Omega-Prime-ROS

This repository provides a Dockerized ROS 2 conversion pipeline that exports rosbag2 data to omega-prime .mcap files.

The conversion pipeline is based on the perception_interfaces. It scans rosbag2 recordings, reads EgoData and ObjectList topics, and resolves /tf + /tf_static transforms into a configurable fixed frame. The converter writes one .mcap per bag and supports optional OpenDRIVE map embedding and schema validation for downstream analytics workflows.

For further processing of resulting omega-prime files, see the main omega-prime repository.

Requirements

You need to have installed Docker to be able to convert ROS 2 bags to Omega-Prime MCAP files

Usage

Use the Docker image to run the converter automatically. It will discovers rosbag2 folders and writes omega-prime files to the output folder.

1. Build or pull the omega-prime-ros image
2. Mount your ROS bag folder to /input
3. Mount an output directory to /output
4. Optionally mount /map/map.xodr to embed OpenDRIVE map data
5. Set at least one topic (EGO_DATA_TOPIC and/or OBJECT_LIST_TOPIC)
6. Run the container

docker run --rm -it \
    -e EGO_DATA_TOPIC=</your/ego_data_topic> \
    -e OBJECT_LIST_TOPIC=</your/object_list_topic> \
    -v <path/to/bags>:/input \
    -v </path/to/map.xodr>:/map/map.xodr \
    -v "$PWD"/output:/output \
    ghcr.io/ika-rwth-aachen/omega-prime-ros:latest

Example

We provide an examplaric ROS 2 bag file from simulation, which can be used to generate an omega-prime file.

docker run --rm \
    -e EGO_DATA_TOPIC=/simulation/ego_data \
    -e OBJECT_LIST_TOPIC=/simulation/object_list \
    -v "$PWD"/example:/input \
    -v "$PWD"/output:/output \
    ghcr.io/ika-rwth-aachen/omega-prime-ros:latest

The converter writes an .omega-prime.mcap file to the output/ directory.

CLI Description

Environment variables and CLI flags:

• BAG_DIR / --bag-dir (default /input)
• OP_DIR / --op-dir (default /output)
• EGO_DATA_TOPIC / --ego_data_topic
• OBJECT_LIST_TOPIC / --object_list_topic
• FIXED_FRAME / --fixed_frame (default utm_32N)
• MAP / --map (default /map/map.xodr)
• BAG / --bag to process explicit bags (supports comma-separated paths)
• VALIDATE / --validate enable omega-prime schema validation
• WARN_GAP_SECONDS / --warn-gap-seconds warning threshold in seconds if same object ID appears multiple times

Notes

• The converter scans /input for rosbag2 directories containing a metadata.yaml and writes one omega-prime .mcap per bag into /output by default.
• For large bags, ensure sufficient RAM.

Projection Information

• The converter reads /tf and /tf_static and resolves each EgoData and ObjectList message frame against the configured fixed_frame.
• The fixed_frame should be the georeferenced top-level ROS coordinate frame (TF root), for example a global UTM/world frame.
• When fixed_frame=map, the map must be parsed and the map projection string is used.
• These transforms are stored in omega-prime as per-timestamp ProjectionOffset metadata.
• The fixed frame is converted to an EPSG projection string and written as projections["proj_string"].
• Supported fixed_frame values: utm_<zone: int>[N/S] and map (e.g. utm_30N).

Docker Image

The provided image bundles ROS 2 Jazzy, rosbag2 Python bindings, omega-prime, and builds perception_interfaces from GitHub so EgoData and ObjectList topics can be exported to omega-prime MCAP.

Build Args

• OMEGA_PRIME_VERSION (default latest): PyPI version to install
• PERCEPTION_INTERFACES_VERSION (optional): commit/branch/tag; if unset, the repo default branch is used

Local Build

docker build -t ghcr.io/ika-rwth-aachen/omega-prime-ros:latest \
    --build-arg OMEGA_PRIME_VERSION=latest \
    --build-arg PERCEPTION_INTERFACES_VERSION=<commit-or-branch> \
    -f Dockerfile .

Acknowledgements

This package is developed as part of the SYNERGIES project.

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Climate, Infrastructure and Environment Executive Agency (CINEA). Neither the European Union nor the granting authority can be held responsible for them.

Notice

Important

The project is open-sourced and maintained by the Institute for Automotive Engineering (ika) at RWTH Aachen University. We cover a wide variety of research topics within our Vehicle Intelligence & Automated Driving domain. If you would like to learn more about how we can support your automated driving or robotics efforts, feel free to reach out to us! Contact: opensource@ika.rwth-aachen.de