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autoware_ptv3 package from autoware_universe repo

autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_designs autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_spheric_collision_detector autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_tensorrt_vad autoware_control_evaluator autoware_evaluation_adapter autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_camera_streampetr autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_ground_segmentation_cuda autoware_image_object_locator autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_frnet autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_sorter autoware_occupancy_grid_map_outlier_filter autoware_predicted_path_postprocessor autoware_probabilistic_occupancy_grid_map autoware_ptv3 autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_bevformer autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_manual_lane_change_handler autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_trajectory_adapter autoware_trajectory_concatenator autoware_trajectory_modifier autoware_trajectory_optimizer autoware_trajectory_ranker autoware_trajectory_validator autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module 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 autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_manual_lane_change_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

ROS Distro
github

API Docs
Browse Code

Package Summary

Version 0.50.0
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 2026-04-07
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_ptv3 package

Maintainers

  • Kenzo Lobos-Tsunekawa
  • Amadeusz Szymko
  • Manato Hirabayashi

Authors

No additional authors.
perception/autoware_ptv3/README.md

autoware_ptv3

Purpose

The autoware_ptv3 package is used for 3D lidar segmentation.

Inner-workings / Algorithms

This package implements a TensorRT powered inference node for Point Transformers V3 (PTv3) [1]. The sparse convolution backend corresponds to spconv. Autoware installs it automatically in its setup script. If needed, the user can also build it and install it following the following instructions.

Inputs / Outputs

Input

Name Type Description
~/input/pointcloud sensor_msgs::msg::PointCloud2 Input pointcloud topic.

Output

Name Type Description
~/output/pointcloud/segmentation sensor_msgs::msg::PointCloud2 XYZ cloud with class ID and probability fields.
~/output/pointcloud/visualization sensor_msgs::msg::PointCloud2 XYZ cloud with RGB field.
~/output/pointcloud/filtered sensor_msgs::msg::PointCloud2 Filtered cloud in the requested filter.output_format.
debug/cyclic_time_ms autoware_internal_debug_msgs::msg::Float64Stamped Cyclic time (ms).
debug/pipeline_latency_ms autoware_internal_debug_msgs::msg::Float64Stamped Pipeline latency time (ms).
debug/processing_time/preprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Preprocess (ms).
debug/processing_time/inference_ms autoware_internal_debug_msgs::msg::Float64Stamped Inference time (ms).
debug/processing_time/postprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Postprocess time (ms).
debug/processing_time/total_ms autoware_internal_debug_msgs::msg::Float64Stamped Total processing time (ms).

Parameters

PTv3Node node

{{ json_to_markdown(“perception/autoware_ptv3/schema/ptv3.schema.json”) }}

PTv3Node model

{{ json_to_markdown(“perception/autoware_ptv3/schema/ml_package_ptv3.schema.json”) }}

filter.* parameters are configured in config/ptv3.param.yaml, while class metadata and the visualization palette are configured in config/ml_package_ptv3.param.yaml.

The build_only option

The autoware_ptv3 node has a build_only option to build the TensorRT engine file from the specified ONNX file, after which the program exits.

ros2 launch autoware_ptv3 ptv3.launch.xml build_only:=true

The log_level option

The default logging severity level for autoware_ptv3 is info. For debugging purposes, the developer may decrease severity level using log_level parameter:

ros2 launch autoware_ptv3 ptv3.launch.xml log_level:=debug

Assumptions / Known limits

This node detects the input pointcloud format automatically on the first received message and supports:

  • XYZIRCAEDT (10 fields)
  • XYZIRADRT (9 fields)
  • XYZIRC (6 fields)
  • XYZI (4 fields)

The filtered output cloud format is controlled by filter.output_format. When it is set to an empty string, the filtered output preserves the same format as the input cloud.

Trained Models

The model was trained on the T4Dataset using approximately 4,000 frames and is available in the Autoware artifacts.

Troubleshooting

Fail to create host memory

This error may occur when the system runs out of memory during TensorRT engine building. To mitigate this issue, consider reducing the voxels_num maximum limit in the model parameters, which controls the maximum number of voxels processed by the model. For the instance, using GPU with 8 GB of memory, setting maximum voxels_num to 192’000 may help to avoid this error.

[1] Xiaoyang Wu, Li Jiang, Peng-Shuai Wang, Zhijian Liu, Xihui Liu, Yu Qiao, Wanli Ouyang, Tong He, and Hengshuang Zhao. “Point Transformer V3: Simpler, Faster, Stronger.” 2024 Conference on Computer Vision and Pattern Recognition.

CHANGELOG

Changelog for package autoware_ptv3

0.50.0 (2026-02-14)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): update nvcc flags (#12053)

  • chore(autoware_ptv3): remove cudnn dependency (#11894)

  • chore: add maintainer of PTv3, FRNet, and CalibrationStatusClassifier (#11945)

    • chore: update [autoware_ptv3]{.title-ref} maintainer
    • chore: update [autoware_lidar_frnet]{.title-ref} maintainer

    * chore: update [autoware_calibration_status_classifier]{.title-ref} maintainer ---------

  • Contributors: Amadeusz Szymko, Manato Hirabayashi, Ryohsuke Mitsudome

0.49.0 (2025-12-30)

0.48.0 (2025-11-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): implemented an inference node for ptv3 using tensorrt (#10600)

    • feat: implemented an inference node for ptv3 using tensorrt
    • chore: cspells
    • chore: schemas
    • chore: lint (line was too long)
    • chore: more schemas
    • fix: mistook the compute capabilities of edge devices
    • chore: replaced incorrect bevfusion -> ptv3
    • chore: forgot to remove unused schema
    • chore: duplicated variable
    • chore: changed package dep name
    • chore: fixed schema comment
    • chore: removed unused headers in the post process kernels
    • chore: replaced in favor of auto
    • chore: removed unused headers
    • chore: changed initialization order
    • chore: replaced 0 by nullptr
    • chore: replaced type in favor of auto
    • chore: removed redundant message
    • chore: fixed compilation due to review changes
    • fix: replaced int64 by uint64
    • chore: added more descriptive comment in the schema

    * style(autoware_ptv3): cleanup ---------Co-authored-by: Amadeusz Szymko <<amadeusz.szymko.2@tier4.jp>>

  • Contributors: Kenzo Lobos Tsunekawa, Ryohsuke Mitsudome

Launch files

  • launch/ptv3.launch.xml
      • input/pointcloud [default: /sensing/lidar/concatenated/pointcloud]
      • output/pointcloud/segmentation [default: ~/segmentation]
      • output/pointcloud/visualization [default: ~/visualization]
      • output/pointcloud/filtered [default: ~/filtered]
      • data_path [default: $(env HOME)/autoware_data]
      • model_name [default: ptv3]
      • model_path [default: $(var data_path)/ptv3]
      • model_param_path [default: $(find-pkg-share autoware_ptv3)/config/$(var model_name).param.yaml]
      • ml_package_param_path [default: $(var model_path)/ml_package_$(var model_name).param.yaml]
      • class_remapper_param_path [default: $(var model_path)/detection_class_remapper.param.yaml]
      • build_only [default: false]
      • log_level [default: info]
      • use_pointcloud_container [default: false]
      • pointcloud_container_name [default: pointcloud_container]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged autoware_ptv3 at Robotics Stack Exchange

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autoware_ptv3 package from autoware_universe repo

autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_designs autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_spheric_collision_detector autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_tensorrt_vad autoware_control_evaluator autoware_evaluation_adapter autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_camera_streampetr autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_ground_segmentation_cuda autoware_image_object_locator autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_frnet autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_sorter autoware_occupancy_grid_map_outlier_filter autoware_predicted_path_postprocessor autoware_probabilistic_occupancy_grid_map autoware_ptv3 autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_bevformer autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_manual_lane_change_handler autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_trajectory_adapter autoware_trajectory_concatenator autoware_trajectory_modifier autoware_trajectory_optimizer autoware_trajectory_ranker autoware_trajectory_validator autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module 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 autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_manual_lane_change_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

ROS Distro
github

API Docs
Browse Code

Package Summary

Version 0.50.0
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 2026-04-07
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_ptv3 package

Maintainers

  • Kenzo Lobos-Tsunekawa
  • Amadeusz Szymko
  • Manato Hirabayashi

Authors

No additional authors.
perception/autoware_ptv3/README.md

autoware_ptv3

Purpose

The autoware_ptv3 package is used for 3D lidar segmentation.

Inner-workings / Algorithms

This package implements a TensorRT powered inference node for Point Transformers V3 (PTv3) [1]. The sparse convolution backend corresponds to spconv. Autoware installs it automatically in its setup script. If needed, the user can also build it and install it following the following instructions.

Inputs / Outputs

Input

Name Type Description
~/input/pointcloud sensor_msgs::msg::PointCloud2 Input pointcloud topic.

