Update README.md

README.md

@@ -73,14 +73,14 @@ Merged_Trajectory: Trajectory data
 
 ### Data Specifications
 
-Attributes
-sim:
+#### Attributes
+##### sim:
 
 False: Real environment data
 
 True: Simulation data
 
-Observations
+##### Observations
 observations/images/: Camera image data
 
 Default camera name: front
@@ -101,14 +101,14 @@ Meaning: Robot end-effector position + quaternion orientation
 
 Order: [Pos X, Pos Y, Pos Z, Q_X, Q_Y, Q_Z, Q_W]
 
-Actions
+##### Actions
 Type: Floating point dataset
 
 Shape: (timesteps, 7)
 
 Meaning: Actions (same structure as qpos, typically mirroring qpos)
 
-Data Conversion
+## Data Conversion
 Supports one-click export to specific formats via web toolchain, or conversion between formats using tools like:
 
 Any4lerobot: GitHub - Tavish9/any4lerobot
@@ -120,55 +120,3 @@ hdf5 → lerobot v3.0
 hdf5 → lerobot(Pi0) v2.0
 
 hdf5 → rlds
-
-Model Performance
-Preliminary experiments show that models trained on this dataset demonstrate significant multi-task generalization capabilities in universal manipulation tasks:
-
-VLA Models: Including PI-O models with language understanding and action planning capabilities, exhibiting excellent generalization and execution stability in multi-task language-conditioned control
-
-VA Models: Classical visual control architectures like ACT, DP also show significant improvements, particularly in complex operation sequences, viewpoint perturbations, and fine motion tracking with enhanced robustness
-
-Related Links
-Project Homepage: https://fastumi.com/pro/
-
-FastUMI Project: https://fastumi.com
-
-Hugging Face Dataset: https://huggingface.co/datasets/IPE...
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-Research Paper: [2409.19499] FastUMI: A Scalable and...
-
-Open Source Toolchain:
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-Demo Replay: GitHub - Loki-Lu/FastUMI_replay_sin...
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-Dual-arm Demo: GitHub - Loki-Lu/FastUMI_replay_du...
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-Hardware SDK: GitHub - FastUMIRobotics/FastUMI_...
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-Monitoring Tools: GitHub - FastUMIRobotics/FastUMI_...
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-Data Collection Tools: GitHub - FastUMIRobotics/FastUMI_...
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-Related Research
-[2508.10538] MLM: Learning Multi-ta...
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-PIO (FastUMI Lightweight Adaptation, Version V0) Full Tutorial: PIO (FastUMI数据轻量级适配，版本V0)…
-
-Citation
-If you use this dataset in your research, please cite the relevant papers:
-
-bibtex
-@article{fastumi2024,
-  title={FastUMI: A Scalable and Hardware-Agnostic Framework for Robot Manipulation Learning},
-  author={FastUMI Team},
-  journal={arXiv preprint},
-  year={2024}
-}
-Contact
-For any questions or suggestions, please contact the development team:
-
-Lead: [Name]
-
-Email: [Email Address]
-
-WeChat: [WeChat ID]