[pull] main from autowarefoundation:main

.github/workflows/build-and-test-differential.yaml

@@ -2,21 +2,10 @@ name: build-and-test-differential
 
 on:
   pull_request:
-    types:
-      - opened
-      - synchronize
-      - labeled
 
 jobs:
-  prevent-no-label-execution:
-    uses: autowarefoundation/autoware-github-actions/.github/workflows/prevent-no-label-execution.yaml@v1
-    with:
-      label: tag:run-build-and-test-differential
-
   build-and-test-differential:
-    needs: prevent-no-label-execution
-    if: ${{ needs.prevent-no-label-execution.outputs.run == 'true' }}
-    runs-on: [self-hosted, linux, X64]
+    runs-on: ubuntu-latest
     container: ${{ matrix.container }}${{ matrix.container-suffix }}
     strategy:
       fail-fast: false
@@ -36,6 +25,9 @@ jobs:
         with:
           fetch-depth: 0
 
+      - name: Check disk space before build
+        run: df -h
+
       - name: Remove exec_depend
         uses: autowarefoundation/autoware-github-actions/remove-exec-depend@v1
 
@@ -69,8 +61,11 @@ jobs:
           verbose: true
           flags: differential
 
+      - name: Check disk space after build
+        run: df -h
+
   clang-tidy-differential:
-    runs-on: [self-hosted, linux, X64]
+    runs-on: ubuntu-latest
     container: ghcr.io/autowarefoundation/autoware-universe:humble-latest-cuda
     needs: build-and-test-differential
     steps:

common/tensorrt_common/include/tensorrt_common/logger.hpp

@@ -493,7 +493,7 @@ namespace
 //!
 inline LogStreamConsumer LOG_VERBOSE(const Logger & logger)
 {
-  return LogStreamConsumer(logger.getReportableSeverity(), Severity::kVERBOSE) << "[TRT] ";
+  return LogStreamConsumer(logger.getReportableSeverity(), Severity::kVERBOSE);
 }
 
 //!
@@ -505,7 +505,7 @@ inline LogStreamConsumer LOG_VERBOSE(const Logger & logger)
 //!
 inline LogStreamConsumer LOG_INFO(const Logger & logger)
 {
-  return LogStreamConsumer(logger.getReportableSeverity(), Severity::kINFO) << "[TRT] ";
+  return LogStreamConsumer(logger.getReportableSeverity(), Severity::kINFO);
 }
 
 //!
@@ -517,7 +517,7 @@ inline LogStreamConsumer LOG_INFO(const Logger & logger)
 //!
 inline LogStreamConsumer LOG_WARN(const Logger & logger)
 {
-  return LogStreamConsumer(logger.getReportableSeverity(), Severity::kWARNING) << "[TRT] ";
+  return LogStreamConsumer(logger.getReportableSeverity(), Severity::kWARNING);
 }
 
 //!
@@ -529,7 +529,7 @@ inline LogStreamConsumer LOG_WARN(const Logger & logger)
 //!
 inline LogStreamConsumer LOG_ERROR(const Logger & logger)
 {
-  return LogStreamConsumer(logger.getReportableSeverity(), Severity::kERROR) << "[TRT] ";
+  return LogStreamConsumer(logger.getReportableSeverity(), Severity::kERROR);
 }
 
 //!
@@ -543,7 +543,7 @@ inline LogStreamConsumer LOG_ERROR(const Logger & logger)
 //!
 inline LogStreamConsumer LOG_FATAL(const Logger & logger)
 {
-  return LogStreamConsumer(logger.getReportableSeverity(), Severity::kINTERNAL_ERROR) << "[TRT] ";
+  return LogStreamConsumer(logger.getReportableSeverity(), Severity::kINTERNAL_ERROR);
 }
 
 }  // anonymous namespace

launch/tier4_localization_launch/launch/pose_twist_fusion_filter/pose_twist_fusion_filter.launch.xml

