Merge branch 'autowarefoundation:main' into main

docs/contributing/coding-guidelines/ros-nodes/parameters.md

@@ -149,7 +149,7 @@ Autoware has the following two types of parameter files for ROS packages:
 
 The schema file path is `INSERT_PATH_TO_PACKAGE/schema/` and the schema file name is `INSERT_NODE_NAME.schema.json`. To adapt the template to the ROS node, replace each `INSERT_...` and add all parameters `1..N`.
 
-See example: _Lidar Apollo Segmentation TVM Nodes_ [schema](https://github.com/autowarefoundation/autoware.universe/blob/main/perception/lidar_apollo_segmentation_tvm_nodes/schema/lidar_apollo_segmentation_tvm_nodes.schema.json)
+See example: _Image Projection Based Fusion - Pointpainting_ [schema](https://github.com/autowarefoundation/autoware.universe/blob/main/universe/perception/autoware_image_projection_based_fusion/schema/pointpainting.schema.json)
 
 ### Attributes
 

docs/contributing/testing-guidelines/integration-testing.md

@@ -70,16 +70,16 @@ The simplest scenario is a single node.
 In this case, the integration test is commonly referred to as a component test.
 
 To add a component test to an existing node,
-you can follow the example of the `lanelet2_map_loader` in the [`map_loader` package](https://github.com/autowarefoundation/autoware.universe/tree/main/map/map_loader)
+you can follow the example of the `lanelet2_map_loader` in the [`autoware_map_loader` package](https://github.com/autowarefoundation/autoware.universe/tree/main/map/autoware_map_loader)
 (added in [this PR](https://github.com/autowarefoundation/autoware.universe/pull/1056)).
 
-In [`package.xml`](https://github.com/autowarefoundation/autoware.universe/blob/main/map/map_loader/package.xml), add:
+In [`package.xml`](https://github.com/autowarefoundation/autoware.universe/blob/main/map/autoware_map_loader/package.xml), add:
 
 ```xml
 <test_depend>ros_testing</test_depend>
 ```
 
-In [`CMakeLists.txt`](https://github.com/autowarefoundation/autoware.universe/blob/main/map/map_loader/CMakeLists.txt),
+In [`CMakeLists.txt`](https://github.com/autowarefoundation/autoware.universe/blob/main/map/autoware_map_loader/CMakeLists.txt),
 add or modify the `BUILD_TESTING` section:
 
 ```cmake
@@ -106,7 +106,7 @@ To create a test,
 either read the [launch_testing quick-start example](https://github.com/ros2/launch/tree/master/launch_testing#quick-start-example),
 or follow the steps below.
 
-Taking [`test/lanelet2_map_loader_launch.test.py`](https://github.com/autowarefoundation/autoware.universe/blob/main/map/map_loader/test/lanelet2_map_loader_launch.test.py) as an example,
+Taking [`test/lanelet2_map_loader_launch.test.py`](https://github.com/autowarefoundation/autoware.universe/blob/main/map/autoware_map_loader/test/lanelet2_map_loader_launch.test.py) as an example,
 first dependencies are imported:
 
 ```python
@@ -122,20 +122,20 @@ import pytest
 ```
 
 Then a launch description is created to launch the node under test.
-Note that the [`test_map.osm`](https://github.com/autowarefoundation/autoware.universe/blob/main/map/map_loader/test/data/test_map.osm) file path is found and passed to the node,
+Note that the [`test_map.osm`](https://github.com/autowarefoundation/autoware.universe/blob/main/map/autoware_map_loader/test/data/test_map.osm) file path is found and passed to the node,
 something that cannot be done with the [smoke testing API](#smoke-tests):
 
 ```python
 @pytest.mark.launch_test
 def generate_test_description():
 
     lanelet2_map_path = os.path.join(
-        get_package_share_directory("map_loader"), "test/data/test_map.osm"
+        get_package_share_directory("autoware_map_loader"), "test/data/test_map.osm"
     )
 
     lanelet2_map_loader = Node(
-        package="map_loader",
-        executable="lanelet2_map_loader",
+        package="autoware_map_loader",
+        executable="autoware_lanelet2_map_loader",
         parameters=[{"lanelet2_map_path": lanelet2_map_path}],
     )
 