Output

Name Type Description
~/output/pointcloud/segmentation sensor_msgs::msg::PointCloud2 XYZ cloud with class ID and probability fields.
~/output/pointcloud/visualization sensor_msgs::msg::PointCloud2 XYZ cloud with RGB field.
~/output/pointcloud/filtered sensor_msgs::msg::PointCloud2 Filtered cloud in the requested filter.output_format.
debug/cyclic_time_ms autoware_internal_debug_msgs::msg::Float64Stamped Cyclic time (ms).
debug/pipeline_latency_ms autoware_internal_debug_msgs::msg::Float64Stamped Pipeline latency time (ms).
debug/processing_time/preprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Preprocess (ms).
debug/processing_time/inference_ms autoware_internal_debug_msgs::msg::Float64Stamped Inference time (ms).
debug/processing_time/postprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Postprocess time (ms).
debug/processing_time/total_ms autoware_internal_debug_msgs::msg::Float64Stamped Total processing time (ms).

Parameters

PTv3Node node

{{ json_to_markdown(“perception/autoware_ptv3/schema/ptv3.schema.json”) }}

PTv3Node model

{{ json_to_markdown(“perception/autoware_ptv3/schema/ml_package_ptv3.schema.json”) }}

filter.* parameters are configured in config/ptv3.param.yaml, while class metadata and the visualization palette are configured in config/ml_package_ptv3.param.yaml.

The build_only option

The autoware_ptv3 node has a build_only option to build the TensorRT engine file from the specified ONNX file, after which the program exits.

ros2 launch autoware_ptv3 ptv3.launch.xml build_only:=true

The log_level option

The default logging severity level for autoware_ptv3 is info. For debugging purposes, the developer may decrease severity level using log_level parameter:

ros2 launch autoware_ptv3 ptv3.launch.xml log_level:=debug

Assumptions / Known limits

This node detects the input pointcloud format automatically on the first received message and supports:

  • XYZIRCAEDT (10 fields)
  • XYZIRADRT (9 fields)
  • XYZIRC (6 fields)
  • XYZI (4 fields)

The filtered output cloud format is controlled by filter.output_format. When it is set to an empty string, the filtered output preserves the same format as the input cloud.

Trained Models

The model was trained on the T4Dataset using approximately 4,000 frames and is available in the Autoware artifacts.

Troubleshooting

Fail to create host memory

This error may occur when the system runs out of memory during TensorRT engine building. To mitigate this issue, consider reducing the voxels_num maximum limit in the model parameters, which controls the maximum number of voxels processed by the model. For the instance, using GPU with 8 GB of memory, setting maximum voxels_num to 192’000 may help to avoid this error.

[1] Xiaoyang Wu, Li Jiang, Peng-Shuai Wang, Zhijian Liu, Xihui Liu, Yu Qiao, Wanli Ouyang, Tong He, and Hengshuang Zhao. “Point Transformer V3: Simpler, Faster, Stronger.” 2024 Conference on Computer Vision and Pattern Recognition.

CHANGELOG

Changelog for package autoware_ptv3

0.50.0 (2026-02-14)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): update nvcc flags (#12053)

  • chore(autoware_ptv3): remove cudnn dependency (#11894)

  • chore: add maintainer of PTv3, FRNet, and CalibrationStatusClassifier (#11945)

    • chore: update [autoware_ptv3]{.title-ref} maintainer
    • chore: update [autoware_lidar_frnet]{.title-ref} maintainer

    * chore: update [autoware_calibration_status_classifier]{.title-ref} maintainer ---------

  • Contributors: Amadeusz Szymko, Manato Hirabayashi, Ryohsuke Mitsudome

0.49.0 (2025-12-30)

0.48.0 (2025-11-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): implemented an inference node for ptv3 using tensorrt (#10600)

    • feat: implemented an inference node for ptv3 using tensorrt
    • chore: cspells
    • chore: schemas
    • chore: lint (line was too long)
    • chore: more schemas
    • fix: mistook the compute capabilities of edge devices
    • chore: replaced incorrect bevfusion -> ptv3
    • chore: forgot to remove unused schema
    • chore: duplicated variable
    • chore: changed package dep name
    • chore: fixed schema comment
    • chore: removed unused headers in the post process kernels
    • chore: replaced in favor of auto
    • chore: removed unused headers
    • chore: changed initialization order
    • chore: replaced 0 by nullptr
    • chore: replaced type in favor of auto
    • chore: removed redundant message
    • chore: fixed compilation due to review changes
    • fix: replaced int64 by uint64
    • chore: added more descriptive comment in the schema

    * style(autoware_ptv3): cleanup ---------Co-authored-by: Amadeusz Szymko <<amadeusz.szymko.2@tier4.jp>>

  • Contributors: Kenzo Lobos Tsunekawa, Ryohsuke Mitsudome

Launch files

  • launch/ptv3.launch.xml
      • input/pointcloud [default: /sensing/lidar/concatenated/pointcloud]
      • output/pointcloud/segmentation [default: ~/segmentation]
      • output/pointcloud/visualization [default: ~/visualization]
      • output/pointcloud/filtered [default: ~/filtered]
      • data_path [default: $(env HOME)/autoware_data]
      • model_name [default: ptv3]
      • model_path [default: $(var data_path)/ptv3]
      • model_param_path [default: $(find-pkg-share autoware_ptv3)/config/$(var model_name).param.yaml]
      • ml_package_param_path [default: $(var model_path)/ml_package_$(var model_name).param.yaml]
      • class_remapper_param_path [default: $(var model_path)/detection_class_remapper.param.yaml]
      • build_only [default: false]
      • log_level [default: info]
      • use_pointcloud_container [default: false]
      • pointcloud_container_name [default: pointcloud_container]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged autoware_ptv3 at Robotics Stack Exchange

No version for distro kilted showing github. Known supported distros are highlighted in the buttons above.
Package symbol

autoware_ptv3 package from autoware_universe repo

autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_designs autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_spheric_collision_detector autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_tensorrt_vad autoware_control_evaluator autoware_evaluation_adapter autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_camera_streampetr autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_ground_segmentation_cuda autoware_image_object_locator autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_frnet autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_sorter autoware_occupancy_grid_map_outlier_filter autoware_predicted_path_postprocessor autoware_probabilistic_occupancy_grid_map autoware_ptv3 autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_bevformer autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_manual_lane_change_handler autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_trajectory_adapter autoware_trajectory_concatenator autoware_trajectory_modifier autoware_trajectory_optimizer autoware_trajectory_ranker autoware_trajectory_validator autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module 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 autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_manual_lane_change_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

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API Docs
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Package Summary

Version 0.50.0
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 2026-04-07
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_ptv3 package

Maintainers

  • Kenzo Lobos-Tsunekawa
  • Amadeusz Szymko
  • Manato Hirabayashi

Authors

No additional authors.
perception/autoware_ptv3/README.md

autoware_ptv3

Purpose

The autoware_ptv3 package is used for 3D lidar segmentation.

Inner-workings / Algorithms

This package implements a TensorRT powered inference node for Point Transformers V3 (PTv3) [1]. The sparse convolution backend corresponds to spconv. Autoware installs it automatically in its setup script. If needed, the user can also build it and install it following the following instructions.

Inputs / Outputs

Input

Name Type Description
~/input/pointcloud sensor_msgs::msg::PointCloud2 Input pointcloud topic.

Output

Name Type Description
~/output/pointcloud/segmentation sensor_msgs::msg::PointCloud2 XYZ cloud with class ID and probability fields.
~/output/pointcloud/visualization sensor_msgs::msg::PointCloud2 XYZ cloud with RGB field.
~/output/pointcloud/filtered sensor_msgs::msg::PointCloud2 Filtered cloud in the requested filter.output_format.
debug/cyclic_time_ms autoware_internal_debug_msgs::msg::Float64Stamped Cyclic time (ms).
debug/pipeline_latency_ms autoware_internal_debug_msgs::msg::Float64Stamped Pipeline latency time (ms).
debug/processing_time/preprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Preprocess (ms).
debug/processing_time/inference_ms autoware_internal_debug_msgs::msg::Float64Stamped Inference time (ms).
debug/processing_time/postprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Postprocess time (ms).
debug/processing_time/total_ms autoware_internal_debug_msgs::msg::Float64Stamped Total processing time (ms).

Parameters

PTv3Node node

{{ json_to_markdown(“perception/autoware_ptv3/schema/ptv3.schema.json”) }}

PTv3Node model

{{ json_to_markdown(“perception/autoware_ptv3/schema/ml_package_ptv3.schema.json”) }}

filter.* parameters are configured in config/ptv3.param.yaml, while class metadata and the visualization palette are configured in config/ml_package_ptv3.param.yaml.