@@ -27,10 +27,10 @@
 
   <group>
     <include file="$(find-pkg-share twist2accel)/launch/twist2accel.launch.xml">
-      <arg name="use_odom" value="true"/>
       <arg name="in_odom" value="/localization/kinematic_state"/>
       <arg name="in_twist" value="/localization/twist_estimator/twist_with_covariance"/>
       <arg name="out_accel" value="/localization/acceleration"/>
+      <arg name="param_file" value="$(var twist2accel_param_path)"/>
     </include>
   </group>
 

launch/tier4_map_launch/launch/map.launch.xml

@@ -8,6 +8,7 @@
   <!-- Parameter files -->
   <arg name="pointcloud_map_loader_param_path"/>
   <arg name="lanelet2_map_loader_param_path"/>
+  <arg name="map_projection_loader_param_path"/>
 
   <!-- whether use intra-process -->
   <arg name="use_intra_process" default="false"/>
@@ -59,6 +60,7 @@
     </node>
 
     <include file="$(find-pkg-share map_projection_loader)/launch/map_projection_loader.launch.xml">
+      <arg name="param_path" value="$(var map_projection_loader_param_path)"/>
       <arg name="map_projector_info_path" value="$(var map_projector_info_path)"/>
       <arg name="lanelet2_map_path" value="$(var lanelet2_map_path)"/>
     </include>

launch/tier4_map_launch/package.xml

@@ -8,6 +8,11 @@
   <maintainer email="ryu.yamamoto@tier4.jp">Ryu Yamamoto</maintainer>
   <maintainer email="koji.minoda@tier4.jp">Koji Minoda</maintainer>
   <maintainer email="kento.yabuuchi.2@tier4.jp">Kento Yabuuchi</maintainer>
+  <maintainer email="yamato.ando@tier4.jp">Yamato Ando</maintainer>
+  <maintainer email="anh.nguyen.2@tier4.jp">NGUYEN Viet Anh</maintainer>
+  <maintainer email="taiki.yamada@tier4.jp">Taiki Yamada</maintainer>
+  <maintainer email="shintaro.sakoda@tier4.jp">Shintaro Sakoda</maintainer>
+  <maintainer email="masahiro.sakamoto@tier4.jp">Masahiro Sakamoto</maintainer>
   <license>Apache License 2.0</license>
 
   <buildtool_depend>ament_cmake_auto</buildtool_depend>

launch/tier4_perception_launch/launch/object_recognition/detection/detector/camera_lidar_detector.launch.xml

@@ -85,6 +85,9 @@
       <arg name="model_path" value="$(var pointpainting_model_path)"/>
       <arg name="model_param_path" value="$(var lidar_model_param_path)/$(var lidar_detection_model).param.yaml"/>
       <arg name="class_remapper_param_path" value="$(var lidar_model_param_path)/detection_class_remapper.param.yaml"/>
+
+      <arg name="use_pointcloud_container" value="$(var use_pointcloud_container)"/>
+      <arg name="pointcloud_container_name" value="$(var pointcloud_container_name)"/>
     </include>
   </group>
 

launch/tier4_perception_launch/launch/object_recognition/detection/detector/lidar_dnn_detector.launch.xml

@@ -22,6 +22,9 @@
         <arg name="model_path" value="$(var centerpoint_model_path)"/>
         <arg name="model_param_path" value="$(var lidar_model_param_path)/$(var centerpoint_model_name).param.yaml"/>
         <arg name="class_remapper_param_path" value="$(var lidar_model_param_path)/detection_class_remapper.param.yaml"/>
+
+        <arg name="use_pointcloud_container" value="$(var use_pointcloud_container)"/>
+        <arg name="pointcloud_container_name" value="$(var pointcloud_container_name)"/>
       </include>
     </group>
   </group>

launch/tier4_perception_launch/launch/object_recognition/detection/detector/lidar_rule_detector.launch.xml

