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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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- <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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  </div>
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@@ -115,15 +117,22 @@ timestamp x y z qx qy qz qw
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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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- 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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- 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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- 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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  <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>
@@ -155,11 +164,12 @@ dataset_root/ \
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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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@@ -181,11 +191,10 @@ export HF_ENDPOINT=https://hf-mirror.com
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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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- 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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  ---
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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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+
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+ <a href="https://fastumi.com/pro/">Project Homepage</a>
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+
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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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+
 
 
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  To ensure correct visualization and control, please adhere to the following frame definition:
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+
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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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+
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+ ### Data Structure
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+
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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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+
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+
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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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+
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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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  ---
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