@@ -177,28 +177,28 @@ class TestProcessOutput(unittest.TestCase):
 Continuing the example from above, first build your package:
 
 ```console
-colcon build --packages-up-to map_loader
+colcon build --packages-up-to autoware_map_loader
 source install/setup.bash
 ```
 
 Then either execute the component test manually:
 
 ```console
-ros2 test src/universe/autoware.universe/map/map_loader/test/lanelet2_map_loader_launch.test.py
+ros2 test src/universe/autoware.universe/map/autoware_map_loader/test/lanelet2_map_loader_launch.test.py
 ```
 
 Or as part of testing the entire package:
 
 ```console
-colcon test --packages-select map_loader
+colcon test --packages-select autoware_map_loader
 ```
 
 Verify that the test is executed; e.g.
 
 ```console
 $ colcon test-result --all --verbose
 ...
-build/map_loader/test_results/map_loader/test_lanelet2_map_loader_launch.test.py.xunit.xml: 1 test, 0 errors, 0 failures, 0 skipped
+build/autoware_map_loader/test_results/autoware_map_loader/test_lanelet2_map_loader_launch.test.py.xunit.xml: 1 test, 0 errors, 0 failures, 0 skipped
 ```
 
 ### Next steps

docs/design/autoware-architecture/map/index.md

@@ -69,7 +69,7 @@ The point cloud map must be supplied as a file with the following requirements:
 - Its resolution should be at least 0.2 m to yield reliable localization results.
 - It can be in either local or global coordinates, but must be in global coordinates (georeferenced) to use GNSS data for localization.
 
-For more details on divided map format, please refer to [the readme of `map_loader` in Autoware Universe](https://github.com/autowarefoundation/autoware.universe/blob/main/map/map_loader/README.md).
+For more details on divided map format, please refer to [the readme of `map_loader` in Autoware Universe](https://github.com/autowarefoundation/autoware.universe/blob/main/map/autoware_map_loader/README.md).
 
 !!! note
 

docs/design/autoware-architecture/perception/reference-implementations/radar-based-3d-detector/faraway-object-detection.md

@@ -10,28 +10,28 @@ This diagram describes the pipeline for radar faraway dynamic object detection.
 
 ### Crossing filter
 
-- [radar_crossing_objects_noise_filter](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/radar_crossing_objects_noise_filter)
+- [radar_crossing_objects_noise_filter](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_radar_crossing_objects_noise_filter)
 
 This package can filter the noise objects crossing to the ego vehicle, which are most likely ghost objects.
 
 ### Velocity filter
 
-- [object_velocity_splitter](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/object_velocity_splitter)
+- [object_velocity_splitter](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_object_velocity_splitter)
 
 Static objects include many noise like the objects reflected from ground.
 In many cases for radars, dynamic objects can be detected stably.
 To filter out static objects, `object_velocity_splitter` can be used.
 
 ### Range filter
 
-- [object_range_splitter](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/object_range_splitter)
+- [object_range_splitter](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_object_range_splitter)
 
 For some radars, ghost objects sometimes occur for near objects.
 To filter these objects, `object_range_splitter` can be used.
 
 ### Vector map filter
 
-- [object-lanelet-filter](https://github.com/autowarefoundation/autoware.universe/blob/main/perception/detected_object_validation/object-lanelet-filter.md)
+- [object-lanelet-filter](https://github.com/autowarefoundation/autoware.universe/blob/main/perception/autoware_detected_object_validation/object-lanelet-filter.md)
 
 In most cases, vehicles drive in drivable are.
 To filter objects that are out of drivable area, `object-lanelet-filter` can be used.
@@ -41,12 +41,12 @@ Note that if you use `object-lanelet-filter` for radar faraway detection, you ne
 
 ### Radar object clustering
 
-- [radar_object_clustering](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/radar_object_clustering)
+- [radar_object_clustering](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_radar_object_clustering)
 
 This package can combine multiple radar detections from one object into one and adjust class and size.
 It can suppress splitting objects in tracking module.
 