The build_only option

The autoware_ptv3 node has a build_only option to build the TensorRT engine file from the specified ONNX file, after which the program exits.

ros2 launch autoware_ptv3 ptv3.launch.xml build_only:=true

The log_level option

The default logging severity level for autoware_ptv3 is info. For debugging purposes, the developer may decrease severity level using log_level parameter:

ros2 launch autoware_ptv3 ptv3.launch.xml log_level:=debug

Assumptions / Known limits

This node detects the input pointcloud format automatically on the first received message and supports:

  • XYZIRCAEDT (10 fields)
  • XYZIRADRT (9 fields)
  • XYZIRC (6 fields)
  • XYZI (4 fields)

The filtered output cloud format is controlled by filter.output_format. When it is set to an empty string, the filtered output preserves the same format as the input cloud.

Trained Models

The model was trained on the T4Dataset using approximately 4,000 frames and is available in the Autoware artifacts.

Troubleshooting

Fail to create host memory

This error may occur when the system runs out of memory during TensorRT engine building. To mitigate this issue, consider reducing the voxels_num maximum limit in the model parameters, which controls the maximum number of voxels processed by the model. For the instance, using GPU with 8 GB of memory, setting maximum voxels_num to 192’000 may help to avoid this error.

[1] Xiaoyang Wu, Li Jiang, Peng-Shuai Wang, Zhijian Liu, Xihui Liu, Yu Qiao, Wanli Ouyang, Tong He, and Hengshuang Zhao. “Point Transformer V3: Simpler, Faster, Stronger.” 2024 Conference on Computer Vision and Pattern Recognition.

CHANGELOG

Changelog for package autoware_ptv3

0.50.0 (2026-02-14)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): update nvcc flags (#12053)

  • chore(autoware_ptv3): remove cudnn dependency (#11894)

  • chore: add maintainer of PTv3, FRNet, and CalibrationStatusClassifier (#11945)

    • chore: update [autoware_ptv3]{.title-ref} maintainer
    • chore: update [autoware_lidar_frnet]{.title-ref} maintainer

    * chore: update [autoware_calibration_status_classifier]{.title-ref} maintainer ---------

  • Contributors: Amadeusz Szymko, Manato Hirabayashi, Ryohsuke Mitsudome

0.49.0 (2025-12-30)

0.48.0 (2025-11-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): implemented an inference node for ptv3 using tensorrt (#10600)

    • feat: implemented an inference node for ptv3 using tensorrt
    • chore: cspells
    • chore: schemas
    • chore: lint (line was too long)
    • chore: more schemas
    • fix: mistook the compute capabilities of edge devices
    • chore: replaced incorrect bevfusion -> ptv3
    • chore: forgot to remove unused schema
    • chore: duplicated variable
    • chore: changed package dep name
    • chore: fixed schema comment
    • chore: removed unused headers in the post process kernels
    • chore: replaced in favor of auto
    • chore: removed unused headers
    • chore: changed initialization order
    • chore: replaced 0 by nullptr
    • chore: replaced type in favor of auto
    • chore: removed redundant message
    • chore: fixed compilation due to review changes
    • fix: replaced int64 by uint64
    • chore: added more descriptive comment in the schema

    * style(autoware_ptv3): cleanup ---------Co-authored-by: Amadeusz Szymko <<amadeusz.szymko.2@tier4.jp>>

  • Contributors: Kenzo Lobos Tsunekawa, Ryohsuke Mitsudome

Launch files

  • launch/ptv3.launch.xml
      • input/pointcloud [default: /sensing/lidar/concatenated/pointcloud]
      • output/pointcloud/segmentation [default: ~/segmentation]
      • output/pointcloud/visualization [default: ~/visualization]
      • output/pointcloud/filtered [default: ~/filtered]
      • data_path [default: $(env HOME)/autoware_data]
      • model_name [default: ptv3]
      • model_path [default: $(var data_path)/ptv3]
      • model_param_path [default: $(find-pkg-share autoware_ptv3)/config/$(var model_name).param.yaml]
      • ml_package_param_path [default: $(var model_path)/ml_package_$(var model_name).param.yaml]
      • class_remapper_param_path [default: $(var model_path)/detection_class_remapper.param.yaml]
      • build_only [default: false]
      • log_level [default: info]
      • use_pointcloud_container [default: false]
      • pointcloud_container_name [default: pointcloud_container]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged autoware_ptv3 at Robotics Stack Exchange

No version for distro rolling showing github. Known supported distros are highlighted in the buttons above.
Package symbol

autoware_ptv3 package from autoware_universe repo

autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_designs autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_spheric_collision_detector autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_tensorrt_vad autoware_control_evaluator autoware_evaluation_adapter autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_camera_streampetr autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_ground_segmentation_cuda autoware_image_object_locator autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_frnet autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_sorter autoware_occupancy_grid_map_outlier_filter autoware_predicted_path_postprocessor autoware_probabilistic_occupancy_grid_map autoware_ptv3 autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_bevformer autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_manual_lane_change_handler autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_trajectory_adapter autoware_trajectory_concatenator autoware_trajectory_modifier autoware_trajectory_optimizer autoware_trajectory_ranker autoware_trajectory_validator autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module 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 autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_manual_lane_change_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

ROS Distro
github

API Docs
Browse Code

Package Summary

Version 0.50.0
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 2026-04-07
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_ptv3 package

Maintainers

  • Kenzo Lobos-Tsunekawa
  • Amadeusz Szymko
  • Manato Hirabayashi

Authors

No additional authors.
perception/autoware_ptv3/README.md

autoware_ptv3

Purpose

The autoware_ptv3 package is used for 3D lidar segmentation.

Inner-workings / Algorithms

This package implements a TensorRT powered inference node for Point Transformers V3 (PTv3) [1]. The sparse convolution backend corresponds to spconv. Autoware installs it automatically in its setup script. If needed, the user can also build it and install it following the following instructions.

Inputs / Outputs

Input

Name Type Description
~/input/pointcloud sensor_msgs::msg::PointCloud2 Input pointcloud topic.

Output

Name Type Description
~/output/pointcloud/segmentation sensor_msgs::msg::PointCloud2 XYZ cloud with class ID and probability fields.
~/output/pointcloud/visualization sensor_msgs::msg::PointCloud2 XYZ cloud with RGB field.
~/output/pointcloud/filtered sensor_msgs::msg::PointCloud2 Filtered cloud in the requested filter.output_format.
debug/cyclic_time_ms autoware_internal_debug_msgs::msg::Float64Stamped Cyclic time (ms).
debug/pipeline_latency_ms autoware_internal_debug_msgs::msg::Float64Stamped Pipeline latency time (ms).
debug/processing_time/preprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Preprocess (ms).
debug/processing_time/inference_ms autoware_internal_debug_msgs::msg::Float64Stamped Inference time (ms).
debug/processing_time/postprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Postprocess time (ms).
debug/processing_time/total_ms autoware_internal_debug_msgs::msg::Float64Stamped Total processing time (ms).

Parameters

PTv3Node node

{{ json_to_markdown(“perception/autoware_ptv3/schema/ptv3.schema.json”) }}

PTv3Node model

{{ json_to_markdown(“perception/autoware_ptv3/schema/ml_package_ptv3.schema.json”) }}

filter.* parameters are configured in config/ptv3.param.yaml, while class metadata and the visualization palette are configured in config/ml_package_ptv3.param.yaml.

The build_only option

The autoware_ptv3 node has a build_only option to build the TensorRT engine file from the specified ONNX file, after which the program exits.

ros2 launch autoware_ptv3 ptv3.launch.xml build_only:=true

The log_level option

The default logging severity level for autoware_ptv3 is info. For debugging purposes, the developer may decrease severity level using log_level parameter:

ros2 launch autoware_ptv3 ptv3.launch.xml log_level:=debug

Assumptions / Known limits

This node detects the input pointcloud format automatically on the first received message and supports:

  • XYZIRCAEDT (10 fields)
  • XYZIRADRT (9 fields)
  • XYZIRC (6 fields)
  • XYZI (4 fields)

The filtered output cloud format is controlled by filter.output_format. When it is set to an empty string, the filtered output preserves the same format as the input cloud.

Trained Models

The model was trained on the T4Dataset using approximately 4,000 frames and is available in the Autoware artifacts.

Troubleshooting

Fail to create host memory

This error may occur when the system runs out of memory during TensorRT engine building. To mitigate this issue, consider reducing the voxels_num maximum limit in the model parameters, which controls the maximum number of voxels processed by the model. For the instance, using GPU with 8 GB of memory, setting maximum voxels_num to 192’000 may help to avoid this error.

[1] Xiaoyang Wu, Li Jiang, Peng-Shuai Wang, Zhijian Liu, Xihui Liu, Yu Qiao, Wanli Ouyang, Tong He, and Hengshuang Zhao. “Point Transformer V3: Simpler, Faster, Stronger.” 2024 Conference on Computer Vision and Pattern Recognition.

