tensorrt_bevdet

Purpose

The core algorithm, named BEVDet, it unifies multi-view images into the perspective of BEV for 3D object detection task.

Inner-workings / Algorithms

Cite

• Junjie Huang, Guan Huang, “BEVPoolv2: A Cutting-edge Implementation of BEVDet Toward Deployment”, [ref]
• bevdet_vendor package are copied from the original codes (The TensorRT, C++ implementation by LCH1238) and modified.
• This package is ported version toward Autoware from bevdet_vendor.

Inputs / Outputs

Inputs

Outputs

How to Use Tensorrt BEVDet Node

Prerequisites

• Tensorrt 10.8.0.43
• CUDA 12.4

Trained Models

Download the trained models with the instructions in Autoware artifacts.

The BEVDet model was trained in NuScenes dataset for 20 epochs.

Test Tensorrt BEVDet Node with Nuscenes

1. Integrate this branch changes in your autoware_universe/perception directory

2. Include this bevdet_vendor pr in src/universe/external/bevdet_vendor as this supports fp16 precision and api support for Tensorrt 10.x.x

3. To play ros2 bag of nuScenes data

   cd autoware/src
   git clone https://github.com/Owen-Liuyuxuan/ros2_dataset_bridge
   cd ..

   # Open the launch file to configure dataset settings:

   nano src/ros2_dataset_bridge/launch/nuscenes_launch.xml

   # Update the following lines with the correct NuScenes dataset path and set the publishing frequency to 10 Hz for optimal data streaming:

   <arg name="NUSCENES_DIR" default="<nuscenes_dataset_path>"/>
   <arg name="NUSCENES_VER" default="v1.0-trainval"/>
   <arg name="UPDATE_FREQUENCY" default="10.0"/>

   # Open the ros_utils script:

   nano src/ros2_dataset_bridge/ros2_dataset_bridge/utils/ros_util.py

   # Modify the encoding to bgr8 at line 92:

   image_msg = self.cv_bridge.cv2_to_imgmsg(image, encoding="bgr8")

   

1. Build the autoware_tensorrt_bevdet and ros2_dataset_bridge packages

```bash

# Build autoware_tensorrt_bevdet

colcon build –packages-up-to autoware_tensorrt_bevdet

# Build ros2_dataset_bridge

File truncated at 100 lines see the full file

Changelog for package autoware_tensorrt_bevdet

0.53.0 (2026-09-29)

• Merge remote-tracking branch 'origin/main' into prepare-0.53.0-changelog
• refactor(autoware_universe): use autoware_ament_auto_package in perception DNN packages (#12277) Co-authored-by: github-actions <<github-actions@github.com>> Co-authored-by: Taekjin LEE <<taekjin.lee@tier4.jp>>
• refactor(perception): move node design files into each package (#13104) Co-authored-by: Claude Opus 5 (1M context) <<noreply@anthropic.com>>
• Contributors: Ryohsuke Mitsudome, Taekjin LEE, Vishal Chauhan

0.52.0 (2026-06-30)

0.51.0 (2026-05-01)

• Merge remote-tracking branch 'origin/main' into tmp/bot/bump_version_base

• feat: default artifact paths to ~/autoware_data/ml_models (#12523) feat(launches,configs): default artifact paths to ~/autoware_data/ml_models Roll every per-package [data_path]{.title-ref} / [model_path]{.title-ref} launch-arg default from [$(env HOME)/autoware_data[/...]]{.title-ref} to [$(env HOME)/autoware_data/ml_models[/...]]{.title-ref} so standalone universe launches resolve artifacts under the new [~/autoware_data/ml_models/]{.title-ref} layout (autowarefoundation/autoware#7068). When invoked through autoware_launch the parent overrides cascade and already pin the new root (autowarefoundation/autoware_launch#1835); this commit closes the gap for users who launch a perception / localization / sensing / planning component directly with [ros2 launch <pkg>]{.title-ref}. 22 launch files updated (one-line default change each):

  • e2e/autoware_tensorrt_vad/launch/vad_carla_tiny.launch.xml
  • localization/yabloc/yabloc_pose_initializer/launch/yabloc_pose_initializer.launch.xml
  • perception/autoware_bevfusion/launch/bevfusion.launch.xml
  • perception/autoware_camera_streampetr/launch/streampetr.launch.xml
  • perception/autoware_image_projection_based_fusion/launch/pointpainting_fusion.launch.xml
  • perception/autoware_lidar_apollo_instance_segmentation/launch/lidar_apollo_instance_segmentation.launch.xml
  • perception/autoware_lidar_centerpoint/launch/lidar_centerpoint.launch.xml
  • perception/autoware_lidar_frnet/launch/lidar_frnet.launch.xml
  • perception/autoware_lidar_transfusion/launch/lidar_transfusion.launch.xml
  • perception/autoware_ptv3/launch/ptv3.launch.xml
  • perception/autoware_shape_estimation/launch/shape_estimation.launch.xml
  • perception/autoware_simpl_prediction/launch/simpl.launch.xml
  • perception/autoware_tensorrt_bevdet/launch/tensorrt_bevdet.launch.xml
  • perception/autoware_tensorrt_bevformer/launch/bevformer.launch.xml
  • perception/autoware_tensorrt_yolox/launch/{yolox_traffic_light_detector,yolox_tiny,yolox_s_plus_opt}.launch.xml
  • perception/autoware_traffic_light_classifier/launch/{car,pedestrian}_traffic_light_classifier.launch.xml
  • perception/autoware_traffic_light_fine_detector/launch/traffic_light_fine_detector.launch.xml
  • planning/autoware_diffusion_planner/launch/diffusion_planner.launch.xml

  - sensing/autoware_calibration_status_classifier/launch/calibration_status_classifier.launch.xml Drive-by README and test fixes:

  - e2e/autoware_tensorrt_vad/{README.md,docs/design.md}: also migrate the [$HOME/autoware_map/Town01]{.title-ref} examples to [$HOME/autoware_data/maps/Town01]{.title-ref}.

  - localization/yabloc/{README.md,yabloc_pose_initializer/README.md}: also migrate [$HOME/autoware_map/sample-map-rosbag]{.title-ref} to [$HOME/autoware_data/maps/demos/sample-map-rosbag]{.title-ref}.

  - control/autoware_smart_mpc_trajectory_follower/README.md: migrate the [map_path:=$HOME/autoware_map/sample-map-planning]{.title-ref} example to [$HOME/autoware_data/maps/demos/sample-map-planning]{.title-ref}.

  - simulator/autoware_carla_interface/README.md: migrate every [$HOME/autoware_map/Town01/...]{.title-ref} reference to [$HOME/autoware_data/maps/Town01/...]{.title-ref}.

  • perception/{autoware_bevfusion,autoware_image_projection_based_fusion,autoware_lidar_centerpoint,autoware_tensorrt_bevformer}/README.md: copy-paste examples updated to [~/autoware_data/ml_models/<pkg>]{.title-ref}.
  • perception/autoware_camera_streampetr/config/ml_package_camera_streampetr.param.yaml: header comment updated.
  • planning/autoware_diffusion_planner/README.md: prerequisites snippet updated.

  - sensing/autoware_calibration_status_classifier/test/{test_model_inference,test_calibration_status_classifier}.cpp: hardcoded fallback ONNX path updated. Users on the legacy layout can pin the old root with [data_path:=$HOME/autoware_data]{.title-ref} (or the per-package equivalent) on the command line. Refs: https://github.com/autowarefoundation/autoware/issues/7068

• Contributors: Mete Fatih Cırıt, github-actions

File truncated at 100 lines see the full file