Raiden

Raiden is an end-to-end data collection toolkit for YAM robot arms. It covers the full pipeline from hardware setup to policy-ready datasets: camera calibration, teleoperation, multi-camera recording, dataset conversion, and visualization.

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Key features

• Flexible control — leader-follower teleoperation or SpaceMouse end-effector control, in bimanual or single-arm configurations.
• Manipulability-aware IK — uses PyRoki and J-Parse for smooth and singularity-aware control.
• Multiple depth backends — IR structured light (RealSense), ZED SDK stereo, TRI Stereo, and Fast Foundation Stereo for high-quality depth tailored to manipulation scenes.
• Heterogeneous cameras — mix ZED and Intel RealSense cameras freely in a single session, across scene and wrist roles.
• Automated extrinsic calibration — hand-eye calibration for wrist cameras and static extrinsic estimation for scene cameras via ChArUco boards.
• Metadata console — a terminal UI (rd console) for reviewing demonstrations, correcting success/failure labels, and managing tasks and teachers.
• Policy-ready output — converts recordings to a simple, flat file format with synchronized frames, per-frame extrinsics, and interpolated joint poses, ready to plug into policy training frameworks.

Installation

Clone the repository with submodules and install dependencies:

git clone --recurse-submodules git@github.com:TRI-ML/raiden.git
cd raiden
uv sync

ZED cameras — install the ZED SDK, then:

uv run python scripts/install_pyzed.py
uv sync --extra zed

TRI Stereo depth — pull the ONNX model weights via Git LFS:

git lfs install
git lfs pull

Fast Foundation Stereo — foundation model stereo depth:

uv run python scripts/install_ffs.py

Install rd as a shell command:

uv tool install -e .                                                    # base install
uv tool install -e ".[zed]"                                             # + ZED cameras
uv tool install -e ".[zed,tri-stereo]"                                  # + TRI Stereo depth (ONNX)
uv tool install -e ".[zed,tri-stereo,tri-stereo-trt-cu12]"              # + TensorRT (CUDA 12)
uv tool install -e ".[zed,tri-stereo,tri-stereo-trt-cu13]"              # + TensorRT (CUDA 13)

For TensorRT acceleration, see the documentation.

Commands

| Command | Description | |---|---| | rd list_devices | List all connected cameras, arms, and SpaceMouse devices | | rd calibrate | Calibrate cameras (hand-eye + scene extrinsics) | | rd teleop | Teleoperate arms without recording | | rd record | Record teleoperation demonstrations | | rd console | Browse and correct demonstration metadata in a terminal UI | | rd convert | Convert successful recordings to a structured dataset | | rd visualize | Visualize a converted recording with Rerun |

Run rd <command> --help for all options.

Roadmap

The following features are coming soon:

• Fin-ray gripper support — support for fin-ray compliant grippers, which conform to object shapes for robust and gentle grasping.
• Policy training and inference — built-in integration for policy training pipelines and closed-loop inference.

Disclaimer

Raiden is research software provided as-is, without warranty of any kind. Operating robotic arms involves inherent physical risks. The authors and Toyota Research Institute accept no liability for any damage to property, equipment, or persons arising from the use of this software.

Citation

@misc{raiden2026,
  title  = {{RAIDEN}: A Toolkit for Policy Learning with {YAM} Bimanual Robot Arms},
  author = {Iwase, Shun and Miller, Patrick and Yao, Jonathan and Jatavallabhula, {Krishna Murthy} and Zakharov, Sergey},
  year   = {2026},
}