Merge pull request #304 from tier4/sync-awf-upstream

chore: sync awf/autoware_launch

Author: tier4-autoware-public-bot[bot]

autoware_launch/config/localization/ekf_localizer.param.yaml

@@ -1,37 +1,46 @@
 /**:
   ros__parameters:
-    show_debug_info: false
-    enable_yaw_bias_estimation: true
-    predict_frequency: 50.0
-    tf_rate: 50.0
-    publish_tf: true
-    extend_state_step: 50
+    node:
+      show_debug_info: false
+      enable_yaw_bias_estimation: true
+      predict_frequency: 50.0
+      tf_rate: 50.0
+      publish_tf: true
+      extend_state_step: 50
 
-    # for Pose measurement
-    pose_additional_delay: 0.0
-    pose_measure_uncertainty_time: 0.01
-    pose_smoothing_steps: 5
-    pose_gate_dist: 10000.0
+    pose_measurement:
+      # for Pose measurement
+      pose_additional_delay: 0.0
+      pose_measure_uncertainty_time: 0.01
+      pose_smoothing_steps: 5
+      pose_gate_dist: 10000.0
 
-    # for twist measurement
-    twist_additional_delay: 0.0
-    twist_smoothing_steps: 2
-    twist_gate_dist: 10000.0
+    twist_measurement:
+      # for twist measurement
+      twist_additional_delay: 0.0
+      twist_smoothing_steps: 2
+      twist_gate_dist: 10000.0
 
-    # for process model
-    proc_stddev_yaw_c: 0.005
-    proc_stddev_vx_c: 10.0
-    proc_stddev_wz_c: 5.0
+    process_noise:
+      # for process model
+      proc_stddev_yaw_c: 0.005
+      proc_stddev_vx_c: 10.0
+      proc_stddev_wz_c: 5.0
 
-    #Simple1DFilter parameters
-    z_filter_proc_dev: 1.0
-    roll_filter_proc_dev: 0.01
-    pitch_filter_proc_dev: 0.01
-    # for diagnostics
-    pose_no_update_count_threshold_warn: 50
-    pose_no_update_count_threshold_error: 100
-    twist_no_update_count_threshold_warn: 50
-    twist_no_update_count_threshold_error: 100
+    simple_1d_filter_parameters:
+      #Simple1DFilter parameters
+      z_filter_proc_dev: 1.0
+      roll_filter_proc_dev: 0.01
+      pitch_filter_proc_dev: 0.01
 
-    # for velocity measurement limitation (Set 0.0 if you want to ignore)
-    threshold_observable_velocity_mps: 0.0 # [m/s]
+    diagnostics:
+      # for diagnostics
+      pose_no_update_count_threshold_warn: 50
+      pose_no_update_count_threshold_error: 100
+      twist_no_update_count_threshold_warn: 50
+      twist_no_update_count_threshold_error: 100
+
+    misc:
+      # for velocity measurement limitation (Set 0.0 if you want to ignore)
+      threshold_observable_velocity_mps: 0.0 # [m/s]
+      pose_frame_id: "map"

autoware_launch/config/localization/ndt_scan_matcher.param.yaml

@@ -1,103 +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
 
-    # Number of threads used for parallel computing
-    num_threads: 4
+      # Tolerance of timestamp difference between initial_pose and sensor pointcloud. [sec]
+      initial_pose_timeout_sec: 1.0
 
-    # 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,
-      ]
+      # Tolerance of distance difference between two initial poses used for linear interpolation. [m]
+      initial_pose_distance_tolerance_m: 10.0
 
-    # 2D Real-time covariance estimation with multiple searches (output_pose_covariance is the minimum value)
-    use_covariance_estimation: false
+      # The execution time which means probably NDT cannot matches scans properly. [ms]
+      critical_upper_bound_exe_time_ms: 100.0
 
-    # 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]
 
-    # Regularization switch
-    regularization_enabled: false
+    score_estimation:
+      # Converged param type
+      # 0=TRANSFORM_PROBABILITY, 1=NEAREST_VOXEL_TRANSFORMATION_LIKELIHOOD
+      converged_param_type: 1
 
-    # Regularization scale factor
-    regularization_scale_factor: 0.01
+      # If converged_param_type is 0
+      # Threshold for deciding whether to trust the estimation result
+      converged_param_transform_probability: 3.0
 
