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ML pipeline for Autoware (a.k.a. AWML)

This repository is a machine learning library to deploy for Autoware to aim for "robotics MLOps". AWML supports training with T4dataset format in addition to open datasets and deployment for Autoware. In addition to ML model deployment, AWML supports active learning framework include auto labeling, semi-auto labeling, and data mining.

AWML can deploy following task for now.

  • 2D detection for dynamic recognition
  • 3D detection for dynamic recognition
  • 2D fine detection for traffic light recognition
  • 2D classification for traffic light recognition

AWML supports following environment.

  • All tools are tested by Docker environment on Ubuntu 22.04LTS
  • NVIDIA dependency: CUDA 12.1 + cuDNN 8
    • Need > 530.xx.xx NVIDIA device driver

The arXiv paper is here. If you use this project in your research, please consider cite.

@misc{tanaka2025awmlopensourcemlbasedrobotics,
      title={AWML: An Open-Source ML-based Robotics Perception Framework to Deploy for ROS-based Autonomous Driving Software},
      author={Satoshi Tanaka and Samrat Thapa and Kok Seang Tan and Amadeusz Szymko and Lobos Kenzo and Koji Minoda and Shintaro Tomie and Kotaro Uetake and Guolong Zhang and Isamu Yamashita and Takamasa Horibe},
      year={2025},
      eprint={2506.00645},
      archivePrefix={arXiv},
      primaryClass={cs.RO},
      url={https://arxiv.org/abs/2506.00645},
}

Docs

Design documents

If you want to know about the design of AWML, you should read following pages.

Contribution

If you want to develop AWML, you should read following pages.

If you want to search the OSS tools around AWML, you should read following pages.

Tips

If you want to know about AWML, you should read following pages.

Release note

Supported tools

Supported pipelines

Supported model

3D detection

3D segmentation

  • Model for Autoware

2D detection

2D segmentation

  • Model for ML tools
    • TBD

2D classification

Vision language

Additional operation

Reference

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