-![radar_object_clustering](https://raw.githubusercontent.com/autowarefoundation/autoware.universe/main/perception/radar_object_clustering/docs/radar_clustering.drawio.svg)
+![radar_object_clustering](https://raw.githubusercontent.com/autowarefoundation/autoware.universe/main/perception/autoware_radar_object_clustering/docs/radar_clustering.drawio.svg)
 
 ## Note
 

docs/design/autoware-architecture/perception/reference-implementations/radar-based-3d-detector/radar-based-3d-detector.md

@@ -58,7 +58,7 @@ In detail, please see [this document](faraway-object-detection.md)
 
 ### Radar fusion to LiDAR-based 3D object detection
 
-- [radar_fusion_to_detected_object](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/radar_fusion_to_detected_object)
+- [radar_fusion_to_detected_object](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_radar_fusion_to_detected_object)
 
 This package contains a sensor fusion module for radar-detected objects and 3D detected objects. The fusion node can:
 

docs/design/autoware-architecture/sensing/data-types/radar-data/radar-objects-data.md

@@ -43,20 +43,20 @@ Radar can detect x-axis velocity as doppler velocity, but cannot detect y-axis v
 
 ### Message converter
 
-- [radar_tracks_msgs_converter](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/radar_tracks_msgs_converter)
+- [radar_tracks_msgs_converter](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_radar_tracks_msgs_converter)
 
 This package converts from `radar_msgs/msg/RadarTracks` into `autoware_auto_perception_msgs/msg/DetectedObject` with ego vehicle motion compensation and coordinate transform.
 
 ### Object merger
 
-- [object_merger](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/object_merger)
+- [object_merger](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_object_merger)
 
 This package can merge 2 topics of `autoware_auto_perception_msgs/msg/DetectedObject`.
 
-- [simple_object_merger](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/simple_object_merger)
+- [simple_object_merger](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_simple_object_merger)
 
 This package can merge simply multiple topics of `autoware_auto_perception_msgs/msg/DetectedObject`.
-Different from [object_merger](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/object_merger), this package doesn't use association algorithm and can merge with low calculation cost.
+Different from [object_merger](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_object_merger), this package doesn't use association algorithm and can merge with low calculation cost.
 
 - [topic_tools](https://github.com/ros-tooling/topic_tools)
 

docs/design/autoware-architecture/sensing/data-types/radar-data/radar-pointcloud-data.md

@@ -64,7 +64,7 @@ For convenient use of radar pointcloud within existing LiDAR packages, we sugges
 For considered use cases,
 
 - Use [pointcloud_preprocessor](https://github.com/autowarefoundation/autoware.universe/tree/main/sensing/pointcloud_preprocessor) for radar scan.
-- Apply obstacle segmentation like [ground segmentation](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/ground_segmentation) to radar points for LiDAR-less (camera + radar) systems.
+- Apply obstacle segmentation like [ground segmentation](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_ground_segmentation) to radar points for LiDAR-less (camera + radar) systems.
 
 ## Appendix
 

docs/design/autoware-architecture/sensing/data-types/radar-data/reference-implementations/data-message.md