-    # Dynamic map loading distance
-    dynamic_map_loading_update_distance: 20.0
+      # 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 loading radius
-    dynamic_map_loading_map_radius: 150.0
+      # Scan matching score based on no ground LiDAR scan
+      no_ground_points:
+        enable: false
 
-    # Radius of input LiDAR range (used for diagnostics of dynamic map loading)
-    lidar_radius: 100.0
+        # If lidar_point.z - base_link.z <= this threshold , the point will be removed
+        z_margin_for_ground_removal: 0.8
 
-    # cspell: ignore degrounded
-    # A flag for using scan matching score based on de-grounded LiDAR scan
-    estimate_scores_for_degrounded_scan: false
 
-    # If lidar_point.z - base_link.z <= this threshold , the point will be removed
-    z_margin_for_ground_removal: 0.8
+    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,
+        ]
 
-    # The execution time which means probably NDT cannot matches scans properly. [ms]
-    critical_upper_bound_exe_time_ms: 100
+      # 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

autoware_launch/config/localization/pose_initializer.param.yaml

@@ -2,6 +2,11 @@
   ros__parameters:
     gnss_pose_timeout: 3.0 # [sec]
     stop_check_duration: 3.0 # [sec]
+    ekf_enabled: $(var ekf_enabled)
+    gnss_enabled: $(var gnss_enabled)
+    yabloc_enabled: $(var yabloc_enabled)
+    ndt_enabled: $(var ndt_enabled)
+    stop_check_enabled: $(var stop_check_enabled)
 
     # from gnss
     gnss_particle_covariance:

autoware_launch/config/localization/twist2accel.param.yaml

@@ -0,0 +1,4 @@
+/**:
+  ros__parameters:
+    use_odom: true
+    accel_lowpass_gain: 0.9

autoware_launch/config/map/map_projection_loader.param.yaml

@@ -0,0 +1,4 @@
+/**:
+  ros__parameters:
+    map_projector_info_path: $(var map_projector_info_path)
+    lanelet2_map_path: $(var lanelet2_map_path)

autoware_launch/config/map/map_tf_generator.param.yaml

@@ -0,0 +1,4 @@
+/**:
+  ros__parameters:
+    map_frame: map
+    viewer_frame: viewer

autoware_launch/config/perception/object_recognition/detection/lidar_model/centerpoint.param.yaml

@@ -13,3 +13,14 @@
     iou_nms_search_distance_2d: 10.0
     iou_nms_threshold: 0.1
     yaw_norm_thresholds: [0.3, 0.3, 0.3, 0.3, 0.0]
+    score_threshold: 0.35
+    has_twist: false
+    trt_precision: fp16
+    densification_num_past_frames: 1
+    densification_world_frame_id: map
+
+    # weight files
+    encoder_onnx_path: "$(var model_path)/pts_voxel_encoder_$(var model_name).onnx"
+    encoder_engine_path: "$(var model_path)/pts_voxel_encoder_$(var model_name).engine"
+    head_onnx_path: "$(var model_path)/pts_backbone_neck_head_$(var model_name).onnx"
+    head_engine_path: "$(var model_path)/pts_backbone_neck_head_$(var model_name).engine"

autoware_launch/config/perception/object_recognition/detection/lidar_model/centerpoint_tiny.param.yaml

@@ -13,3 +13,15 @@
     iou_nms_search_distance_2d: 10.0
     iou_nms_threshold: 0.1
     yaw_norm_thresholds: [0.3, 0.3, 0.3, 0.3, 0.0]
+    score_threshold: 0.35
+    build_only: false # shutdown node after TensorRT engine file is built
+    has_twist: false
+    trt_precision: fp16
+    densification_num_past_frames: 1
+    densification_world_frame_id: map
+
+    # weight files
+    encoder_onnx_path: "$(var model_path)/pts_voxel_encoder_$(var model_name).onnx"
+    encoder_engine_path: "$(var model_path)/pts_voxel_encoder_$(var model_name).engine"
+    head_onnx_path: "$(var model_path)/pts_backbone_neck_head_$(var model_name).onnx"
+    head_engine_path: "$(var model_path)/pts_backbone_neck_head_$(var model_name).engine"

autoware_launch/config/perception/object_recognition/detection/lidar_model/detection_class_remapper.param.yaml