CHANGELOG

Changelog for package autoware_ptv3

0.50.0 (2026-02-14)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): update nvcc flags (#12053)

  • chore(autoware_ptv3): remove cudnn dependency (#11894)

  • chore: add maintainer of PTv3, FRNet, and CalibrationStatusClassifier (#11945)

    • chore: update [autoware_ptv3]{.title-ref} maintainer
    • chore: update [autoware_lidar_frnet]{.title-ref} maintainer

    * chore: update [autoware_calibration_status_classifier]{.title-ref} maintainer ---------

  • Contributors: Amadeusz Szymko, Manato Hirabayashi, Ryohsuke Mitsudome

0.49.0 (2025-12-30)

0.48.0 (2025-11-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): implemented an inference node for ptv3 using tensorrt (#10600)

    • feat: implemented an inference node for ptv3 using tensorrt
    • chore: cspells
    • chore: schemas
    • chore: lint (line was too long)
    • chore: more schemas
    • fix: mistook the compute capabilities of edge devices
    • chore: replaced incorrect bevfusion -> ptv3
    • chore: forgot to remove unused schema
    • chore: duplicated variable
    • chore: changed package dep name
    • chore: fixed schema comment
    • chore: removed unused headers in the post process kernels
    • chore: replaced in favor of auto
    • chore: removed unused headers
    • chore: changed initialization order
    • chore: replaced 0 by nullptr
    • chore: replaced type in favor of auto
    • chore: removed redundant message
    • chore: fixed compilation due to review changes
    • fix: replaced int64 by uint64
    • chore: added more descriptive comment in the schema

    * style(autoware_ptv3): cleanup ---------Co-authored-by: Amadeusz Szymko <<amadeusz.szymko.2@tier4.jp>>

  • Contributors: Kenzo Lobos Tsunekawa, Ryohsuke Mitsudome

Launch files

  • launch/ptv3.launch.xml
      • input/pointcloud [default: /sensing/lidar/concatenated/pointcloud]
      • output/pointcloud/segmentation [default: ~/segmentation]
      • output/pointcloud/visualization [default: ~/visualization]
      • output/pointcloud/filtered [default: ~/filtered]
      • data_path [default: $(env HOME)/autoware_data]
      • model_name [default: ptv3]
      • model_path [default: $(var data_path)/ptv3]
      • model_param_path [default: $(find-pkg-share autoware_ptv3)/config/$(var model_name).param.yaml]
      • ml_package_param_path [default: $(var model_path)/ml_package_$(var model_name).param.yaml]
      • class_remapper_param_path [default: $(var model_path)/detection_class_remapper.param.yaml]
      • build_only [default: false]
      • log_level [default: info]
      • use_pointcloud_container [default: false]
      • pointcloud_container_name [default: pointcloud_container]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged autoware_ptv3 at Robotics Stack Exchange

Package symbol

autoware_ptv3 package from autoware_universe repo

autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_designs autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_spheric_collision_detector autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_tensorrt_vad autoware_control_evaluator autoware_evaluation_adapter autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_camera_streampetr autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_ground_segmentation_cuda autoware_image_object_locator autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_frnet autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_sorter autoware_occupancy_grid_map_outlier_filter autoware_predicted_path_postprocessor autoware_probabilistic_occupancy_grid_map autoware_ptv3 autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_bevformer autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_manual_lane_change_handler autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_trajectory_adapter autoware_trajectory_concatenator autoware_trajectory_modifier autoware_trajectory_optimizer autoware_trajectory_ranker autoware_trajectory_validator autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module 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 autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_manual_lane_change_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

ROS Distro
github

API Docs
Browse Code

Package Summary

Version 0.50.0
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 2026-04-07
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_ptv3 package

Maintainers

  • Kenzo Lobos-Tsunekawa
  • Amadeusz Szymko
  • Manato Hirabayashi

Authors

No additional authors.
perception/autoware_ptv3/README.md

autoware_ptv3

Purpose

The autoware_ptv3 package is used for 3D lidar segmentation.

Inner-workings / Algorithms

This package implements a TensorRT powered inference node for Point Transformers V3 (PTv3) [1]. The sparse convolution backend corresponds to spconv. Autoware installs it automatically in its setup script. If needed, the user can also build it and install it following the following instructions.

Inputs / Outputs

Input

Name Type Description
~/input/pointcloud sensor_msgs::msg::PointCloud2 Input pointcloud topic.

Output

Name Type Description
~/output/pointcloud/segmentation sensor_msgs::msg::PointCloud2 XYZ cloud with class ID and probability fields.
~/output/pointcloud/visualization sensor_msgs::msg::PointCloud2 XYZ cloud with RGB field.
~/output/pointcloud/filtered sensor_msgs::msg::PointCloud2 Filtered cloud in the requested filter.output_format.
debug/cyclic_time_ms autoware_internal_debug_msgs::msg::Float64Stamped Cyclic time (ms).
debug/pipeline_latency_ms autoware_internal_debug_msgs::msg::Float64Stamped Pipeline latency time (ms).
debug/processing_time/preprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Preprocess (ms).
debug/processing_time/inference_ms autoware_internal_debug_msgs::msg::Float64Stamped Inference time (ms).
debug/processing_time/postprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Postprocess time (ms).
debug/processing_time/total_ms autoware_internal_debug_msgs::msg::Float64Stamped Total processing time (ms).

Parameters

PTv3Node node

{{ json_to_markdown(“perception/autoware_ptv3/schema/ptv3.schema.json”) }}

PTv3Node model

{{ json_to_markdown(“perception/autoware_ptv3/schema/ml_package_ptv3.schema.json”) }}

filter.* parameters are configured in config/ptv3.param.yaml, while class metadata and the visualization palette are configured in config/ml_package_ptv3.param.yaml.

The build_only option

The autoware_ptv3 node has a build_only option to build the TensorRT engine file from the specified ONNX file, after which the program exits.

ros2 launch autoware_ptv3 ptv3.launch.xml build_only:=true

The log_level option

The default logging severity level for autoware_ptv3 is info. For debugging purposes, the developer may decrease severity level using log_level parameter:

ros2 launch autoware_ptv3 ptv3.launch.xml log_level:=debug

Assumptions / Known limits

This node detects the input pointcloud format automatically on the first received message and supports:

  • XYZIRCAEDT (10 fields)
  • XYZIRADRT (9 fields)
  • XYZIRC (6 fields)
  • XYZI (4 fields)

The filtered output cloud format is controlled by filter.output_format. When it is set to an empty string, the filtered output preserves the same format as the input cloud.

Trained Models

The model was trained on the T4Dataset using approximately 4,000 frames and is available in the Autoware artifacts.

Troubleshooting

Fail to create host memory

This error may occur when the system runs out of memory during TensorRT engine building. To mitigate this issue, consider reducing the voxels_num maximum limit in the model parameters, which controls the maximum number of voxels processed by the model. For the instance, using GPU with 8 GB of memory, setting maximum voxels_num to 192’000 may help to avoid this error.

[1] Xiaoyang Wu, Li Jiang, Peng-Shuai Wang, Zhijian Liu, Xihui Liu, Yu Qiao, Wanli Ouyang, Tong He, and Hengshuang Zhao. “Point Transformer V3: Simpler, Faster, Stronger.” 2024 Conference on Computer Vision and Pattern Recognition.

CHANGELOG

Changelog for package autoware_ptv3

0.50.0 (2026-02-14)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): update nvcc flags (#12053)

  • chore(autoware_ptv3): remove cudnn dependency (#11894)

  • chore: add maintainer of PTv3, FRNet, and CalibrationStatusClassifier (#11945)

    • chore: update [autoware_ptv3]{.title-ref} maintainer
    • chore: update [autoware_lidar_frnet]{.title-ref} maintainer

    * chore: update [autoware_calibration_status_classifier]{.title-ref} maintainer ---------

  • Contributors: Amadeusz Szymko, Manato Hirabayashi, Ryohsuke Mitsudome

0.49.0 (2025-12-30)

0.48.0 (2025-11-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): implemented an inference node for ptv3 using tensorrt (#10600)

    • feat: implemented an inference node for ptv3 using tensorrt
    • chore: cspells
    • chore: schemas
    • chore: lint (line was too long)
    • chore: more schemas
    • fix: mistook the compute capabilities of edge devices
    • chore: replaced incorrect bevfusion -> ptv3
    • chore: forgot to remove unused schema
    • chore: duplicated variable
    • chore: changed package dep name
    • chore: fixed schema comment
    • chore: removed unused headers in the post process kernels
    • chore: replaced in favor of auto
    • chore: removed unused headers
    • chore: changed initialization order
    • chore: replaced 0 by nullptr
    • chore: replaced type in favor of auto
    • chore: removed redundant message
    • chore: fixed compilation due to review changes
    • fix: replaced int64 by uint64
    • chore: added more descriptive comment in the schema

    * style(autoware_ptv3): cleanup ---------Co-authored-by: Amadeusz Szymko <<amadeusz.szymko.2@tier4.jp>>

