DW05-Robotwin
DW05-Robotwin is a released DW05 world-action model checkpoint for
RobotWin-style robot policy inference and video rollout. It predicts future
robot actions and can generate future robot-view video through the Dexbotic DW05
runtime.
The repository is packaged as a DW05 runtime bundle. Users should point the
runtime to this repository root; they do not need to reproduce upstream model
cache directory names.
What Is Included
The core checkpoint is:
For RobotWin policy inference, the runtime also needs normalization statistics.
The recommended release layout is:
1DW05-Robotwin/
2 model.pt
3 norm_stats.json
If norm_stats.json is not included in a particular release snapshot, provide
the matching RobotWin normalization statistics explicitly through the runtime
--stats / --norm-stats-path argument.
This release is organized as a full offline runtime bundle:
1DW05-Robotwin/
2 model.pt
3 norm_stats.json
4 vae/
5 model.pth
6 text_encoder/
7 model.pth
8 tokenizer/
9 tokenizer_config.json
10 tokenizer.json
11 spiece.model
12 special_tokens_map.json
vae/, text_encoder/, and tokenizer/ are DW05-facing bundle directories.
They contain upstream-compatible runtime components, but the user-facing package
layout remains DW05-owned.
Intended Runtime
Use this checkpoint with the Dexbotic DW05 runtime:
1git clone https://gitlab.dexmal.com/robotics/dexbotic-open.git dexbotic
2cd dexbotic
3pip install -e .
Set the bundle root:
1export DW05_MODEL_BASE_PATH=/path/to/DW05-Robotwin
2export TOKENIZERS_PARALLELISM=false
If norm_stats.json is not placed at the bundle root, pass its path explicitly
with --stats, --norm-stats-path, or the corresponding Dexbotic config field.
Online Demo
Run the RobotWin online demo from the Dexbotic repository:
1python playground/online_demos/robotwin_online_demo.py --web \
2 --ckpt /path/to/DW05-Robotwin/model.pt \
3 --stats /path/to/DW05-Robotwin/norm_stats.json \
4 --model_base_path /path/to/DW05-Robotwin \
5 --device cuda:0 \
6 --num_inference_steps 5
The demo exposes the original interactive RobotWin joint-condition UI and uses
the shared DW05RobotWinPolicy runtime.
Programmatic Policy Loading
1from dexbotic.policy.dw05_policy import DW05RobotWinPolicy, DW05RobotWinPolicyConfig
2
3policy = DW05RobotWinPolicy(
4 DW05RobotWinPolicyConfig(
5 checkpoint_path="/path/to/DW05-Robotwin/model.pt",
6 norm_stats_path="/path/to/DW05-Robotwin/norm_stats.json",
7 model_base_path="/path/to/DW05-Robotwin",
8 device="cuda:0",
9 mixed_precision="bf16",
10 num_inference_steps=5,
11 )
12)
The policy expects RobotWin-style observations with RGB camera images, robot
state, and a natural-language instruction. See the Dexbotic DW05 README for the
complete runtime, evaluation, and deployment examples.
File Notes
model.pt: DW05 trained checkpoint. It contains the DW05 world-action model
parameters used by the released policy, including trained video/action/MoT
weights and the proprio encoder.norm_stats.json: action/state normalization statistics used by RobotWin
policy inference. This is required for action normalization and
denormalization.vae/: local VAE runtime component for image/video latent encoding and
decoding.text_encoder/: local text encoder runtime component for prompt encoding.tokenizer/: local tokenizer files for prompt tokenization.
License And Attribution
This DW05-Robotwin release is distributed under the Apache License 2.0. See
LICENSE for the full license text and
NOTICE for
third-party attribution.
This release is trained from and used with open third-party components,
including Wan2.2, uMT5-compatible tokenizer/text components, and
RoboTwin/RobotWin-style data and evaluation. Those components remain subject to
their own upstream licenses and attribution requirements.
In particular:
- Wan2.2 components are licensed upstream under Apache License 2.0.
- uMT5 tokenizer/text components are licensed upstream under Apache License 2.0.
- RoboTwin code and public dataset metadata were observed under MIT License.
Users who redistribute a modified bundle or include additional third-party files
should preserve the corresponding upstream license and attribution notices.
Limitations
- The checkpoint is released for research and development of world-action
models, robot policy inference, and video rollout experiments.
- Real-robot deployment requires independent safety validation, robustness
evaluation, and environment-specific testing.
- The model expects preprocessing compatible with the Dexbotic DW05 RobotWin
runtime, including image composition, state/action normalization, and prompt
formatting.
- Performance outside RobotWin-style observations and task distributions has not
been guaranteed.
Troubleshooting
Model components are not found.
Set DW05_MODEL_BASE_PATH or pass --model_base_path to the DW05 runtime. The
path should be the root of this DW05 bundle.
Norm stats are missing.
Place norm_stats.json at the bundle root or pass its path explicitly with
--stats / --norm-stats-path.
The online demo starts but generation looks misaligned.
Check that the runtime uses the Dexbotic DW05 preprocessing path: RobotWin image
composition, DW05 normalization statistics, and the matching checkpoint should be
used together.
Citation
If you use DW05-Robotwin, please cite or acknowledge DW05/Dexbotic and the
upstream projects listed in
NOTICE, including Wan2.2, uMT5, and
RoboTwin where applicable.
