Update README.md

README.md

@@ -1,3 +1,62 @@
 ---
 license: cc-by-4.0
----
+pretty_name: RoboMoCap
+tags:
+  - robotics
+  - humanoid
+  - robot-learning
+  - egocentric
+  - whole-body-motion
+  - 3d
+---
+<h1 align="center">RoboMoCap</h1>
+
+<p align="center">A Large-Scale Whole-Body Motion Capture Dataset with Egocentric Vision for Robot Learning</p>
+
+<p align="center">
+  <a href="https://bitrobot-foundation.github.io/robomocap/"><strong>[Website]</strong></a>
+  &nbsp;&nbsp;
+  <strong>[Paper]</strong>
+  &nbsp;&nbsp;
+  <strong>[Code]</strong>
+</p>
+
+**Egocentric vision. High-fidelity whole-body motion.**
+
+RoboMoCap pairs multimodal first-person observations with optical whole-body motion capture for humanoid robot learning. With six head-mounted and two wrist-mounted cameras, the dataset captures diverse locomotion and loco-manipulation behaviours, from everyday walking to dynamic movements and complex object interactions.
+
+**Beyond what egocentric cameras can see.** While many egocentric datasets focus primarily on hand-object interactions, RoboMoCap emphasises locomotion and loco-manipulation. By pairing first-person observations with high-fidelity optical motion capture, it provides accurate supervision for lower-body movement, foot placement, and whole-body coordination during navigation and object interactions.
+
+## Dataset Overview
+
+- **200+ hours** of recording
+- **14** participants
+- **5TB+** of data
+- **290+** captured actions
+
+## Data Modalities
+
+| Modality | Description |
+| --- | --- |
+| **Egocentric sensing ([RoboCap](https://robocap.io/))** | Six head-mounted cameras provide forward, downward, and side views, alongside IMU, magnetometer measurements, and WAV audio. |
+| **Wrist sensing ([RoboWrist](https://robocap.io/))** | Left and right wrist cameras record close-range hand–object interactions, alongside IMU and magnetometer measurements. |
+| **Whole-body motion** | A 53-marker [NOKOV](https://en.nokov.com/) optical mocap setup records whole-body motion at 120 Hz, including leg and foot movement outside the wearable camera views. |
+| **External video** | [NOKOV](https://en.nokov.com/)'s third-person video records the participant, manipulated objects, and the surrounding space. |
+| **Object motion** | Reflective markers track manipulated objects alongside the participant's body motion. |
+| **Object geometry** | Textured 3D scans preserve the shape and appearance of objects used in the recordings. |
+| **Hand pose** | Hand pose complements wrist video to describe hand movements during interaction. |
+
+## License
+
+This dataset is licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
+
+## Citation
+
+If you use this dataset, please cite:
+
+```bibtex
+@misc{robomocap,
+  title = {RoboMoCap: A Large-Scale Whole-Body Motion Capture Dataset with Egocentric Vision for Robot Learning},
+  howpublished = {\url{https://bitrobot-foundation.github.io/robomocap/}}
+}
+```