrate the perfo
### Sensing component
First, we will explain the procedure for performance improvement, taking the node `ring_outlier_filter` as an example.
-Refer to the [Pull Request](https://github.com/autowarefoundation/autoware.universe/pull/3014) for details.
+Refer to the [Pull Request](https://github.com/autowarefoundation/autoware_universe/pull/3014) for details.
The following figure is a time-series plot of the turnaround time of the main processing part of `ring_outlier_filter`, analyzed as described in the "Performance Measurement" section above.
@@ -200,6 +200,6 @@ for ( area : detection_areas )
```
By using O(N) algorithm for minimum enclosing circle, the computational complexity of this program is reduced to almost O(N \* (N + M)) (note that the exact computational complexity does not really change).
-If you are interested, refer to the [Pull Request](https://github.com/autowarefoundation/autoware.universe/pull/2846).
+If you are interested, refer to the [Pull Request](https://github.com/autowarefoundation/autoware_universe/pull/2846).
Similar to this example, in the planning component, we take into consideration thousands to tens of thousands of point clouds, thousands of points in a path representing our own route, and polygons representing obstacles and detection areas in the surroundings, and we repeatedly create paths based on them. Therefore, we access the contents of the point clouds and paths multiple times using for-loops. In most cases, the bottleneck lies in these naive for-loops. Here, understanding Big O notation and reducing the order of computational complexity directly leads to performance improvements.
diff --git a/docs/how-to-guides/others/an-example-procedure-for-adding-and-evaluating-a-new-node.md b/docs/how-to-guides/others/an-example-procedure-for-adding-and-evaluating-a-new-node.md
index 7eecfc8560c..e558b4908a5 100644
--- a/docs/how-to-guides/others/an-example-procedure-for-adding-and-evaluating-a-new-node.md
+++ b/docs/how-to-guides/others/an-example-procedure-for-adding-and-evaluating-a-new-node.md
@@ -39,10 +39,10 @@ When developing a new node, it could be beneficial to reference a package that i
It is advisable to thoroughly read the [Design page](https://autowarefoundation.github.io/autoware-documentation/main/design/), contemplate the addition or replacement of nodes in Autoware, and then implement your solution.
-For example, a node doing NDT, a LiDAR-based localization method, is [ndt_scan_matcher](https://github.com/autowarefoundation/autoware.universe/tree/main/localization/autoware_ndt_scan_matcher).
+For example, a node doing NDT, a LiDAR-based localization method, is [ndt_scan_matcher](https://github.com/autowarefoundation/autoware_universe/tree/main/localization/autoware_ndt_scan_matcher).
If you want to replace this with a different approach, implement a node which produces the same topics and provides the same services.
-`ndt_scan_matcher` is launched as [pose_estimator](https://github.com/autowarefoundation/autoware.universe/blob/main/launch/tier4_localization_launch/launch/pose_twist_estimator/ndt_scan_matcher.launch.xml), so it is necessary to replace the launch file as well.
+`ndt_scan_matcher` is launched as [pose_estimator](https://github.com/autowarefoundation/autoware_universe/blob/main/launch/tier4_localization_launch/launch/pose_twist_estimator/ndt_scan_matcher.launch.xml), so it is necessary to replace the launch file as well.
## 4. Evaluating by a rosbag-based simulator
diff --git a/docs/how-to-guides/others/fixing-dependent-package-versions.md b/docs/how-to-guides/others/fixing-dependent-package-versions.md
index c496a05969e..35edb0c62c7 100644
--- a/docs/how-to-guides/others/fixing-dependent-package-versions.md
+++ b/docs/how-to-guides/others/fixing-dependent-package-versions.md
@@ -1,8 +1,8 @@
# Fixing dependent package versions
Autoware manages dependent package versions in autoware.repos.
-For example, let's say you make a branch in autoware.universe and add new features.
-Suppose you update other dependencies with `vcs pull` after cutting a branch from autoware.universe. Then the version of autoware.universe you are developing and other dependencies will become inconsistent, and the entire Autoware build will fail.
+For example, let's say you make a branch in autoware_universe and add new features.
+Suppose you update other dependencies with `vcs pull` after cutting a branch from autoware_universe. Then the version of autoware_universe you are developing and other dependencies will become inconsistent, and the entire Autoware build will fail.
We recommend saving the dependent package versions by executing the following command when starting the development.
```bash
diff --git a/docs/how-to-guides/others/reducing-start-delays.md b/docs/how-to-guides/others/reducing-start-delays.md
index f3d14dd29b0..66b6ead888c 100644
--- a/docs/how-to-guides/others/reducing-start-delays.md
+++ b/docs/how-to-guides/others/reducing-start-delays.md
@@ -35,9 +35,9 @@ To guarantee passenger comfort,
some Autoware modules implement filters on the jerk of the vehicle, preventing sudden changes in acceleration.