  • Contributors: Kenzo Lobos Tsunekawa, Ryohsuke Mitsudome

Launch files

  • launch/ptv3.launch.xml
      • input/pointcloud [default: /sensing/lidar/concatenated/pointcloud]
      • output/pointcloud/segmentation [default: ~/segmentation]
      • output/pointcloud/visualization [default: ~/visualization]
      • output/pointcloud/filtered [default: ~/filtered]
      • data_path [default: $(env HOME)/autoware_data]
      • model_name [default: ptv3]
      • model_path [default: $(var data_path)/ptv3]
      • model_param_path [default: $(find-pkg-share autoware_ptv3)/config/$(var model_name).param.yaml]
      • ml_package_param_path [default: $(var model_path)/ml_package_$(var model_name).param.yaml]
      • class_remapper_param_path [default: $(var model_path)/detection_class_remapper.param.yaml]
      • build_only [default: false]
      • log_level [default: info]
      • use_pointcloud_container [default: false]
      • pointcloud_container_name [default: pointcloud_container]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged autoware_ptv3 at Robotics Stack Exchange

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autoware_ptv3 package from autoware_universe repo

autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_designs autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_spheric_collision_detector autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_tensorrt_vad autoware_control_evaluator autoware_evaluation_adapter autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_camera_streampetr autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_ground_segmentation_cuda autoware_image_object_locator autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_frnet autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_sorter autoware_occupancy_grid_map_outlier_filter autoware_predicted_path_postprocessor autoware_probabilistic_occupancy_grid_map autoware_ptv3 autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_bevformer autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_manual_lane_change_handler autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_trajectory_adapter autoware_trajectory_concatenator autoware_trajectory_modifier autoware_trajectory_optimizer autoware_trajectory_ranker autoware_trajectory_validator autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module 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 autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_manual_lane_change_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

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Package Summary

Version 0.50.0
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 2026-04-07
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_ptv3 package

Maintainers

  • Kenzo Lobos-Tsunekawa
  • Amadeusz Szymko
  • Manato Hirabayashi

Authors

No additional authors.
perception/autoware_ptv3/README.md

autoware_ptv3

Purpose

The autoware_ptv3 package is used for 3D lidar segmentation.

Inner-workings / Algorithms

This package implements a TensorRT powered inference node for Point Transformers V3 (PTv3) [1]. The sparse convolution backend corresponds to spconv. Autoware installs it automatically in its setup script. If needed, the user can also build it and install it following the following instructions.

Inputs / Outputs

Input

Name Type Description
~/input/pointcloud sensor_msgs::msg::PointCloud2 Input pointcloud topic.

Output

Name Type Description
~/output/pointcloud/segmentation sensor_msgs::msg::PointCloud2 XYZ cloud with class ID and probability fields.
~/output/pointcloud/visualization sensor_msgs::msg::PointCloud2 XYZ cloud with RGB field.
~/output/pointcloud/filtered sensor_msgs::msg::PointCloud2 Filtered cloud in the requested filter.output_format.
debug/cyclic_time_ms autoware_internal_debug_msgs::msg::Float64Stamped Cyclic time (ms).
debug/pipeline_latency_ms autoware_internal_debug_msgs::msg::Float64Stamped Pipeline latency time (ms).
debug/processing_time/preprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Preprocess (ms).
debug/processing_time/inference_ms autoware_internal_debug_msgs::msg::Float64Stamped Inference time (ms).
debug/processing_time/postprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Postprocess time (ms).
debug/processing_time/total_ms autoware_internal_debug_msgs::msg::Float64Stamped Total processing time (ms).

Parameters

PTv3Node node

{{ json_to_markdown(“perception/autoware_ptv3/schema/ptv3.schema.json”) }}

PTv3Node model

{{ json_to_markdown(“perception/autoware_ptv3/schema/ml_package_ptv3.schema.json”) }}

filter.* parameters are configured in config/ptv3.param.yaml, while class metadata and the visualization palette are configured in config/ml_package_ptv3.param.yaml.

The build_only option

The autoware_ptv3 node has a build_only option to build the TensorRT engine file from the specified ONNX file, after which the program exits.

ros2 launch autoware_ptv3 ptv3.launch.xml build_only:=true

The log_level option

The default logging severity level for autoware_ptv3 is info. For debugging purposes, the developer may decrease severity level using log_level parameter:

ros2 launch autoware_ptv3 ptv3.launch.xml log_level:=debug

Assumptions / Known limits

This node detects the input pointcloud format automatically on the first received message and supports:

  • XYZIRCAEDT (10 fields)
  • XYZIRADRT (9 fields)
  • XYZIRC (6 fields)
  • XYZI (4 fields)

The filtered output cloud format is controlled by filter.output_format. When it is set to an empty string, the filtered output preserves the same format as the input cloud.

Trained Models

The model was trained on the T4Dataset using approximately 4,000 frames and is available in the Autoware artifacts.

Troubleshooting

Fail to create host memory

This error may occur when the system runs out of memory during TensorRT engine building. To mitigate this issue, consider reducing the voxels_num maximum limit in the model parameters, which controls the maximum number of voxels processed by the model. For the instance, using GPU with 8 GB of memory, setting maximum voxels_num to 192’000 may help to avoid this error.

[1] Xiaoyang Wu, Li Jiang, Peng-Shuai Wang, Zhijian Liu, Xihui Liu, Yu Qiao, Wanli Ouyang, Tong He, and Hengshuang Zhao. “Point Transformer V3: Simpler, Faster, Stronger.” 2024 Conference on Computer Vision and Pattern Recognition.

CHANGELOG

Changelog for package autoware_ptv3

0.50.0 (2026-02-14)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): update nvcc flags (#12053)

  • chore(autoware_ptv3): remove cudnn dependency (#11894)

  • chore: add maintainer of PTv3, FRNet, and CalibrationStatusClassifier (#11945)

    • chore: update [autoware_ptv3]{.title-ref} maintainer
    • chore: update [autoware_lidar_frnet]{.title-ref} maintainer

    * chore: update [autoware_calibration_status_classifier]{.title-ref} maintainer ---------

  • Contributors: Amadeusz Szymko, Manato Hirabayashi, Ryohsuke Mitsudome

0.49.0 (2025-12-30)

0.48.0 (2025-11-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): implemented an inference node for ptv3 using tensorrt (#10600)

    • feat: implemented an inference node for ptv3 using tensorrt
    • chore: cspells
    • chore: schemas
    • chore: lint (line was too long)
    • chore: more schemas
    • fix: mistook the compute capabilities of edge devices
    • chore: replaced incorrect bevfusion -> ptv3
    • chore: forgot to remove unused schema
    • chore: duplicated variable
    • chore: changed package dep name
    • chore: fixed schema comment
    • chore: removed unused headers in the post process kernels
    • chore: replaced in favor of auto
    • chore: removed unused headers
    • chore: changed initialization order
    • chore: replaced 0 by nullptr
    • chore: replaced type in favor of auto
    • chore: removed redundant message
    • chore: fixed compilation due to review changes
    • fix: replaced int64 by uint64
    • chore: added more descriptive comment in the schema

    * style(autoware_ptv3): cleanup ---------Co-authored-by: Amadeusz Szymko <<amadeusz.szymko.2@tier4.jp>>

  • Contributors: Kenzo Lobos Tsunekawa, Ryohsuke Mitsudome

Launch files

  • launch/ptv3.launch.xml
      • input/pointcloud [default: /sensing/lidar/concatenated/pointcloud]
      • output/pointcloud/segmentation [default: ~/segmentation]
      • output/pointcloud/visualization [default: ~/visualization]
      • output/pointcloud/filtered [default: ~/filtered]
      • data_path [default: $(env HOME)/autoware_data]
      • model_name [default: ptv3]
      • model_path [default: $(var data_path)/ptv3]
      • model_param_path [default: $(find-pkg-share autoware_ptv3)/config/$(var model_name).param.yaml]
      • ml_package_param_path [default: $(var model_path)/ml_package_$(var model_name).param.yaml]
      • class_remapper_param_path [default: $(var model_path)/detection_class_remapper.param.yaml]
      • build_only [default: false]
      • log_level [default: info]
      • use_pointcloud_container [default: false]
      • pointcloud_container_name [default: pointcloud_container]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged autoware_ptv3 at Robotics Stack Exchange

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Package symbol

autoware_ptv3 package from autoware_universe repo

autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_designs autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_spheric_collision_detector autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_tensorrt_vad autoware_control_evaluator autoware_evaluation_adapter autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_camera_streampetr autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_ground_segmentation_cuda autoware_image_object_locator autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_frnet autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_sorter autoware_occupancy_grid_map_outlier_filter autoware_predicted_path_postprocessor autoware_probabilistic_occupancy_grid_map autoware_ptv3 autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_bevformer autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_manual_lane_change_handler autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_trajectory_adapter autoware_trajectory_concatenator autoware_trajectory_modifier autoware_trajectory_optimizer autoware_trajectory_ranker autoware_trajectory_validator autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module 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 autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_manual_lane_change_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

ROS Distro
github

API Docs
Browse Code

Package Summary

Version 0.50.0
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 2026-04-07
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_ptv3 package

Maintainers

  • Kenzo Lobos-Tsunekawa
  • Amadeusz Szymko
  • Manato Hirabayashi

Authors

No additional authors.
perception/autoware_ptv3/README.md

autoware_ptv3

Purpose

The autoware_ptv3 package is used for 3D lidar segmentation.