@@ -78,7 +78,7 @@ uint16 BICYCLE = 32006;
 uint16 PEDESTRIAN = 32007;
 ```
 
-For detail implementation, please see [radar_tracks_msgs_converter](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/radar_tracks_msgs_converter).
+For detail implementation, please see [radar_tracks_msgs_converter](https://github.com/autowarefoundation/autoware.universe/tree/main/perception/autoware_radar_tracks_msgs_converter).
 
 ## Note
 

docs/design/autoware-interfaces/components/control.md

@@ -43,13 +43,13 @@ TODO This represents the reported physical efforts exerted by the vehicle actuat
 
 A motion signal to drive the vehicle, achieved by the low-level controller in the vehicle layer. Used by the Vehicle Interface.
 
-- [autoware_auto_control_msgs/AckermannControlCommand](https://gitlab.com/autowarefoundation/autoware.auto/autoware_auto_msgs/-/blob/master/autoware_auto_control_msgs/msg/AckermannControlCommand.idl)
+- [autoware_control_msgs/Control](https://github.com/autowarefoundation/autoware_msgs/blob/main/autoware_control_msgs/msg/Control.msg)
   - builtin_interfaces::msg::Time stamp
-  - [autoware_auto_control_msgs/AckermannLateralCommand](https://gitlab.com/autowarefoundation/autoware.auto/autoware_auto_msgs/-/blob/master/autoware_auto_control_msgs/msg/AckermannLateralCommand.idl) lateral
+  - [autoware_control_msgs/Lateral](https://github.com/autowarefoundation/autoware_msgs/blob/main/autoware_control_msgs/msg/Lateral.msg) lateral
     - builtin_interfaces::msg::Time stamp
     - float steering_tire_angle
     - float steering_tire_rotation_rate
-  - [autoware_auto_control_msgs/LongitudinalCommand](https://gitlab.com/autowarefoundation/autoware.auto/autoware_auto_msgs/-/blob/master/autoware_auto_control_msgs/msg/LongitudinalCommand.idl) longitudinal
+  - [autoware_control_msgs/Longitudinal](https://github.com/autowarefoundation/autoware_msgs/blob/main/autoware_control_msgs/msg/Lateral.msg) longitudinal
     - builtin_interfaces::msg::Time stamp
     - builtin_interfaces::msg::Duration duration
     - builtin_interfaces::msg::Duration time_step

docs/design/autoware-interfaces/components/localization.md

@@ -84,13 +84,13 @@ Current orientation, angular velocity and linear acceleration of ego, calculated
 
 Current velocity of the ego vehicle, published by the vehicle interface.
 
-- autoware_auto_vehicle_msgs/msg/VelocityReport
+- autoware_vehicle_msgs/msg/VelocityReport
   - std_msgs/msg/Header header;
   - float longitudinal_velocity;
   - float lateral_velocity;
   - float heading_rate;
 
-Before the velocity input localization interface, module `vehicle_velocity_converter` converts message type `autoware_auto_vehicle_msgs/msg/VelocityReport` to `geometry_msgs/msg/TwistWithCovarianceStamped`.
+Before the velocity input localization interface, module `vehicle_velocity_converter` converts message type `autoware_vehicle_msgs/msg/VelocityReport` to `geometry_msgs/msg/TwistWithCovarianceStamped`.
 
 ## Outputs
 

docs/design/autoware-interfaces/components/map.md

@@ -26,9 +26,9 @@ It loads point cloud files and publishes the maps to the other Autoware nodes in
 
 ### Lanelet2 map
 
-It loads a Lanelet2 file and publishes the map data as `autoware_auto_mapping_msgs/msg/HADMapBin` message. The lan/lon coordinates are projected onto the MGRS coordinates.
+It loads a Lanelet2 file and publishes the map data as `autoware_map_msgs/msg/LaneletMapBin` message. The lan/lon coordinates are projected onto the MGRS coordinates.
 
-- autoware_auto_mapping_msgs/msg/HADMapBin
+- autoware_map_msgs/msg/LaneletMapBin
   - std_msgs/Header header
   - string version_map_format
   - string version_map
@@ -37,6 +37,6 @@ It loads a Lanelet2 file and publishes the map data as `autoware_auto_mapping_ms
 
 ### Lanelet2 map visualization
 
-Visualize `autoware_auto_mapping_msgs/HADMapBin` messages in `Rviz`.
+Visualize `autoware_map_msgs/msg/LaneletMapBin` messages in `Rviz`.
 
 - visualization_msgs/msg/MarkerArray

docs/design/autoware-interfaces/components/perception-interface.md

@@ -14,13 +14,13 @@ graph TD
     <font size=1>sensor_msgs/PointCloud2</font size>"):::cls_sen
 
     msg_lanenet("<font size=2><b>Lanelet2 Map</b></font size>
-    <font size=1>autoware_auto_mapping_msgs/HADMapBin</font size>"):::cls_loc
+    <font size=1>autoware_map_msgs/LaneletMapBin</font size>"):::cls_loc
 
