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autoware_cuda_pointcloud_preprocessor package from autoware_universe repo

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autoware_behavior_velocity_crosswalk_module autoware_behavior_velocity_detection_area_module autoware_behavior_velocity_intersection_module autoware_behavior_velocity_no_drivable_lane_module autoware_behavior_velocity_no_stopping_area_module autoware_behavior_velocity_occlusion_spot_module autoware_behavior_velocity_roundabout_module autoware_behavior_velocity_rtc_interface autoware_behavior_velocity_speed_bump_module autoware_behavior_velocity_template_module autoware_behavior_velocity_traffic_light_module autoware_behavior_velocity_virtual_traffic_light_module autoware_behavior_velocity_walkway_module autoware_motion_velocity_boundary_departure_prevention_module autoware_motion_velocity_dynamic_obstacle_stop_module autoware_motion_velocity_obstacle_cruise_module autoware_motion_velocity_obstacle_slow_down_module autoware_motion_velocity_obstacle_velocity_limiter_module autoware_motion_velocity_out_of_lane_module autoware_motion_velocity_road_user_stop_module autoware_motion_velocity_run_out_module autoware_planning_validator autoware_planning_validator_intersection_collision_checker autoware_planning_validator_latency_checker autoware_planning_validator_rear_collision_checker autoware_planning_validator_test_utils autoware_planning_validator_trajectory_checker autoware_bezier_sampler autoware_frenet_planner autoware_path_sampler autoware_sampler_common autoware_calibration_status_classifier autoware_cuda_pointcloud_preprocessor autoware_cuda_utils autoware_image_diagnostics autoware_image_transport_decompressor autoware_imu_corrector autoware_pcl_extensions autoware_pointcloud_preprocessor autoware_radar_objects_adapter autoware_radar_scan_to_pointcloud2 autoware_radar_static_pointcloud_filter autoware_radar_threshold_filter autoware_radar_tracks_noise_filter autoware_livox_tag_filter autoware_carla_interface autoware_dummy_perception_publisher autoware_fault_injection autoware_learning_based_vehicle_model 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Package Summary

Tags	No category tags.
Version	0.48.0
License	Apache License 2.0
Build type	AMENT_CMAKE
Use	RECOMMENDED

Repository Summary

Description
Checkout URI	https://github.com/autowarefoundation/autoware_universe.git
VCS Type	git
VCS Version	main
Last Updated	2025-12-03
Dev Status	UNKNOWN
Released	UNRELEASED
Tags	planner ros calibration self-driving-car autonomous-driving autonomous-vehicles ros2 3d-map autoware
Contributing	Help Wanted (-) Good First Issues (-) Pull Requests to Review (-)

Package Description

autoware_cuda_pointcloud_preprocessor

Additional Links

No additional links.

Maintainers

Kenzo Lobos-Tsunekawa
Amadeusz Szymko
Max Schmeller
David Wong
Manato Hirabayashi
Yihsiang Fang

Authors

Kenzo Lobos-Tsunekawa

sensing/autoware_cuda_pointcloud_preprocessor/README.md

autoware_cuda_pointcloud_preprocessor

Purpose

The pointcloud preprocessing implemented in autoware_pointcloud_preprocessor has been thoroughly tested in autoware. However, the latency it introduces does not scale well with modern LiDAR devices due to the high number of points they introduce.

To alleviate this issue, this package reimplements most of the pipeline presented in autoware_pointcloud_preprocessor leveraging the use of GPGPUs. In particular, this package makes use of CUDA to provide accelerated versions of the already established implementations, while also maintaining compatibility with normal ROS nodes/topics.

Inner-workings / Algorithms

A detailed description of each filter’s algorithm is available in the following links.

Filter Name	Description	Detail
cuda_pointcloud_preprocessor	Implements the cropping, distortion correction, and outlier filtering (ring-based) of the `autoware_pointcloud_preprocessor`’s CPU versions.	link
cuda_concatenate_and_time_sync_node	Implements pointcloud concatenation an synchronization following `autoware_pointcloud_preprocessor`’s CPU implementation.	link
cuda_voxel_grid_downsample_filter	Implements voxel downsample filtering of the `autoware_pointcloud_preprocessor`’s CPU version	link
cuda_polar_voxel_outlier_filter	Implements polar voxel outlier filtering of the `autoware_pointcloud_preprocessor`’s CPU version	link

(Optional) Future extensions / Unimplemented parts

The subsample filters implemented in autoware_pointcloud_preprocessor will have similar counterparts in this package.

CHANGELOG

Changelog for package autoware_cuda_pointcloud_preprocessor

0.48.0 (2025-11-18)

