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+<!--
+Open-H Embodiment Dataset README Template (v1.0)
+Please fill out this template and include it in the ./metadata directory of your LeRobot dataset.
+This file helps others understand the context and details of your contribution.
+-->
+
+# [Dataset Name] - README
+
+---
+
+## 📋 At a Glance
+
+*Freehand ultrasound scan trajectory from an expert.*
+
+---
+
+## 📖 Dataset Overview
+
+*This dataset contains 5 trajectories of expert surgeons using the ultrasound probe to scan bones.*
+
+| | |
+| :--- | :--- |
+| **Total Trajectories** | `[5]` |
+| **Total Hours** | `[]` |
+| **Data Type** | `[ ] Clinical` `[✔️] Ex-Vivo` `[ ] Table-Top Phantom` `[ ] Digital Simulation` `[ ] Physical Simulation` `[ ] Other (If checked, update "Other")` |
+| **License** | CC BY 4.0 |
+| **Version** | `[e.g., 1.0]` |
+
+---
+
+## 🎯 Tasks & Domain
+
+### Domain
+
+*Select the primary domain for this dataset.*
+
+- [ ] **Surgical Robotics**
+- [✔️] **Ultrasound Robotics**
+- [ ] **Other Healthcare Robotics** (Please specify: `[Your Domain]`)
+
+### Demonstrated Skills
+
+- Ultrasound scanning
+
+---
+
+## 🔬 Data Collection Details
+
+### Collection Method
+
+*How was the data collected?*
+
+- [ ] **Human Teleoperation**
+- [ ] **Programmatic/State-Machine**
+- [ ] **AI Policy / Autonomous**
+- [ ] **Other** (Please specify: `[Expert freehand]`)
+
+### Operator Details
+
+| | Description |
+| :--- | :--- |
+| **Operator Count** | `[1]` |
+| **Operator Skill Level** | `[✔️] Expert (e.g., Surgeon, Sonographer)` <br> `[ ] Intermediate (e.g., Trained Researcher)` <br> `[ ] Novice (e.g., ML Researcher with minimal experience)` <br> `[ ] N/A` |
+| **Collection Period** | From `[YYYY-MM-DD]` to `[YYYY-MM-DD]` |
+
+### Recovery Demonstrations
+
+*Does this dataset include examples of recovering from failure?*
+
+- [ ] **Yes**
+- [✔️] **No**
+
+**If yes, please briefly describe the recovery process:**
+
+---
+
+## 💡 Diversity Dimensions
+
+*Check all dimensions that were intentionally varied during data collection.*
+
+- [✔️] **Camera Position / Angle**
+- [ ] **Lighting Conditions**
+- [✔️] **Target Object** (e.g., different phantom models, suture types)
+- [ ] **Spatial Layout** (e.g., placing the target suture needle in various locations)
+- [ ] **Robot Embodiment** (if multiple robots were used)
+- [ ] **Task Execution** (e.g., different techniques for the same task)
+- [ ] **Background / Scene**
+- [ ] **Other** (Please specify: `[Your Dimension]`)
+
+*If you checked any of the above please briefly elaborate below.*
+
+**Example:** We start the ultrasound scan from different initial positions. We scan multiple bone structures including fibla and tibia
+
+---
+
+## 🛠️ Equipment & Setup
+
+### Robotic Platform(s)
+
+*List the primary robot(s) used.*
+
+- **Robot 1:** `[e.g., dVRK (da Vinci Research Kit)]`
+- **Robot 2:** `[If applicable]`
+
+### Sensors & Cameras
+
+*List the sensors and cameras used. Specify model names where possible. (Add and remove rows as needed)*
+
+| Type | Model/Details |
+| :--- | :--- |
+| **Primary Camera** | `[None]` |
+| **Room/3rd Person Camera** | `[None]` |
+| **Force/Torque Sensor** | `[None]` |
+| **Medical Imager** | `[e.g., SuperSonic Imagine SL18-5 Ultrasound, B-Mode]` |
+| **Other** | `[Specify]` |
+
+---
+
+## 🎯 Action & State Space Representation
+
+*Describe how actions and robot states are represented in your dataset. This is crucial for understanding data compatibility and enabling effective policy learning.*
+
+### Action Space Representation
+
+**Primary Action Representation:**
