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

autoware_bevfusion package from autoware_universe repo

autoware_agnocast_wrapper autoware_auto_common 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_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_range_splitter autoware_object_sorter autoware_object_velocity_splitter 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_safety_filter autoware_trajectory_traffic_rule_filter 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	2026-02-25
Dev Status	UNKNOWN
Released	UNRELEASED
Contributing	Help Wanted (-) Good First Issues (-) Pull Requests to Review (-)

Package Description

The autoware_bevfusion package

Maintainers

Kenzo Lobos-Tsunekawa
Amadeusz Szymko
Kotaro Uetake
Masato Saeki
Kok Seang Tan

Authors

No additional authors.

perception/autoware_bevfusion/README.md

autoware_bevfusion

Purpose

The autoware_bevfusion package is used for 3D object detection based on lidar or camera-lidar fusion.

Inner-workings / Algorithms

This package implements a TensorRT powered inference node for BEVFusion [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 topics.
`~/input/image*`	`sensor_msgs::msg::Image`	Input image topics.
`~/input/camera_info*`	`sensor_msgs::msg::CameraInfo`	Input camera info topics.

Output

Name	Type	Description
`~/output/objects`	`autoware_perception_msgs::msg::DetectedObjects`	Detected objects.
`debug/cyclic_time_ms`	`tier4_debug_msgs::msg::Float64Stamped`	Cyclic time (ms).
`debug/pipeline_latency_ms`	`tier4_debug_msgs::msg::Float64Stamped`	Pipeline latency time (ms).
`debug/processing_time/preprocess_ms`	`tier4_debug_msgs::msg::Float64Stamped`	Preprocess (ms).
`debug/processing_time/inference_ms`	`tier4_debug_msgs::msg::Float64Stamped`	Inference time (ms).
`debug/processing_time/postprocess_ms`	`tier4_debug_msgs::msg::Float64Stamped`	Postprocess time (ms).
`debug/processing_time/total_ms`	`tier4_debug_msgs::msg::Float64Stamped`	Total processing time (ms).

Parameters

BEVFusion node

{{ json_to_markdown(“perception/autoware_bevfusion/schema/bevfusion.schema.json”) }}

BEVFusion model

{{ json_to_markdown(“perception/autoware_bevfusion/schema/ml_package_bevfusion.schema.json”) }}

Detection class remapper

{{ json_to_markdown(“perception/autoware_bevfusion/schema/detection_class_remapper.schema.json”) }}

The `build_only` option

The autoware_bevfusion 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_bevfusion bevfusion.launch.xml build_only:=true

The `log_level` option

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

ros2 launch autoware_bevfusion bevfusion.launch.xml log_level:=debug

Assumptions / Known limits

This node assumes that the input pointcloud follows the PointXYZIRC layout defined in autoware_point_types.

Trained Models

You can download the onnx and config files in the following links. The files need to be placed inside $(env HOME)/autoware_data/bevfusion

lidar-only model:
- onnx
- config
camera-lidar model:
- onnx
- config
class remapper

The model was trained in TIER IV’s internal database (~35k lidar frames) for 30 epochs.

Changelog

References/External links

[1] Zhijian Liu, Haotian Tang, Alexander Amini, Xinyu Yang, Huizi Mao, Daniela Rus, and Song Han. “BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird’s-Eye View Representation.” 2023 International Conference on Robotics and Automation.

(Optional) Future extensions / Unimplemented parts

Although this node can perform camera-lidar fusion, as it is the first method in autoware to actually use images and lidars for inference, the package structure and its full integration in the autoware pipeline are left for future work. In the current structure, it can be employed without any changes as a lidar-based detector.

CHANGELOG

Changelog for package autoware_bevfusion

0.50.0 (2026-02-14)

Merge remote-tracking branch 'origin/main' into humble
feat(autoware_bevfusion): update nvcc flags (#12045) Co-authored-by: Kotaro Uetake <<60615504+ktro2828@users.noreply.github.com>>
feat(BEVFusion): move cuda stream creation to the beginning of BEVFusionTRT initialization (#11967)
- move cuda stream init before init
* Remove empty lines ---------
fix(bevfusion): suppress -Werror for precomputed_features.cpp (#11959)
fix(autoware_bevfusion): restore spconv in cmakelists (#11953)
chore(autoware_bevfusion): remove cudnn dependency (#11887)
Contributors: Amadeusz Szymko, Kok Seang Tan, Mete Fatih Cırıt, Ryohsuke Mitsudome

