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README.md
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@@ -54,10 +54,12 @@ Small-Scale Demonstration Data from the FastUMI Pro Multimodal Sensing System
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<img src="https://img.shields.io/badge/Multimodal-Vision%20%7C%20Pose%20%7C%20PointCloud-orange" height="15"/>
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</div>
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<a href="https://fastumi.com/pro/">Project Homepage</a>
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<br><br>
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</div>
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| y | Position Y (meters) | qz | Quaternion Z component |
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| z | Position Z (meters) | qw | Quaternion W component |
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Orientation (qx, qy, qz, qw): Rotation quaternion (Scalar-last format).
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2. Coordinate System Reference
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To ensure correct visualization and control, please adhere to the following frame definition:
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<div align="center">
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<small><i>Tip: If using ROS or specific simulators (like Isaac Gym), ensure you apply the necessary transform if your Z-axis convention differs.</i></small>
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</div>
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---
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## 📸 How We Collect Data
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We collect data using the FastUMI Pro hardware suite. This system integrates high-frequency sensors to capture comprehensive multimodal interaction data:
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Visual: Industrial-grade RGB cameras.
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Spatial: Time-of-Flight depth sensors for dense 3D reconstruction.
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Haptic/State: Force-sensitive clamp sensors for precise gripper feedback.
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## ⚠️ Dataset Scale Notice
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[!IMPORTANT]
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This dataset contains **only a small number of sample episodes**
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For full multimodal datasets or enterprise collaborations, please contact the FastUMI team.
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---
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<img src="https://img.shields.io/badge/Multimodal-Vision%20%7C%20Pose%20%7C%20PointCloud-orange" height="15"/>
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</div>
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<img src="https://huggingface.co/datasets/FastUMIPro/example_data_fastumi_pro_raw/resolve/main/4a84995c57de5d63186f923d7a7e06e1.png" alt="FastUMI Pro Hardware System" width="80%" style="border-radius: 10px; box-shadow: 0 4px 8px 0 rgba(0,0,0,0.2);">
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<br><br>
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<a href="https://fastumi.com/pro/">Project Homepage</a>
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</div>
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| y | Position Y (meters) | qz | Quaternion Z component |
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| z | Position Z (meters) | qw | Quaternion W component |
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### Coordinate System Reference
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To ensure correct visualization and control, please adhere to the following frame definition:
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* **Origin (0,0,0):** Geometric center of the tracking base stations (World Frame).
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* 🔴 **X-Axis:** Points **Right** (facing the robot workspace).
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* 🟢 **Y-Axis:** Points **Forward** (main manipulation direction).
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* 🔵 **Z-Axis:** Points **Upward** (aligned with gravity, opposing g).
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### Data Structure
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* **Timestamp:** Unix timestamp (seconds).
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* **Position (x, y, z):** Translation vector in meters.
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* **Orientation (qx, qy, qz, qw):** Rotation quaternion (Scalar-last format).
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<div align="center">
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<small><i>Tip: If using ROS or specific simulators (like Isaac Gym), ensure you apply the necessary transform if your Z-axis convention differs.</i></small>
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</div>
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---
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## 📸 How We Collect Data
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We collect data using the **FastUMI Pro** hardware suite. This system integrates high-frequency sensors to capture comprehensive multimodal interaction data:
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* **Visual:** Industrial-grade RGB cameras.
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* **Spatial:** Time-of-Flight depth sensors for dense 3D reconstruction.
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* **Haptic/State:** Force-sensitive clamp sensors for precise gripper feedback.
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---
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## ⚠️ Dataset Scale Notice
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> [!IMPORTANT]
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> This dataset contains **only a small number of sample episodes** and is **not intended for large-scale training**.
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>
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> For full multimodal datasets or enterprise collaborations, please contact the FastUMI team.
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