Inner-workings / Algorithms

This package implements a TensorRT powered inference node for Point Transformers V3 (PTv3) [1]. The sparse convolution backend corresponds to spconv. Autoware installs it automatically in its setup script. If needed, the user can also build it and install it following the following instructions.

Inputs / Outputs

Input

Name Type Description
~/input/pointcloud sensor_msgs::msg::PointCloud2 Input pointcloud topic.

Output

Name Type Description
~/output/pointcloud/segmentation sensor_msgs::msg::PointCloud2 XYZ cloud with class ID and probability fields.
~/output/pointcloud/visualization sensor_msgs::msg::PointCloud2 XYZ cloud with RGB field.
~/output/pointcloud/filtered sensor_msgs::msg::PointCloud2 Filtered cloud in the requested filter.output_format.
debug/cyclic_time_ms autoware_internal_debug_msgs::msg::Float64Stamped Cyclic time (ms).
debug/pipeline_latency_ms autoware_internal_debug_msgs::msg::Float64Stamped Pipeline latency time (ms).
debug/processing_time/preprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Preprocess (ms).
debug/processing_time/inference_ms autoware_internal_debug_msgs::msg::Float64Stamped Inference time (ms).
debug/processing_time/postprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Postprocess time (ms).
debug/processing_time/total_ms autoware_internal_debug_msgs::msg::Float64Stamped Total processing time (ms).

Parameters

PTv3Node node

{{ json_to_markdown(“perception/autoware_ptv3/schema/ptv3.schema.json”) }}

PTv3Node model

{{ json_to_markdown(“perception/autoware_ptv3/schema/ml_package_ptv3.schema.json”) }}

filter.* parameters are configured in config/ptv3.param.yaml, while class metadata and the visualization palette are configured in config/ml_package_ptv3.param.yaml.

The build_only option

The autoware_ptv3 node has a build_only option to build the TensorRT engine file from the specified ONNX file, after which the program exits.

ros2 launch autoware_ptv3 ptv3.launch.xml build_only:=true

The log_level option

The default logging severity level for autoware_ptv3 is info. For debugging purposes, the developer may decrease severity level using log_level parameter:

ros2 launch autoware_ptv3 ptv3.launch.xml log_level:=debug

Assumptions / Known limits

This node detects the input pointcloud format automatically on the first received message and supports:

  • XYZIRCAEDT (10 fields)
  • XYZIRADRT (9 fields)
  • XYZIRC (6 fields)
  • XYZI (4 fields)

The filtered output cloud format is controlled by filter.output_format. When it is set to an empty string, the filtered output preserves the same format as the input cloud.

Trained Models

The model was trained on the T4Dataset using approximately 4,000 frames and is available in the Autoware artifacts.

Troubleshooting

Fail to create host memory

This error may occur when the system runs out of memory during TensorRT engine building. To mitigate this issue, consider reducing the voxels_num maximum limit in the model parameters, which controls the maximum number of voxels processed by the model. For the instance, using GPU with 8 GB of memory, setting maximum voxels_num to 192’000 may help to avoid this error.

[1] Xiaoyang Wu, Li Jiang, Peng-Shuai Wang, Zhijian Liu, Xihui Liu, Yu Qiao, Wanli Ouyang, Tong He, and Hengshuang Zhao. “Point Transformer V3: Simpler, Faster, Stronger.” 2024 Conference on Computer Vision and Pattern Recognition.

CHANGELOG

Changelog for package autoware_ptv3

0.50.0 (2026-02-14)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): update nvcc flags (#12053)

  • chore(autoware_ptv3): remove cudnn dependency (#11894)

  • chore: add maintainer of PTv3, FRNet, and CalibrationStatusClassifier (#11945)

    • chore: update [autoware_ptv3]{.title-ref} maintainer
    • chore: update [autoware_lidar_frnet]{.title-ref} maintainer

    * chore: update [autoware_calibration_status_classifier]{.title-ref} maintainer ---------

  • Contributors: Amadeusz Szymko, Manato Hirabayashi, Ryohsuke Mitsudome

0.49.0 (2025-12-30)

0.48.0 (2025-11-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): implemented an inference node for ptv3 using tensorrt (#10600)

    • feat: implemented an inference node for ptv3 using tensorrt
    • chore: cspells
    • chore: schemas
    • chore: lint (line was too long)
    • chore: more schemas
    • fix: mistook the compute capabilities of edge devices
    • chore: replaced incorrect bevfusion -> ptv3
    • chore: forgot to remove unused schema
    • chore: duplicated variable
    • chore: changed package dep name
    • chore: fixed schema comment
    • chore: removed unused headers in the post process kernels
    • chore: replaced in favor of auto
    • chore: removed unused headers
    • chore: changed initialization order
    • chore: replaced 0 by nullptr
    • chore: replaced type in favor of auto
    • chore: removed redundant message
    • chore: fixed compilation due to review changes
    • fix: replaced int64 by uint64
    • chore: added more descriptive comment in the schema

    * style(autoware_ptv3): cleanup ---------Co-authored-by: Amadeusz Szymko <<amadeusz.szymko.2@tier4.jp>>

  • Contributors: Kenzo Lobos Tsunekawa, Ryohsuke Mitsudome

Launch files

  • launch/ptv3.launch.xml
      • input/pointcloud [default: /sensing/lidar/concatenated/pointcloud]
      • output/pointcloud/segmentation [default: ~/segmentation]
      • output/pointcloud/visualization [default: ~/visualization]
      • output/pointcloud/filtered [default: ~/filtered]
      • data_path [default: $(env HOME)/autoware_data]
      • model_name [default: ptv3]
      • model_path [default: $(var data_path)/ptv3]
      • model_param_path [default: $(find-pkg-share autoware_ptv3)/config/$(var model_name).param.yaml]
      • ml_package_param_path [default: $(var model_path)/ml_package_$(var model_name).param.yaml]
      • class_remapper_param_path [default: $(var model_path)/detection_class_remapper.param.yaml]
      • build_only [default: false]
      • log_level [default: info]
      • use_pointcloud_container [default: false]
      • pointcloud_container_name [default: pointcloud_container]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged autoware_ptv3 at Robotics Stack Exchange

No version for distro melodic showing github. Known supported distros are highlighted in the buttons above.
Package symbol

autoware_ptv3 package from autoware_universe repo

autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_designs autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_spheric_collision_detector autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_tensorrt_vad autoware_control_evaluator autoware_evaluation_adapter autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_camera_streampetr autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_ground_segmentation_cuda autoware_image_object_locator autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_frnet autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_sorter autoware_occupancy_grid_map_outlier_filter autoware_predicted_path_postprocessor autoware_probabilistic_occupancy_grid_map autoware_ptv3 autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_bevformer autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_manual_lane_change_handler autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_trajectory_adapter autoware_trajectory_concatenator autoware_trajectory_modifier autoware_trajectory_optimizer autoware_trajectory_ranker autoware_trajectory_validator autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module 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 autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_manual_lane_change_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

ROS Distro
github

API Docs
Browse Code
Wiki

Package Summary

Version 0.50.0
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 2026-04-07
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_ptv3 package

Maintainers

  • Kenzo Lobos-Tsunekawa
  • Amadeusz Szymko
  • Manato Hirabayashi

Authors

No additional authors.
perception/autoware_ptv3/README.md

autoware_ptv3

Purpose

The autoware_ptv3 package is used for 3D lidar segmentation.

Inner-workings / Algorithms

This package implements a TensorRT powered inference node for Point Transformers V3 (PTv3) [1]. The sparse convolution backend corresponds to spconv. Autoware installs it automatically in its setup script. If needed, the user can also build it and install it following the following instructions.

Inputs / Outputs

Input

Name Type Description
~/input/pointcloud sensor_msgs::msg::PointCloud2 Input pointcloud topic.

Output

Name Type Description
~/output/pointcloud/segmentation sensor_msgs::msg::PointCloud2 XYZ cloud with class ID and probability fields.
~/output/pointcloud/visualization sensor_msgs::msg::PointCloud2 XYZ cloud with RGB field.
~/output/pointcloud/filtered sensor_msgs::msg::PointCloud2 Filtered cloud in the requested filter.output_format.
debug/cyclic_time_ms autoware_internal_debug_msgs::msg::Float64Stamped Cyclic time (ms).
debug/pipeline_latency_ms autoware_internal_debug_msgs::msg::Float64Stamped Pipeline latency time (ms).
debug/processing_time/preprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Preprocess (ms).
debug/processing_time/inference_ms autoware_internal_debug_msgs::msg::Float64Stamped Inference time (ms).
debug/processing_time/postprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Postprocess time (ms).
debug/processing_time/total_ms autoware_internal_debug_msgs::msg::Float64Stamped Total processing time (ms).