0.49.0 (2025-12-30)

Merge remote-tracking branch 'origin/main' into prepare-0.49.0-changelog
feat(autoware_bevfusion): separate image backbone from fusion model and add lidar intensity option (#11468)
- image backbone building
- inference running without error
- working bevfusion-cl
- style(pre-commit): autofix
- removed unnecessary changes
- style(pre-commit): autofix
- made requested changes
- style(pre-commit): autofix
- updated memcopy for img_matrices
- fix parameter names and defaults
- style(pre-commit): autofix
- fixed complile time issues
- refactor pre-process method
- refactored node code
- style(pre-commit): autofix
- refactor init method
- style(pre-commit): autofix
- split node code
- style(pre-commit): autofix
- helper code complexity refactor
- fix lint error
- style(pre-commit): autofix
- update schema params
* suppress clang changes ---------Co-authored-by: pre-commit-ci-lite[bot] <117423508+pre-commit-ci-lite[bot]@users.noreply.github.com>
Contributors: Ryohsuke Mitsudome, Samrat Thapa

0.48.0 (2025-11-18)

0.47.1 (2025-08-14)

0.47.0 (2025-08-11)

style(pre-commit): update to clang-format-20 (#11088) Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Contributors: Mete Fatih Cırıt

0.46.0 (2025-06-20)

Merge remote-tracking branch 'upstream/main' into tmp/TaikiYamada/bump_version_base
fix(autoware_bevfusion): fix clang-tidy errors by removing unused fields (#10850)
- fix clang-tidy errors by removing unused fields
* style(pre-commit): autofix ---------Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
fix(cmake): update spconv availability messages to use STATUS and WAR… (#10690)

File truncated at 100 lines see the full file

Package Dependencies

Deps	Name
	ament_cmake_auto
	autoware_cmake
	autoware_image_transport_decompressor
	autoware_tensorrt_plugins
	ament_cmake_ros
	ament_lint_auto
	autoware_lint_common
	autoware_cuda_dependency_meta
	autoware_cuda_utils
	autoware_object_recognition_utils
	autoware_perception_msgs
	autoware_point_types
	autoware_tensorrt_common
	autoware_universe_utils
	cuda_blackboard
	launch_ros
	pcl_ros
	rclcpp
	rclcpp_components
	tf2_eigen
	tf2_geometry_msgs
	tf2_sensor_msgs

System Dependencies

No direct system dependencies.

Dependant Packages

Name	Deps
tier4_perception_launch

Launch files

launch/bevfusion.launch.xml
- - input/pointcloud [default: /sensing/lidar/concatenated/pointcloud]
  - output/objects [default: objects]
  - data_path [default: $(env HOME)/autoware_data]
  - model_name [default: bevfusion_lidar]
  - model_path [default: $(var data_path)/bevfusion]
  - model_param_path [default: $(find-pkg-share autoware_bevfusion)/config/$(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]
  - common_param_path [default: $(find-pkg-share autoware_bevfusion)/config/common_bevfusion.param.yaml]
  - build_only [default: false]
  - log_level [default: info]
  - use_pointcloud_container [default: false]
  - pointcloud_container_name [default: pointcloud_container]
  - use_decompress [default: false]
  - camera_info0 [default: /sensing/camera/camera0/camera_info]
  - camera_info1 [default: /sensing/camera/camera1/camera_info]
  - camera_info2 [default: /sensing/camera/camera2/camera_info]
  - camera_info3 [default: /sensing/camera/camera3/camera_info]
  - camera_info4 [default: /sensing/camera/camera4/camera_info]
  - camera_info5 [default: /sensing/camera/camera5/camera_info]
  - image0 [default: /sensing/camera/camera0/image_rect_color]
  - image1 [default: /sensing/camera/camera1/image_rect_color]
  - image2 [default: /sensing/camera/camera2/image_rect_color]
  - image3 [default: /sensing/camera/camera3/image_rect_color]
  - image4 [default: /sensing/camera/camera4/image_rect_color]
  - image5 [default: /sensing/camera/camera5/image_rect_color]
  - decompressor_param_file [default: $(find-pkg-share autoware_image_transport_decompressor)/config/image_transport_decompressor.param.yaml]

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged `autoware_bevfusion` at Robotics Stack Exchange

API Docs Browse Code

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