For example,
-the [`vehicle_cmd_gate`](https://autowarefoundation.github.io/autoware.universe/main/control/vehicle_cmd_gate/)
+the [`vehicle_cmd_gate`](https://autowarefoundation.github.io/autoware_universe/main/control/vehicle_cmd_gate/)
filters the acceleration command generated by the controller
-and [was previously introducing significant delays](https://github.com/autowarefoundation/autoware.universe/pull/3385)
+and [was previously introducing significant delays](https://github.com/autowarefoundation/autoware_universe/pull/3385)
when transitioning between a stop command where the acceleration is negative,
and a move command where the acceleration is positive.
Because of the jerk filter, the transition between negative and positive was not instantaneous and would take several hundreds of milliseconds.
@@ -87,10 +87,10 @@ but this can cause uncomfortably high initial accelerations.
As we just discussed, for vehicles with throttle control, an increased initial throttle value can reduce the start delay.
Since Autoware outputs an acceleration value, the conversion module
-[`raw_vehicle_cmd_converter`](https://autowarefoundation.github.io/autoware.universe/main/vehicle/raw_vehicle_cmd_converter/)
+[`raw_vehicle_cmd_converter`](https://autowarefoundation.github.io/autoware_universe/main/vehicle/raw_vehicle_cmd_converter/)
is used to map the acceleration value from Autoware to a throttle value to be sent to the vehicle.
Such mapping is usually calibrated automatically using the
-[`accel_brake_map_calibrator`](https://autowarefoundation.github.io/autoware.universe/main/vehicle/accel_brake_map_calibrator/accel_brake_map_calibrator/) module,
+[`accel_brake_map_calibrator`](https://autowarefoundation.github.io/autoware_universe/main/vehicle/accel_brake_map_calibrator/accel_brake_map_calibrator/) module,
but it may produce a low initial throttle which leads to high start delays.
In order to increase the initial throttle, there are two options:
@@ -98,9 +98,9 @@ increase the initial acceleration output by Autoware,
or modify the acceleration to throttle mapping.
The initial acceleration output by Autoware can be tuned in the
-[`motion_velocity_smoother`](https://autowarefoundation.github.io/autoware.universe/main/planning/motion_velocity_smoother/)
+[`motion_velocity_smoother`](https://autowarefoundation.github.io/autoware_universe/main/planning/motion_velocity_smoother/)
with parameters `engage_velocity` and `engage_acceleration`.
-However, the [`vehicle_cmd_gate`](https://autowarefoundation.github.io/autoware.universe/main/control/vehicle_cmd_gate/)
+However, the [`vehicle_cmd_gate`](https://autowarefoundation.github.io/autoware_universe/main/control/vehicle_cmd_gate/)
applies a filter on the control command to prevent too sudden changes in jerk and acceleration,
limiting the maximum allowed acceleration while the ego vehicle is stopped.
diff --git a/docs/how-to-guides/others/running-autoware-without-cuda.md b/docs/how-to-guides/others/running-autoware-without-cuda.md
index 294eb4626c8..ad20673afc6 100644
--- a/docs/how-to-guides/others/running-autoware-without-cuda.md
+++ b/docs/how-to-guides/others/running-autoware-without-cuda.md
@@ -13,7 +13,7 @@ Autoware Universe's object detection can be run using one of five possible confi
- `lidar-centerpoint` + `tensorrt_yolo`
- `euclidean_cluster`
-Of these five configurations, only the last one (`euclidean_cluster`) can be run without CUDA. For more details, refer to the [`euclidean_cluster` module's README file](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_euclidean_cluster).
+Of these five configurations, only the last one (`euclidean_cluster`) can be run without CUDA. For more details, refer to the [`euclidean_cluster` module's README file](https://github.com/autowarefoundation/autoware_universe/tree/main/perception/autoware_euclidean_cluster).
## Running traffic light detection without CUDA
@@ -22,6 +22,6 @@ For traffic light recognition (both detection and classification), there are two
- `traffic_light_ssd_fine_detector`
- `traffic_light_classifier`
-To run traffic light detection without CUDA, set [`enable_fine_detection` to `false` in the traffic light launch file](https://github.com/autowarefoundation/autoware.universe/blob/9445f3a7acd645d12a64507c3d3bfa57e74a3634/launch/tier4_perception_launch/launch/traffic_light_recognition/traffic_light.launch.xml#L3). Doing so disables the `traffic_light_ssd_fine_detector` such that traffic light detection is handled by the `map_based_traffic_light_detector` module instead.