Merge remote-tracking branch 'origin/main' into humble
fix: tf2 uses hpp headers in rolling (and is backported) (#11620)
fix(cuda_pointcloud_preprocessor): use uint64_t and nanoseconds to prevent potential precision loss (#11398)
feat(autoware_cuda_pointcloud_preprocessor): cuda/polar voxel filter (#11122)
- feat(cuda_utils): support device memory allocation from memory pool
* feat(cuda_pointcloud_preprocessor): support polar_voxel_outlier_filter WIP: use cuda::std::optional. compile passed wip: version 1 wip: update wip: update launcher
- feat(cuda_pointcloud_preprocessor): add a flag to enable/disable ring outlier filter in cuda_pointcloud_preprocessor
- chore: clean up the code
- docs: update documents briefly
- style(pre-commit): autofix
- style(pre-commit): autofix
- feat(cuda_polar_voxel_outlier_filter): add xyzirc format support
- fix(cuda_polar_voxel_outlier_filter): move sync point to avoid unexpected memory release during async copy
- chore(cuda_polar_voxel_outlier_filter): update parameters
- add SI unit postfix
- deprecate [secondary_return_type]{.title-ref}
- and think points with non-primary return value as points with secondary return
- refactor(cuda_polar_voxel_outlier_filter): explicity specify index integer type
- refactor(cuda_polar_voxel_outlier_filter): snake case for functions
* refactor(cuda_polar_voxel_outlier_filter): std::optional for visibility and filter ratio And update related task functions for diagnostics
- fix(cuda_polar_voxel_outlier_filter): register parameters_callback
- refactor(cuda_polar_voxel_outlier_filter): remove log spam and unneccesary comments
- refactor(cuda_polar_voxel_outlier_filter): rename [valid_points_mask]{.title-ref}
* feat(cuda_polar_voxel_outlier_filter): make noise pointcloud publishing optional Because all parameters are now compatible with [autoware_pointcloud_preprocessor::polar_voxel_outlier_filter]{.title-ref}, this commit also removes the parameter files named [cuda_polar_voxel_outlier_filter.param.yaml]{.title-ref} to avoid duplicated file copying.
- refactor(cuda_polar_voxel_outlier_filter): simplify by enforcing use of XYZIRC or XYZIRCAEDT
- feat(cuda_polar_voxel_outlier_filter): limit range in visibility calculation
- refactor(cuda_polar_voxel_outlier_filter): use array of int for return_type instead of int64
* refactor(cuda_polar_voxel_outlier_filter): update parameter callback to align with the CPU implementation And small clean up the codes

* fix(cuda_polar_voxel_outlier_filter): return when invalid index fix the error revealed by [compute-sanitizer --tool memcheck]{.title-ref}

* feat(cuda_polar_voxel_outlier_filter): add visibility estimation parameters And update visibility calculation to align with the CPU implementation
- feat(cuda_polar_voxel_outlier_filter): add option to not publish a filtered pointcloud (only estimate visibility)
- fix(cuda_polar_voxel_outlier_filter): ensure zero started positive values for indices
- feat(cuda_polar_voxel_outlier_filter): add input validation. align diag format to the CPU implementation
- perf(cuda_polar_voxel_outlier_filter): skip output generation if visualization_estimation_only==true
- refactor(cuda_polar_voxel_outlier_filter): clean up the code
- feat(cuda_polar_voxel_outlier_filter): add intensity parameter for secondary returns
- fix(cuda_polar_voxel_outlier_filter): update param name to align CPU impl.
- feat(cuda_polar_voxel_outlier_filter): update codes to align CPU impl.
- fix(cuda_polar_voxel_outlier_filter): correct unintended comparison
- fix(cuda_polar_voxel_outlier_filter): correct meaningless cast
- refactor(cuda_polar_voxel_outlier_filter): unify common calculation

File truncated at 100 lines see the full file

Package Dependencies

Deps	Name
	ament_cmake_auto
	autoware_cmake
	ament_clang_format
	ament_lint_auto
	ament_lint_common
	agnocastlib
	autoware_agnocast_wrapper
	autoware_cuda_dependency_meta
	autoware_cuda_utils
	autoware_point_types
	autoware_pointcloud_preprocessor
	autoware_sensing_msgs
	autoware_utils
	cuda_blackboard
	diagnostic_msgs
	rclcpp
	rclcpp_components
	sensor_msgs
	tf2
	tf2_msgs
	tier4_debug_msgs

System Dependencies

No direct system dependencies.

Dependant Packages

No known dependants.

Launch files

launch/cuda_concatenate_and_time_sync_node.launch.xml
- - input/twist [default: /sensing/vehicle_velocity_converter/twist_with_covariance]
  - output [default: /sensing/lidar/concatenated/pointcloud]
  - output_info [default: /sensing/lidar/concatenated/pointcloud_info]
  - param_file [default: $(find-pkg-share autoware_pointcloud_preprocessor)/config/concatenate_and_time_sync_node.param.yaml]
launch/cuda_pointcloud_preprocessor.launch.xml
- - input/pointcloud [default: /sensing/lidar/top/pointcloud_raw_ex]
  - input/imu [default: /sensing/imu/imu_data]
  - input/twist [default: /sensing/vehicle_velocity_converter/twist_with_covariance]
  - output/pointcloud [default: /sensing/lidar/top/test]
  - cuda_pointcloud_preprocessor_param_file [default: $(find-pkg-share autoware_cuda_pointcloud_preprocessor)/config/cuda_pointcloud_preprocessor.param.yaml]
launch/cuda_polar_voxel_outlier_filter.launch.xml
- - input/pointcloud [default: /sensing/lidar/top/pointcloud_raw]
  - output/pointcloud [default: /sensing/lidar/top/filtered]
  - debug [default: false]
  - use_sim_time [default: false]
  - polar_voxel_outlier_filter_param_file [default: $(find-pkg-share autoware_pointcloud_preprocessor)/config/polar_voxel_outlier_filter_node.param.yaml]
launch/cuda_voxel_grid_downsample_filter.launch.xml
- - input/pointcloud [default: /sensing/lidar/top/pointcloud_raw]
  - output/pointcloud [default: /sensing/lidar/top/downsampled]
  - debug [default: false]
  - cuda_voxel_gird_downsample_filter_param_file [default: $(find-pkg-share autoware_cuda_pointcloud_preprocessor)/config/cuda_voxel_grid_downsample_filter.param.yaml]

Messages

No message files found.

Services

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Plugins

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