Parameters

PTv3Node node

{{ json_to_markdown(“perception/autoware_ptv3/schema/ptv3.schema.json”) }}

PTv3Node model

{{ json_to_markdown(“perception/autoware_ptv3/schema/ml_package_ptv3.schema.json”) }}

filter.* parameters are configured in config/ptv3.param.yaml, while class metadata and the visualization palette are configured in config/ml_package_ptv3.param.yaml.

The build_only option

The autoware_ptv3 node has a build_only option to build the TensorRT engine file from the specified ONNX file, after which the program exits.

ros2 launch autoware_ptv3 ptv3.launch.xml build_only:=true

The log_level option

The default logging severity level for autoware_ptv3 is info. For debugging purposes, the developer may decrease severity level using log_level parameter:

ros2 launch autoware_ptv3 ptv3.launch.xml log_level:=debug

Assumptions / Known limits

This node detects the input pointcloud format automatically on the first received message and supports:

  • XYZIRCAEDT (10 fields)
  • XYZIRADRT (9 fields)
  • XYZIRC (6 fields)
  • XYZI (4 fields)

The filtered output cloud format is controlled by filter.output_format. When it is set to an empty string, the filtered output preserves the same format as the input cloud.

Trained Models

The model was trained on the T4Dataset using approximately 4,000 frames and is available in the Autoware artifacts.

Troubleshooting

Fail to create host memory

This error may occur when the system runs out of memory during TensorRT engine building. To mitigate this issue, consider reducing the voxels_num maximum limit in the model parameters, which controls the maximum number of voxels processed by the model. For the instance, using GPU with 8 GB of memory, setting maximum voxels_num to 192’000 may help to avoid this error.

[1] Xiaoyang Wu, Li Jiang, Peng-Shuai Wang, Zhijian Liu, Xihui Liu, Yu Qiao, Wanli Ouyang, Tong He, and Hengshuang Zhao. “Point Transformer V3: Simpler, Faster, Stronger.” 2024 Conference on Computer Vision and Pattern Recognition.

CHANGELOG

Changelog for package autoware_ptv3

0.50.0 (2026-02-14)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): update nvcc flags (#12053)

  • chore(autoware_ptv3): remove cudnn dependency (#11894)

  • chore: add maintainer of PTv3, FRNet, and CalibrationStatusClassifier (#11945)

    • chore: update [autoware_ptv3]{.title-ref} maintainer
    • chore: update [autoware_lidar_frnet]{.title-ref} maintainer

    * chore: update [autoware_calibration_status_classifier]{.title-ref} maintainer ---------

  • Contributors: Amadeusz Szymko, Manato Hirabayashi, Ryohsuke Mitsudome

0.49.0 (2025-12-30)

0.48.0 (2025-11-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): implemented an inference node for ptv3 using tensorrt (#10600)

    • feat: implemented an inference node for ptv3 using tensorrt
    • chore: cspells
    • chore: schemas
    • chore: lint (line was too long)
    • chore: more schemas
    • fix: mistook the compute capabilities of edge devices
    • chore: replaced incorrect bevfusion -> ptv3
    • chore: forgot to remove unused schema
    • chore: duplicated variable
    • chore: changed package dep name
    • chore: fixed schema comment
    • chore: removed unused headers in the post process kernels
    • chore: replaced in favor of auto
    • chore: removed unused headers
    • chore: changed initialization order
    • chore: replaced 0 by nullptr
    • chore: replaced type in favor of auto
    • chore: removed redundant message
    • chore: fixed compilation due to review changes
    • fix: replaced int64 by uint64
    • chore: added more descriptive comment in the schema

    * style(autoware_ptv3): cleanup ---------Co-authored-by: Amadeusz Szymko <<amadeusz.szymko.2@tier4.jp>>

  • Contributors: Kenzo Lobos Tsunekawa, Ryohsuke Mitsudome

Launch files

  • launch/ptv3.launch.xml
      • input/pointcloud [default: /sensing/lidar/concatenated/pointcloud]
      • output/pointcloud/segmentation [default: ~/segmentation]
      • output/pointcloud/visualization [default: ~/visualization]
      • output/pointcloud/filtered [default: ~/filtered]
      • data_path [default: $(env HOME)/autoware_data]
      • model_name [default: ptv3]
      • model_path [default: $(var data_path)/ptv3]
      • model_param_path [default: $(find-pkg-share autoware_ptv3)/config/$(var model_name).param.yaml]
      • ml_package_param_path [default: $(var model_path)/ml_package_$(var model_name).param.yaml]
      • class_remapper_param_path [default: $(var model_path)/detection_class_remapper.param.yaml]
      • build_only [default: false]
      • log_level [default: info]
      • use_pointcloud_container [default: false]
      • pointcloud_container_name [default: pointcloud_container]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged autoware_ptv3 at Robotics Stack Exchange

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autoware_ptv3 package from autoware_universe repo

autoware_boundary_departure_checker autoware_component_interface_specs_universe autoware_component_interface_tools autoware_component_interface_utils autoware_cuda_dependency_meta autoware_fake_test_node autoware_glog_component autoware_goal_distance_calculator autoware_grid_map_utils autoware_path_distance_calculator autoware_polar_grid autoware_time_utils autoware_traffic_light_recognition_marker_publisher autoware_traffic_light_utils autoware_universe_designs autoware_universe_utils tier4_api_utils autoware_autonomous_emergency_braking autoware_collision_detector autoware_control_command_gate autoware_control_performance_analysis autoware_control_validator autoware_external_cmd_selector autoware_joy_controller autoware_lane_departure_checker autoware_mpc_lateral_controller autoware_obstacle_collision_checker autoware_operation_mode_transition_manager autoware_pid_longitudinal_controller autoware_predicted_path_checker autoware_pure_pursuit autoware_shift_decider autoware_smart_mpc_trajectory_follower autoware_spheric_collision_detector autoware_stop_mode_operator autoware_trajectory_follower_base autoware_trajectory_follower_node autoware_vehicle_cmd_gate autoware_tensorrt_vad autoware_control_evaluator autoware_evaluation_adapter autoware_kinematic_evaluator autoware_localization_evaluator autoware_perception_online_evaluator autoware_planning_evaluator autoware_scenario_simulator_v2_adapter autoware_diagnostic_graph_test_examples autoware_geo_pose_projector autoware_ar_tag_based_localizer autoware_landmark_manager autoware_lidar_marker_localizer autoware_localization_error_monitor autoware_pose2twist autoware_pose_covariance_modifier autoware_pose_estimator_arbiter autoware_pose_instability_detector yabloc_common yabloc_image_processing yabloc_monitor yabloc_particle_filter yabloc_pose_initializer autoware_map_tf_generator autoware_bevfusion autoware_bytetrack autoware_camera_streampetr autoware_cluster_merger autoware_compare_map_segmentation autoware_crosswalk_traffic_light_estimator autoware_detected_object_feature_remover autoware_detected_object_validation autoware_detection_by_tracker autoware_elevation_map_loader autoware_euclidean_cluster autoware_ground_segmentation autoware_ground_segmentation_cuda autoware_image_object_locator autoware_image_projection_based_fusion autoware_lidar_apollo_instance_segmentation autoware_lidar_centerpoint autoware_lidar_frnet autoware_lidar_transfusion autoware_map_based_prediction autoware_multi_object_tracker autoware_object_merger autoware_object_sorter autoware_occupancy_grid_map_outlier_filter autoware_predicted_path_postprocessor autoware_probabilistic_occupancy_grid_map autoware_ptv3 autoware_radar_fusion_to_detected_object autoware_radar_object_tracker autoware_radar_tracks_msgs_converter autoware_raindrop_cluster_filter autoware_shape_estimation autoware_simpl_prediction autoware_simple_object_merger autoware_tensorrt_bevdet autoware_tensorrt_bevformer autoware_tensorrt_classifier autoware_tensorrt_common autoware_tensorrt_plugins autoware_tensorrt_yolox autoware_tracking_object_merger autoware_traffic_light_arbiter autoware_traffic_light_category_merger autoware_traffic_light_classifier autoware_traffic_light_fine_detector autoware_traffic_light_map_based_detector autoware_traffic_light_multi_camera_fusion autoware_traffic_light_occlusion_predictor autoware_traffic_light_selector autoware_traffic_light_visualization perception_utils autoware_costmap_generator autoware_diffusion_planner autoware_external_velocity_limit_selector autoware_freespace_planner autoware_freespace_planning_algorithms autoware_hazard_lights_selector autoware_manual_lane_change_handler autoware_mission_planner_universe autoware_path_optimizer autoware_path_smoother autoware_remaining_distance_time_calculator autoware_rtc_interface autoware_scenario_selector autoware_surround_obstacle_checker autoware_trajectory_adapter autoware_trajectory_concatenator autoware_trajectory_modifier autoware_trajectory_optimizer autoware_trajectory_ranker autoware_trajectory_validator autoware_behavior_path_avoidance_by_lane_change_module autoware_behavior_path_bidirectional_traffic_module autoware_behavior_path_dynamic_obstacle_avoidance_module autoware_behavior_path_external_request_lane_change_module autoware_behavior_path_goal_planner_module autoware_behavior_path_lane_change_module autoware_behavior_path_planner autoware_behavior_path_planner_common autoware_behavior_path_sampling_planner_module autoware_behavior_path_side_shift_module autoware_behavior_path_start_planner_module autoware_behavior_path_static_obstacle_avoidance_module autoware_behavior_velocity_blind_spot_module 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 autoware_simple_planning_simulator autoware_vehicle_door_simulator tier4_dummy_object_rviz_plugin autoware_bluetooth_monitor autoware_command_mode_decider autoware_command_mode_decider_plugins autoware_command_mode_switcher autoware_command_mode_switcher_plugins autoware_command_mode_types autoware_component_monitor autoware_component_state_monitor autoware_adapi_visualizers autoware_automatic_pose_initializer autoware_default_adapi_universe autoware_diagnostic_graph_aggregator autoware_diagnostic_graph_utils autoware_dummy_diag_publisher autoware_dummy_infrastructure autoware_duplicated_node_checker autoware_hazard_status_converter autoware_mrm_comfortable_stop_operator autoware_mrm_emergency_stop_operator autoware_mrm_handler autoware_pipeline_latency_monitor autoware_processing_time_checker autoware_system_monitor autoware_topic_relay_controller autoware_topic_state_monitor autoware_velodyne_monitor autoware_accel_brake_map_calibrator autoware_external_cmd_converter autoware_raw_vehicle_cmd_converter autoware_steer_offset_estimator autoware_bag_time_manager_rviz_plugin autoware_traffic_light_rviz_plugin tier4_adapi_rviz_plugin tier4_camera_view_rviz_plugin tier4_control_mode_rviz_plugin tier4_datetime_rviz_plugin tier4_manual_lane_change_rviz_plugin tier4_perception_rviz_plugin tier4_planning_factor_rviz_plugin tier4_state_rviz_plugin tier4_traffic_light_rviz_plugin tier4_vehicle_rviz_plugin