+To run traffic light detection without CUDA, set [`enable_fine_detection` to `false` in the traffic light launch file](https://github.com/autowarefoundation/autoware_universe/blob/9445f3a7acd645d12a64507c3d3bfa57e74a3634/launch/tier4_perception_launch/launch/traffic_light_recognition/traffic_light.launch.xml#L3). Doing so disables the `traffic_light_ssd_fine_detector` such that traffic light detection is handled by the `map_based_traffic_light_detector` module instead.
-To run traffic light classification without CUDA, set [`use_gpu` to `false` in the traffic light classifier launch file](https://github.com/autowarefoundation/autoware.universe/blob/9445f3a7acd645d12a64507c3d3bfa57e74a3634/perception/traffic_light_classifier/launch/traffic_light_classifier.launch.xml#L7). Doing so will force the `traffic_light_classifier` to use a different classification algorithm that does not require CUDA or a GPU.
+To run traffic light classification without CUDA, set [`use_gpu` to `false` in the traffic light classifier launch file](https://github.com/autowarefoundation/autoware_universe/blob/9445f3a7acd645d12a64507c3d3bfa57e74a3634/perception/traffic_light_classifier/launch/traffic_light_classifier.launch.xml#L7). Doing so will force the `traffic_light_classifier` to use a different classification algorithm that does not require CUDA or a GPU.
diff --git a/docs/how-to-guides/others/using-divided-map.md b/docs/how-to-guides/others/using-divided-map.md
index 459f37464d8..849a053a6d3 100644
--- a/docs/how-to-guides/others/using-divided-map.md
+++ b/docs/how-to-guides/others/using-divided-map.md
@@ -26,5 +26,5 @@ For playing rosbag to simulate Autoware, please refer to the instruction in [the
## Related links
- For specific format definition of the divided map, please refer to [Map component design page](https://autowarefoundation.github.io/autoware-documentation/main/design/autoware-architecture/map/)
-- [The Readme of map_loader](https://github.com/autowarefoundation/autoware.universe/tree/main/map/autoware_map_loader) may be useful specific instructions for dividing maps
+- [The Readme of map_loader](https://github.com/autowarefoundation/autoware_universe/tree/main/map/autoware_map_loader) may be useful specific instructions for dividing maps
- When dividing your own pointcloud map, you may use [pointcloud_divider](https://github.com/autowarefoundation/autoware_tools/tree/main/map/autoware_pointcloud_divider), which can divide the map as well as generating the compatible metadata
diff --git a/docs/how-to-guides/training-machine-learning-models/training-models.md b/docs/how-to-guides/training-machine-learning-models/training-models.md
index 22b87787b64..8d5ca729f24 100644
--- a/docs/how-to-guides/training-machine-learning-models/training-models.md
+++ b/docs/how-to-guides/training-machine-learning-models/training-models.md
@@ -26,14 +26,14 @@ the readme file accompanying **"traffic_light_classifier"** package. These instr
the process of training the model using your own dataset. To facilitate your training, we have also provided
an example dataset containing three distinct classes (green, yellow, red), which you can leverage during the training process.
-Detailed instructions for training the traffic light classifier model can be found **[here](https://github.com/autowarefoundation/autoware.universe/blob/main/perception/autoware_traffic_light_classifier/README.md)**.
+Detailed instructions for training the traffic light classifier model can be found **[here](https://github.com/autowarefoundation/autoware_universe/blob/main/perception/autoware_traffic_light_classifier/README.md)**.
## Training CenterPoint 3D object detection model
The CenterPoint 3D object detection model within the Autoware has been trained using the **[autowarefoundation/mmdetection3d](https://github.com/autowarefoundation/mmdetection3d/blob/main/projects/AutowareCenterPoint/README.md)** repository.
To train custom CenterPoint models and convert them into ONNX format for deployment in Autoware, please refer to the instructions provided in the README file included with Autoware's
-**[lidar_centerpoint](https://autowarefoundation.github.io/autoware.universe/main/perception/autoware_lidar_centerpoint/)** package. These instructions will provide a step-by-step guide for training the CenterPoint model.
+**[lidar_centerpoint](https://autowarefoundation.github.io/autoware_universe/main/perception/autoware_lidar_centerpoint/)** package. These instructions will provide a step-by-step guide for training the CenterPoint model.
In order to assist you with your training process, we have also included an example dataset in the TIER IV dataset format.
diff --git a/docs/index.md b/docs/index.md
index bb1b77a3f88..06998e79502 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -44,5 +44,5 @@ Autoware is the world’s leading open-source project dedicated to autonomous dr
In addition to this page, there are several related documentations to further your knowledge and understanding of Autoware:
-- [Autoware Universe Documentation](https://autowarefoundation.github.io/autoware.universe/) contains technical documentations of each component/function such as localization, planning, etc.
+- [Autoware Universe Documentation](https://autowarefoundation.github.io/autoware_universe/) contains technical documentations of each component/function such as localization, planning, etc.