@@ -26,6 +26,9 @@
         <arg name="input_pointcloud" value="/perception/object_recognition/detection/pointcloud_map_filtered/pointcloud"/>
         <arg name="output_clusters" value="clusters"/>
         <arg name="use_low_height_cropbox" value="$(var use_low_height_cropbox)"/>
+
+        <arg name="use_pointcloud_container" value="$(var use_pointcloud_container)"/>
+        <arg name="pointcloud_container_name" value="$(var pointcloud_container_name)"/>
       </include>
     </group>
 

localization/ndt_scan_matcher/config/ndt_scan_matcher.param.yaml

@@ -1,102 +1,114 @@
 /**:
   ros__parameters:
-    # Vehicle reference frame
-    base_frame: "base_link"
+    frame:
+      # Vehicle reference frame
+      base_frame: "base_link"
 
-    # NDT reference frame
-    ndt_base_frame: "ndt_base_link"
+      # NDT reference frame
+      ndt_base_frame: "ndt_base_link"
 
-    # map frame
-    map_frame: "map"
+      # Map frame
+      map_frame: "map"
 
-    # Subscriber queue size
-    input_sensor_points_queue_size: 1
 
-    # The maximum difference between two consecutive
-    # transformations in order to consider convergence
-    trans_epsilon: 0.01
+    ndt:
+      # The maximum difference between two consecutive
+      # transformations in order to consider convergence
+      trans_epsilon: 0.01
 
-    # The newton line search maximum step length
-    step_size: 0.1
+      # The newton line search maximum step length
+      step_size: 0.1
 
-    # The ND voxel grid resolution
-    resolution: 2.0
+      # The ND voxel grid resolution
+      resolution: 2.0
 
-    # The number of iterations required to calculate alignment
-    max_iterations: 30
+      # The number of iterations required to calculate alignment
+      max_iterations: 30
 
-    # Converged param type
-    # 0=TRANSFORM_PROBABILITY, 1=NEAREST_VOXEL_TRANSFORMATION_LIKELIHOOD
-    converged_param_type: 1
+      # Number of threads used for parallel computing
+      num_threads: 4
 
-    # If converged_param_type is 0
-    # Threshold for deciding whether to trust the estimation result
-    converged_param_transform_probability: 3.0
+      regularization:
+        enable: false
 
-    # If converged_param_type is 1
-    # Threshold for deciding whether to trust the estimation result
-    converged_param_nearest_voxel_transformation_likelihood: 2.3
+        # Regularization scale factor
+        scale_factor: 0.01
 
-    # The number of particles to estimate initial pose
-    initial_estimate_particles_num: 200
 
-    # The number of initial random trials in the TPE (Tree-Structured Parzen Estimator).
-    # This value should be equal to or less than 'initial_estimate_particles_num' and more than 0.
-    # If it is equal to 'initial_estimate_particles_num', the search will be the same as a full random search.
-    n_startup_trials: 20
+    initial_pose_estimation:
+      # The number of particles to estimate initial pose
+      particles_num: 200
 
-    # Tolerance of timestamp difference between current time and sensor pointcloud. [sec]
-    lidar_topic_timeout_sec: 1.0
+      # The number of initial random trials in the TPE (Tree-Structured Parzen Estimator).
+      # This value should be equal to or less than 'initial_estimate_particles_num' and more than 0.
+      # If it is equal to 'initial_estimate_particles_num', the search will be the same as a full random search.
+      n_startup_trials: 20
 
-    # Tolerance of timestamp difference between initial_pose and sensor pointcloud. [sec]
-    initial_pose_timeout_sec: 1.0
 
-    # Tolerance of distance difference between two initial poses used for linear interpolation. [m]
-    initial_pose_distance_tolerance_m: 10.0
+    validation:
+      # Tolerance of timestamp difference between current time and sensor pointcloud. [sec]
+      lidar_topic_timeout_sec: 1.0
 
-    # The execution time which means probably NDT cannot matches scans properly. [ms]
-    critical_upper_bound_exe_time_ms: 100.0
+      # Tolerance of timestamp difference between initial_pose and sensor pointcloud. [sec]
+      initial_pose_timeout_sec: 1.0
 
-    # Number of threads used for parallel computing
-    num_threads: 4
+      # Tolerance of distance difference between two initial poses used for linear interpolation. [m]
+      initial_pose_distance_tolerance_m: 10.0
 