@@ -29,9 +29,9 @@
     max_area_matrix:
       #UNKNOWN, CAR,   TRUCK,  BUS,    TRAILER,   MOTORBIKE, BICYCLE, PEDESTRIAN
       [ 0.000,  0.000,  0.000,  0.000,   0.000,   0.000,     0.000,   0.000,      #UNKNOWN
-        0.000,  0.000, 36.000,  0.000,     inf,   0.000,     0.000,   0.000,      #CAR
-        0.000,  0.000,  0.000,  0.000,     inf,   0.000,     0.000,   0.000,      #TRUCK
-        0.000,  0.000,  0.000,  0.000,     inf,   0.000,     0.000,   0.000,      #BUS
+        0.000,  0.000, 36.000,  0.000, 999.999,   0.000,     0.000,   0.000,      #CAR
+        0.000,  0.000,  0.000,  0.000, 999.999,   0.000,     0.000,   0.000,      #TRUCK
+        0.000,  0.000,  0.000,  0.000, 999.999,   0.000,     0.000,   0.000,      #BUS
         0.000,  0.000,  0.000,  0.000,   0.000,   0.000,     0.000,   0.000,      #TRAILER
         0.000,  0.000,  0.000,  0.000,   0.000,   0.000,     0.000,   0.000,      #MOTORBIKE
         0.000,  0.000,  0.000,  0.000,   0.000,   0.000,     0.000,   0.000,      #BICYCLE

autoware_launch/config/perception/object_recognition/detection/lidar_model/pointpainting.param.yaml

@@ -1,5 +1,11 @@
 /**:
   ros__parameters:
+    trt_precision: fp16
+    encoder_onnx_path: "$(var model_path)/pts_voxel_encoder_$(var model_name).onnx"
+    encoder_engine_path: "$(var model_path)/pts_voxel_encoder_$(var model_name).engine"
+    head_onnx_path: "$(var model_path)/pts_backbone_neck_head_$(var model_name).onnx"
+    head_engine_path: "$(var model_path)/pts_backbone_neck_head_$(var model_name).engine"
+
     model_params:
       class_names: ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"]
       paint_class_names: ["CAR", "BICYCLE", "PEDESTRIAN"]

autoware_launch/config/perception/object_recognition/detection/object_range_splitter/object_range_splitter_radar.param.yaml

@@ -0,0 +1,3 @@
+/**:
+  ros__parameters:
+    split_range: 80.0

autoware_launch/config/perception/object_recognition/detection/object_range_splitter/object_range_splitter_radar_fusion.param.yaml

@@ -0,0 +1,3 @@
+/**:
+  ros__parameters:
+    split_range: 70.0

autoware_launch/config/perception/object_recognition/detection/object_velocity_splitter/object_velocity_splitter_radar.param.yaml

@@ -0,0 +1,3 @@
+/**:
+  ros__parameters:
+    velocity_threshold: 5.5

autoware_launch/config/perception/object_recognition/detection/object_velocity_splitter/object_velocity_splitter_radar_fusion.param.yaml

@@ -0,0 +1,3 @@
+/**:
+  ros__parameters:
+    velocity_threshold: 4.5

autoware_launch/config/perception/object_recognition/detection/radar_crossing_objects_noise_filter/radar_crossing_objects_noise_filter.param.yaml

@@ -0,0 +1,4 @@
+/**:
+  ros__parameters:
+    angle_threshold: 1.2210
+    velocity_threshold: 1.5

autoware_launch/config/perception/object_recognition/prediction/map_based_prediction.param.yaml

@@ -19,6 +19,7 @@
     use_vehicle_acceleration: false # whether to consider current vehicle acceleration when predicting paths or not
     speed_limit_multiplier: 1.5 # When using vehicle acceleration. Set vehicle's maximum predicted speed as the legal speed limit in that lanelet times this value
     acceleration_exponential_half_life: 2.5 # [s] When using vehicle acceleration. The decaying acceleration model considers that the current vehicle acceleration will be halved after this many seconds
+    use_crosswalk_signal: true
     # parameter for shoulder lane prediction
     prediction_time_horizon_rate_for_validate_shoulder_lane_length: 0.8