- [Autoware Tools Documentation](https://autowarefoundation.github.io/autoware_tools/main/) contains technical documentations of each tools for autonomous driving such as performance analysis, calibration, etc.
diff --git a/docs/reference-hw/index.md b/docs/reference-hw/index.md
index 46eecc3e8a9..d9e6579960c 100644
--- a/docs/reference-hw/index.md
+++ b/docs/reference-hw/index.md
@@ -1,6 +1,6 @@
# Reference HW Design
-This document is created to describe and give additional information of the sensors and systems supported by Autoware.Universe software.
+This document is created to describe and give additional information of the sensors and systems supported by Autoware Universe software.
All equipment listed in this document has available ROS 2 drivers and has been tested by one or more of the community members on field in autonomous vehicle and robotics applications.
diff --git a/docs/support/docs-guide.md b/docs/support/docs-guide.md
index 7b4341e8a8b..8b8aa9c7de6 100644
--- a/docs/support/docs-guide.md
+++ b/docs/support/docs-guide.md
@@ -4,5 +4,5 @@ This page explains several documentation sites that are useful for Autoware and
- [The Autoware Foundation](https://www.autoware.org/) is the official site of the Autoware Foundation. You can learn about the Autoware community here.
- [Autoware Documentation](https://autowarefoundation.github.io/autoware-documentation) (this site) is the central documentation site for Autoware maintained by the Autoware community. General software-related information of Autoware is aggregated here.
-- [Autoware Universe Documentation](https://autowarefoundation.github.io/autoware.universe) has READMEs and design documents of software components.
+- [Autoware Universe Documentation](https://autowarefoundation.github.io/autoware_universe) has READMEs and design documents of software components.
- [ROS Docs Guide](https://docs.ros.org/en/rolling/Docs-Guide.html) explains the ROS 1 and ROS 2 documentation infrastructure.
diff --git a/docs/support/troubleshooting/performance-troubleshooting.md b/docs/support/troubleshooting/performance-troubleshooting.md
index 5f4ca4b3864..2255d1f6138 100644
--- a/docs/support/troubleshooting/performance-troubleshooting.md
+++ b/docs/support/troubleshooting/performance-troubleshooting.md
@@ -52,7 +52,7 @@ Even if a build starts with these flags but same workspace gets compiled without
In addition, the nodes will run slow in general, especially the `pointcloud_preprocessor` nodes.
-Example issue: [issue2597](https://github.com/autowarefoundation/autoware.universe/issues/2597#issuecomment-1491789081)
+Example issue: [issue2597](https://github.com/autowarefoundation/autoware_universe/issues/2597#issuecomment-1491789081)
#### Solution
diff --git a/docs/tutorials/ad-hoc-simulation/digital-twin-simulation/carla-tutorial.md b/docs/tutorials/ad-hoc-simulation/digital-twin-simulation/carla-tutorial.md
index a82566d3fbb..c94bc868fcc 100644
--- a/docs/tutorials/ad-hoc-simulation/digital-twin-simulation/carla-tutorial.md
+++ b/docs/tutorials/ad-hoc-simulation/digital-twin-simulation/carla-tutorial.md
@@ -1,7 +1,7 @@
# CARLA simulator
[CARLA](https://carla.org) is a famous open-source simulator for the autonomous driving research.
-Now there is no official support to Autoware.universe, but some projects from communities support it.
+Now there is no official support to Autoware Universe, but some projects from communities support it.
The document is to list these projects for anyone who wants to run Autoware with Carla.
You can report issues to each project if there is any problem.
@@ -10,9 +10,9 @@ You can report issues to each project if there is any problem.
## autoware_carla_interface
Autoware ROS package to enables communication between Autoware and CARLA simulator for autonomous driving simulation.
-It is integrated in autoware.universe and actively maintained to stay compatible with the latest Autoware updates.
+It is integrated in autoware_universe and actively maintained to stay compatible with the latest Autoware updates.
-- Package Link and Tutorial: [autoware_carla_interface](https://github.com/autowarefoundation/autoware.universe/tree/main/simulator/autoware_carla_interface).
+- Package Link and Tutorial: [autoware_carla_interface](https://github.com/autowarefoundation/autoware_universe/tree/main/simulator/autoware_carla_interface).
### carla_autoware_bridge
| Ongoing | **[Autoware / TIER IV Challenge 2023](https://autoware.org/autoware-challenge-2023)** 
| Finished | **[Japan Automotive AI Challenge 2023 (Integration)](https://www.jsae.or.jp/jaaic/2023_summary.php)** 
| Ongoing | **[Japan Automotive AI Challenge 2023 (Simulation)](https://www.jsae.or.jp/jaaic/2023_simulation.php)**