-    # The covariance of output pose
-    # Note that this covariance matrix is empirically derived
-    output_pose_covariance:
-      [
-        0.0225, 0.0,   0.0,   0.0,      0.0,      0.0,
-        0.0,   0.0225, 0.0,   0.0,      0.0,      0.0,
-        0.0,   0.0,   0.0225, 0.0,      0.0,      0.0,
-        0.0,   0.0,   0.0,   0.000625, 0.0,      0.0,
-        0.0,   0.0,   0.0,   0.0,      0.000625, 0.0,
-        0.0,   0.0,   0.0,   0.0,      0.0,      0.000625,
-      ]
+      # The execution time which means probably NDT cannot matches scans properly. [ms]
+      critical_upper_bound_exe_time_ms: 100.0
 
-    # 2D Real-time covariance estimation with multiple searches (output_pose_covariance is the minimum value)
-    use_covariance_estimation: false
 
-    # Offset arrangement in covariance estimation [m]
-    # initial_pose_offset_model_x & initial_pose_offset_model_y must have the same number of elements.
-    initial_pose_offset_model_x: [0.0, 0.0, 0.5, -0.5, 1.0, -1.0]
-    initial_pose_offset_model_y: [0.5, -0.5, 0.0, 0.0, 0.0, 0.0]
+    score_estimation:
+      # Converged param type
+      # 0=TRANSFORM_PROBABILITY, 1=NEAREST_VOXEL_TRANSFORMATION_LIKELIHOOD
+      converged_param_type: 1
 
-    # Regularization switch
-    regularization_enabled: false
+      # If converged_param_type is 0
+      # Threshold for deciding whether to trust the estimation result
+      converged_param_transform_probability: 3.0
 
-    # Regularization scale factor
-    regularization_scale_factor: 0.01
+      # If converged_param_type is 1
+      # Threshold for deciding whether to trust the estimation result
+      converged_param_nearest_voxel_transformation_likelihood: 2.3
 
-    # Dynamic map loading distance
-    dynamic_map_loading_update_distance: 20.0
+      # Scan matching score based on no ground LiDAR scan
+      no_ground_points:
+        enable: false
 
-    # Dynamic map loading loading radius
-    dynamic_map_loading_map_radius: 150.0
+        # If lidar_point.z - base_link.z <= this threshold , the point will be removed
+        z_margin_for_ground_removal: 0.8
 
-    # Radius of input LiDAR range (used for diagnostics of dynamic map loading)
-    lidar_radius: 100.0
 
-    # A flag for using scan matching score based on no ground LiDAR scan
-    estimate_scores_by_no_ground_points: false
+    covariance:
+      # The covariance of output pose
+      # Note that this covariance matrix is empirically derived
+      output_pose_covariance:
+        [
+          0.0225, 0.0,   0.0,   0.0,      0.0,      0.0,
+          0.0,   0.0225, 0.0,   0.0,      0.0,      0.0,
+          0.0,   0.0,   0.0225, 0.0,      0.0,      0.0,
+          0.0,   0.0,   0.0,   0.000625, 0.0,      0.0,
+          0.0,   0.0,   0.0,   0.0,      0.000625, 0.0,
+          0.0,   0.0,   0.0,   0.0,      0.0,      0.000625,
+        ]
 
-    # If lidar_point.z - base_link.z <= this threshold , the point will be removed
-    z_margin_for_ground_removal: 0.8
+      # 2D Real-time covariance estimation with multiple searches (output_pose_covariance is the minimum value)
+      covariance_estimation:
+        enable: false
+
+        # Offset arrangement in covariance estimation [m]
+        # initial_pose_offset_model_x & initial_pose_offset_model_y must have the same number of elements.
+        initial_pose_offset_model_x: [0.0, 0.0, 0.5, -0.5, 1.0, -1.0]
+        initial_pose_offset_model_y: [0.5, -0.5, 0.0, 0.0, 0.0, 0.0]
+
+
+    dynamic_map_loading:
+      # Dynamic map loading distance
+      update_distance: 20.0
+
+      # Dynamic map loading loading radius
+      map_radius: 150.0
+
+      # Radius of input LiDAR range (used for diagnostics of dynamic map loading)
+      lidar_radius: 100.0