+- [ ] **Absolute Cartesian** (position/orientation relative to robot base)
+- [ ] **Relative Cartesian** (delta position/orientation from current pose)
+- [ ] **Joint Space** (direct joint angle commands)
+- [ ] **Other** (Please specify: `[Your Representation]`)
+
+**Orientation Representation:**
+- [ ] **Quaternions** (x, y, z, w)
+- [ ] **Euler Angles** (roll, pitch, yaw)
+- [ ] **Axis-Angle** (rotation vector)
+- [ ] **Rotation Matrix** (3x3 matrix)
+- [ ] **Other** (Please specify: `[Your Representation]`)
+
+**Reference Frame:**
+- [ ] **Robot Base Frame**
+- [ ] **Tool/End-Effector Frame**
+- [ ] **World/Global Frame**
+- [ ] **Camera Frame**
+- [ ] **Other** (Please specify: `[Your Frame]`)
+
+**Action Dimensions:**
+*List the action space dimensions and their meanings.*
+
+**Example:**
+```
+action: [x, y, z, qx, qy, qz, qw, gripper]
+- x, y, z: Absolute position in robot base frame (meters)
+- qx, qy, qz, qw: Absolute orientation as quaternion
+- gripper: Gripper opening angle (radians)
+```
+
+### State Space Representation
+
+**State Information Included:**
+- [ ] **Joint Positions** (all articulated joints)
+- [ ] **Joint Velocities**
+- [ ] **End-Effector Pose** (Cartesian position/orientation)
+- [ ] **Force/Torque Readings**
+- [ ] **Gripper State** (position, force, etc.)
+- [ ] **Other** (Please specify: `[Your State Info]`)
+
+**State Dimensions:**
+*List the state space dimensions and their meanings.*
+
+**Example:**
+```
+observation.state: [j1, j2, j3, j4, j5, j6, j7, gripper_pos]
+- j1-j7: Absolute joint positions for 7-DOF arm (radians)
+- gripper_pos: Current gripper opening (meters)
+```
+
+### 📋 Recommended Additional Representations
+
+*Even if not your primary action/state representation, we strongly encourage including these standardized formats for maximum compatibility:*
+
+**Recommended Action Fields:**
+- **`action.cartesian_absolute`**: Absolute Cartesian pose with absolute quaternions
+  ```
+  [x, y, z, qx, qy, qz, qw, gripper_angle]
+  ```
+
+**Recommended State Fields:**
+- **`observation.state.joint_positions`**: Absolute positions for all articulated joints
+  ```
+  [joint_1, joint_2, ..., joint_n]
+  ```
+
+
+---
+
+## ⏱️ Data Synchronization Approach
+
+*Describe how you achieved proper data synchronization across different sensors, cameras, and robotic systems during data collection. This is crucial for ensuring temporal alignment of all modalities in your dataset.*
+
+**Example:** *We collect joint kinematics from our Franka Research 3 and RGB-D frames from Intel RealSense D435 cameras, all running in ROS 2 Galactic on the same workstation clocked with ROS Time. Both drivers stamp their outgoing messages’ header.stamp fields with the shared system clock, and we record /joint_states, /camera/*/image_raw, and /camera/*/camera_info in a single rosbag2 session. During export to LeRobot, each data point’s ROS header.stamp is written verbatim into the timestamp attribute. Offline checks show inter-sensor skew stays below ±2 ms across a 2-minute capture.*
+
+---
+
+## 👥 Attribution & Contact
+
+*Please provide attribution for the dataset creators and a point of contact.*
+
+| | |
+| :--- | :--- |
+| **Dataset Lead** | `[Name1, Name2, ...]` |
+| **Institution** | `[Your Institution]` |
+| **Contact Email** | `[email1@example.com, email2@example.com, ...]` |
+| **Citation (BibTeX)** | <pre><code>@misc{[your_dataset_name_2025],<br>  author = {[Your Name(s)]},<br>  title = {[Your Dataset Title]},<br>  year = {2025},<br>  publisher = {Open-H-Embodiment},<br>  note = {https://hrpp.research.virginia.edu/teams/irb-sbs/researcher-guide-irb-sbs/identifiers}<br>}</code></pre> |