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Package Summary

Version 0.50.0
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 2026-04-07
Dev Status UNKNOWN
Released UNRELEASED
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

The autoware_ptv3 package

Maintainers

  • Kenzo Lobos-Tsunekawa
  • Amadeusz Szymko
  • Manato Hirabayashi

Authors

No additional authors.
perception/autoware_ptv3/README.md

autoware_ptv3

Purpose

The autoware_ptv3 package is used for 3D lidar segmentation.

Inner-workings / Algorithms

This package implements a TensorRT powered inference node for Point Transformers V3 (PTv3) [1]. The sparse convolution backend corresponds to spconv. Autoware installs it automatically in its setup script. If needed, the user can also build it and install it following the following instructions.

Inputs / Outputs

Input

Name Type Description
~/input/pointcloud sensor_msgs::msg::PointCloud2 Input pointcloud topic.

Output

Name Type Description
~/output/pointcloud/segmentation sensor_msgs::msg::PointCloud2 XYZ cloud with class ID and probability fields.
~/output/pointcloud/visualization sensor_msgs::msg::PointCloud2 XYZ cloud with RGB field.
~/output/pointcloud/filtered sensor_msgs::msg::PointCloud2 Filtered cloud in the requested filter.output_format.
debug/cyclic_time_ms autoware_internal_debug_msgs::msg::Float64Stamped Cyclic time (ms).
debug/pipeline_latency_ms autoware_internal_debug_msgs::msg::Float64Stamped Pipeline latency time (ms).
debug/processing_time/preprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Preprocess (ms).
debug/processing_time/inference_ms autoware_internal_debug_msgs::msg::Float64Stamped Inference time (ms).
debug/processing_time/postprocess_ms autoware_internal_debug_msgs::msg::Float64Stamped Postprocess time (ms).
debug/processing_time/total_ms autoware_internal_debug_msgs::msg::Float64Stamped Total processing time (ms).

Parameters

PTv3Node node

{{ json_to_markdown(“perception/autoware_ptv3/schema/ptv3.schema.json”) }}

PTv3Node model

{{ json_to_markdown(“perception/autoware_ptv3/schema/ml_package_ptv3.schema.json”) }}

filter.* parameters are configured in config/ptv3.param.yaml, while class metadata and the visualization palette are configured in config/ml_package_ptv3.param.yaml.

The build_only option

The autoware_ptv3 node has a build_only option to build the TensorRT engine file from the specified ONNX file, after which the program exits.

ros2 launch autoware_ptv3 ptv3.launch.xml build_only:=true

The log_level option

The default logging severity level for autoware_ptv3 is info. For debugging purposes, the developer may decrease severity level using log_level parameter:

ros2 launch autoware_ptv3 ptv3.launch.xml log_level:=debug

Assumptions / Known limits

This node detects the input pointcloud format automatically on the first received message and supports:

  • XYZIRCAEDT (10 fields)
  • XYZIRADRT (9 fields)
  • XYZIRC (6 fields)
  • XYZI (4 fields)

The filtered output cloud format is controlled by filter.output_format. When it is set to an empty string, the filtered output preserves the same format as the input cloud.

Trained Models

The model was trained on the T4Dataset using approximately 4,000 frames and is available in the Autoware artifacts.

Troubleshooting

Fail to create host memory

This error may occur when the system runs out of memory during TensorRT engine building. To mitigate this issue, consider reducing the voxels_num maximum limit in the model parameters, which controls the maximum number of voxels processed by the model. For the instance, using GPU with 8 GB of memory, setting maximum voxels_num to 192’000 may help to avoid this error.

[1] Xiaoyang Wu, Li Jiang, Peng-Shuai Wang, Zhijian Liu, Xihui Liu, Yu Qiao, Wanli Ouyang, Tong He, and Hengshuang Zhao. “Point Transformer V3: Simpler, Faster, Stronger.” 2024 Conference on Computer Vision and Pattern Recognition.

CHANGELOG

Changelog for package autoware_ptv3

0.50.0 (2026-02-14)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): update nvcc flags (#12053)

  • chore(autoware_ptv3): remove cudnn dependency (#11894)

  • chore: add maintainer of PTv3, FRNet, and CalibrationStatusClassifier (#11945)

    • chore: update [autoware_ptv3]{.title-ref} maintainer
    • chore: update [autoware_lidar_frnet]{.title-ref} maintainer

    * chore: update [autoware_calibration_status_classifier]{.title-ref} maintainer ---------

  • Contributors: Amadeusz Szymko, Manato Hirabayashi, Ryohsuke Mitsudome

0.49.0 (2025-12-30)

0.48.0 (2025-11-18)

  • Merge remote-tracking branch 'origin/main' into humble

  • feat(autoware_ptv3): implemented an inference node for ptv3 using tensorrt (#10600)

    • feat: implemented an inference node for ptv3 using tensorrt
    • chore: cspells
    • chore: schemas
    • chore: lint (line was too long)
    • chore: more schemas
    • fix: mistook the compute capabilities of edge devices
    • chore: replaced incorrect bevfusion -> ptv3
    • chore: forgot to remove unused schema
    • chore: duplicated variable
    • chore: changed package dep name
    • chore: fixed schema comment
    • chore: removed unused headers in the post process kernels
    • chore: replaced in favor of auto
    • chore: removed unused headers
    • chore: changed initialization order
    • chore: replaced 0 by nullptr
    • chore: replaced type in favor of auto
    • chore: removed redundant message
    • chore: fixed compilation due to review changes
    • fix: replaced int64 by uint64
    • chore: added more descriptive comment in the schema

    * style(autoware_ptv3): cleanup ---------Co-authored-by: Amadeusz Szymko <<amadeusz.szymko.2@tier4.jp>>

  • Contributors: Kenzo Lobos Tsunekawa, Ryohsuke Mitsudome

Launch files

  • launch/ptv3.launch.xml
      • input/pointcloud [default: /sensing/lidar/concatenated/pointcloud]
      • output/pointcloud/segmentation [default: ~/segmentation]
      • output/pointcloud/visualization [default: ~/visualization]
      • output/pointcloud/filtered [default: ~/filtered]
      • data_path [default: $(env HOME)/autoware_data]
      • model_name [default: ptv3]
      • model_path [default: $(var data_path)/ptv3]
      • model_param_path [default: $(find-pkg-share autoware_ptv3)/config/$(var model_name).param.yaml]
      • ml_package_param_path [default: $(var model_path)/ml_package_$(var model_name).param.yaml]
      • class_remapper_param_path [default: $(var model_path)/detection_class_remapper.param.yaml]
      • build_only [default: false]
      • log_level [default: info]
      • use_pointcloud_container [default: false]
      • pointcloud_container_name [default: pointcloud_container]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

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