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Merge branch 'main' into feat/conditional_e2e_launch
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name: Lint Autoware System Design Format
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on:
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pull_request:
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paths:
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- "**/*.node.yaml"
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- "**/*.module.yaml"
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- "**/*.system.yaml"
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- "**/*.parameter_set.yaml"
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push:
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branches:
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- main
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paths:
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- "**/*.node.yaml"
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- "**/*.module.yaml"
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- "**/*.system.yaml"
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- "**/*.parameter_set.yaml"
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jobs:
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lint:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout code
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uses: actions/checkout@v4
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- name: Lint system design format files
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uses: autowarefoundation/autoware_system_designer@v0.3.0
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with:
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design_files_path: .

.gitignore

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# Vim
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*.swp
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*.swo
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# Visual Studio Code
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.vscode/
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*.code-workspace
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# colcon
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build/
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install/
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log/
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# Python
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*.pyc
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#prettier
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node_modules/

.pre-commit-config.yaml

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files: .svg$
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additional_dependencies: [prettier@2.7.1, "@prettier/plugin-xml@2.2.0"]
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- repo: https://github.com/autowarefoundation/autoware_system_designer
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rev: v0.3.0
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hooks:
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- id: lint-system-design-format
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args: [--format=github-actions]
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- repo: https://github.com/AleksaC/hadolint-py
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rev: v2.12.1b3
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hooks:

autoware_launch/config/control/trajectory_follower/lateral/mpc.param.yaml

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# steer offset
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steering_offset:
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enable_auto_steering_offset_removal: true
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update_vel_threshold: 5.56
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update_steer_threshold: 0.035
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average_num: 1000
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steering_offset_limit: 0.02
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steer_offset_filter_cutoff_hz: 0.3 # cutoff frequency of lowpass filter for steering offset [Hz]
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publish_debug_trajectories: true # flag to publish predicted trajectory and resampled reference trajectory for debug purpose

autoware_launch/config/perception/object_recognition/detection/image_projection_based_fusion/roi_cluster_fusion.param.yaml

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TRAILER : 0.65
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MOTORCYCLE : 0.65
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BICYCLE : 0.65
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PEDESTRIAN : 0.65
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PEDESTRIAN : 0.2
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remove_unknown: false
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# Pedestrian size validation parameters
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pedestrian_size_validation:
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enable: true # Enable pedestrian size validation (3D size check)
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min_width: 0.1 # Minimum width [m] (shoulder width)
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max_width: 1.0 # Maximum width [m] (with bags/umbrella)

autoware_launch/config/perception/object_recognition/detection/irregular_object_detection/irregular_object_detector.param.yaml

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roi_pointcloud_fusion:
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parameters:
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fuse_unknown_only: true
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override_class_with_unknown: false
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min_cluster_size: 2
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max_cluster_size: 100
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cluster_2d_tolerance: 0.5
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roi_scale_factor: 2.0
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max_object_size: 2.0
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fusion_enabled_classes:
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UNKNOWN: true
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CAR: false
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BUS: false
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TRUCK: false
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TRAILER: false
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MOTORCYCLE: false
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BICYCLE: true
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PEDESTRIAN: true

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

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iou_nms_search_distance_2d: 10.0
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iou_nms_threshold: 0.1
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yaw_norm_thresholds: [0.3, 0.3, 0.3, 0.3, 0.0]
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# CAR, TRUCK, BUS, BICYCLE, PEDESTRIAN
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score_thresholds: [0.35, 0.35, 0.35, 0.35, 0.35]
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densification_params:
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world_frame_id: map
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num_past_frames: 1

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

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iou_nms_search_distance_2d: 10.0
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iou_nms_threshold: 0.1
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yaw_norm_thresholds: [0.3, 0.3, 0.3, 0.3, 0.0]
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# CAR, TRUCK, BUS, BICYCLE, PEDESTRIAN
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score_thresholds: [0.35, 0.35, 0.35, 0.35, 0.35]
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densification_params:
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world_frame_id: map
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num_past_frames: 1

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

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iou_nms_search_distance_2d: 10.0
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iou_nms_threshold: 0.1
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yaw_norm_thresholds: [0.3, 0.3, 0.3, 0.3, 0.0]
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# CAR, TRUCK, BUS, BICYCLE, PEDESTRIAN
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score_thresholds: [0.35, 0.35, 0.35, 0.35, 0.35]
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densification_params:
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world_frame_id: map
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num_past_frames: 1

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

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circle_nms_dist_threshold: 0.3
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iou_nms_search_distance_2d: 10.0
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iou_nms_threshold: 0.1
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# CAR, TRUCK, BUS, BICYCLE, PEDESTRIAN
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score_thresholds: [0.45, 0.45, 0.45, 0.45, 0.45]
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yaw_norm_thresholds: [0.3, 0.3, 0.3, 0.3, 0.0]
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densification_params:
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world_frame_id: "map"

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