     msg_vks("<font size=2><b>Vehicle Kinematic State</b></font size>
     <font size=1>nav_msgs/Odometry</font size>"):::cls_loc
 
     msg_obj("<font size=2><b>3D Object Predictions </b></font size>
-    <font size=1>autoware_auto_perception_msgs/PredictedObjects</font size>"):::cls_per
+    <font size=1>autoware_perception_msgs/PredictedObjects</font size>"):::cls_per
 
     msg_tl("<font size=2><b>Traffic Light Response </b></font size>
     <font size=1>autoware_perception_msgs/TrafficSignalArray</font size>"):::cls_per
@@ -72,23 +72,23 @@ map of the environment. See [outputs of Map](https://autowarefoundation.github.i
 
 3D Objects detected, tracked and predicted by sensor fusing.
 
-- [autoware_auto_perception_msgs/msg/PredictedObjects](https://gitlab.com/autowarefoundation/autoware.auto/autoware_auto_msgs/-/blob/master/autoware_auto_perception_msgs/msg/PredictedObjects.idl)
+- [autoware_perception_msgs/msg/PredictedObjects](https://github.com/autowarefoundation/autoware_msgs/blob/main/autoware_perception_msgs/msg/PredictedObjects.msg)
   - [std_msgs/Header](https://docs.ros.org/en/noetic/api/std_msgs/html/msg/Header.html) header
-  - sequence<[autoware_auto_perception_msgs::msg::PredictedObject](https://gitlab.com/autowarefoundation/autoware.auto/autoware_auto_msgs/-/blob/master/autoware_auto_perception_msgs/msg/PredictedObject.idl)> objects
+  - sequence<[autoware_perception_msgs::msg::PredictedObject](https://github.com/autowarefoundation/autoware_msgs/blob/main/autoware_perception_msgs/msg/PredictedObject.msg)> objects
     - unique_identifier_msgs::msg::UUID uuid
     - float existence_probability
-    - sequence<[autoware_auto_perception_msgs::msg::ObjectClassification](https://gitlab.com/autowarefoundation/autoware.auto/autoware_auto_msgs/-/blob/master/autoware_auto_perception_msgs/msg/ObjectClassification.idl)> classification
+    - sequence<[autoware_perception_msgs::msg::ObjectClassification](https://github.com/autowarefoundation/autoware_msgs/blob/main/autoware_perception_msgs/msg/ObjectClassification.msg)> classification
       - uint8 classification
       - float probability
-    - [autoware_auto_perception_msgs::msg::PredictedObjectKinematics](https://gitlab.com/autowarefoundation/autoware.auto/autoware_auto_msgs/-/blob/master/autoware_auto_perception_msgs/msg/PredictedObjectKinematics.idl) kinematics
+    - [autoware_perception_msgs::msg::PredictedObjectKinematics](https://github.com/autowarefoundation/autoware_msgs/blob/main/autoware_perception_msgs/msg/PredictedObjectKinematics.msg) kinematics
       - [geometry_msgs::msg::PoseWithCovariance](https://docs.ros.org/en/noetic/api/geometry_msgs/html/msg/PoseWithCovariance.html) initial_pose
       - [geometry_msgs::msg::TwistWithCovariance](https://docs.ros.org/en/noetic/api/geometry_msgs/html/msg/TwistWithCovariance.html)
       - [geometry_msgs::msg::AccelWithCovariance](https://docs.ros.org/en/noetic/api/geometry_msgs/html/msg/AccelWithCovariance.html) initial_acceleration
-      - sequence<[autoware_auto_perception_msgs::msg::PredictedPath](https://gitlab.com/autowarefoundation/autoware.auto/autoware_auto_msgs/-/blob/master/autoware_auto_perception_msgs/msg/PredictedPath.idl), 10> predicted_paths
-        - sequence<[geometry_msgs::msg::Pose](https://docs.ros.org/en/lunar/api/geometry_msgs/html/msg/Pose.html), 100> path
-        - builtin_interfaces::msg::Duration time_step
-        - float confidence
-    - sequence<[autoware_auto_perception_msgs::msg::Shape](https://gitlab.com/autowarefoundation/autoware.auto/autoware_auto_msgs/-/blob/master/autoware_auto_perception_msgs/msg/Shape.idl), 5> shape
+    - sequence<[autoware_perception_msgs::msg::PredictedPath](https://github.com/autowarefoundation/autoware_msgs/blob/main/autoware_perception_msgs/msg/PredictedPath.msg), 10> predicted_paths
+      - sequence<[geometry_msgs::msg::Pose](https://docs.ros.org/en/lunar/api/geometry_msgs/html/msg/Pose.html), 100> path
+      - builtin_interfaces::msg::Duration time_step
+      - float confidence
+    - sequence<[autoware_perception_msgs::msg::Shape](https://github.com/autowarefoundation/autoware_msgs/blob/main/autoware_perception_msgs/msg/Shape.msg), 5> shape
       - [geometry_msgs::msg::Polygon](https://docs.ros.org/en/noetic/api/geometry_msgs/html/msg/Polygon.html) polygon
       - float height