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Surgical/jhu/lcsr/miracle/needle_regrasp/data/chunk-000/episode_000000.parquet

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Surgical/jhu/lcsr/miracle/needle_regrasp/lerobot_ep1_ep20.zip

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Surgical/jhu/lcsr/miracle/needle_regrasp/meta/README.md

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+# JHU-MIRACLELab/needle-regrasp - README
+
+---
+
+## 📋 At a Glance
+
+*Teleoperated demonstrations of a da Vinci robot regrasping a needle until reaching the optimal configuration.*
+
+---
+
+## 📖 Dataset Overview
+
+*This dataset contains TODO trajectory of a trained researcher using the dVRK to perform suture needle regrasp.*
+
+| | |
+| :--- | :--- |
+| **Total Trajectories** | `1` |
+| **Total Hours** | `[Number]` |
+| **Data Type** | `[ ] Clinical` `[ ] Ex-Vivo` `[V] Table-Top Phantom` `[ ] Digital Simulation` `[ ] Physical Simulation` `[ ] Other (If checked, update "Other")` |
+| **License** | CC BY 4.0 |
+| **Version** | `[1.0]` |
+
+---
+
+## 🎯 Tasks & Domain
+
+### Domain
+
+*Select the primary domain for this dataset.*
+
+- [x] **Surgical Robotics**
+- [ ] **Ultrasound Robotics**
+- [ ] **Other Healthcare Robotics** (Please specify: `[Your Domain]`)
+
+### Demonstrated Skills
+
+*List the primary skills or procedures demonstrated in this dataset.*
+
+- Needle-regrasp
+
+---
+
+## 🔬 Data Collection Details
+
+### Collection Method
+
+*How was the data collected?*
+
+- [x] **Human Teleoperation**
+- [ ] **Programmatic/State-Machine**
+- [ ] **AI Policy / Autonomous**
+- [ ] **Other** (Please specify: `[Your Method]`)
+
+### Operator Details
+
+| | Description |
+| :--- | :--- |
+| **Operator Count** | `1` |
+| **Operator Skill Level** | `[ ] Expert (e.g., Surgeon, Sonographer)` <br> `[V] Intermediate (e.g., Trained Researcher)` <br> `[ ] Novice (e.g., ML Researcher with minimal experience)` <br> `[ ] N/A` |
+| **Collection Period** | From `[2025-12-15]` to `[2025-12-31]` |
+
+### Recovery Demonstrations
+
+*Does this dataset include examples of recovering from failure?*
+
+- [x] **Yes**
+- [ ] **No**
+
+**If yes, please briefly describe the recovery process:**
+
+*The operator will keep trying until the needle is successfully grasped at the optimal configuration.*
+
+---
+
+## 💡 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)
+- [x] **Spatial Layout** (e.g., placing the target suture needle in various locations)
+- [x] **Robot Embodiment** (if multiple robots were used)
+- [x] **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.*
+
+The needle is initially in a random configuration.  
+
+The trajectories contain 50% of a large needle driver as PSM2 and 50% of a cadiere forcep as PSM2. 
+
+---
+
+## 🛠️ Equipment & Setup
+
+### Robotic Platform(s)
+
+*List the primary robot(s) used.*
+
+- **Robot 1:** `dVRK (da Vinci Research Kit)`
+
+### Sensors & Cameras
+
+*List the sensors and cameras used. Specify model names where possible. (Add and remove rows as needed)*
+
+| Type | Model/Details |
+| :--- | :--- |
+| **Primary Camera** | `[e.g., Endoscopic Camera, 1920x1080 @ 30fps]` |
+| **Room/3rd Person Camera** | `N/A` |
+| **Force/Torque Sensor** | `N/A` |
+| **Medical Imager** | `N/A` |
+| **Other** | `N/A` |
+
+---
+
+## 🎯 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)
+- [x] **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.*
+
+```
+action: [PSM1 j1, PSM1 j2, PSM1 j3, PSM1 j4, PSM1 j5, PSM1 j6, PSM1 jaw, PSM2 j1, PSM2 j2, PSM2 j3, PSM2 j4, PSM2 j5, PSM2 j6, PSM2 jaw]
+- j1-j6: Delta joint angles for the 6 joints of a PSM (radians)
+- jaw: Delta jaw angle (radians)
+```
+
+### State Space Representation
+
+**State Information Included:**
+- [x] **Joint Positions** (all articulated joints)
+- [ ] **Joint Velocities**
+- [x] **End-Effector Pose** (Cartesian position/orientation)
+- [ ] **Force/Torque Readings**
+- [x] **Gripper State** (position, force, etc.)
+- [ ] **Other** (Please specify: `[Your State Info]`)
+
+**State Dimensions:**
+*List the state space dimensions and their meanings.*
+
+```
+observation.state: [ECM j1, ECM j2, ECM j3, ECM j4, ECM x, ECM y, ECM z, ECM qx, ECM qy, ECM qz, ECM qw, PSM1 j1, PSM1 j2, PSM1 j3, PSM1 j4, PSM1 j5, PSM1 j6, PSM1 jaw, 
+PSM1 x, PSM1 y, PSM1 z, PSM1 qx, PSM1 qy, PSM1 qz, PSM1 qw, 
+PSM2 j1, PSM2 j2, PSM2 j3, PSM2 j4, PSM2 j5, PSM2 j6, PSM2 jaw, 
+PSM2 x, PSM2 y, PSM2 z, PSM2 qx, PSM2 qy, PSM2 qz, PSM2 qw]
+```
+
+### 📋 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** | `[Chang Liu, Zih-Yun Chiu]` |
+| **Institution** | `[Johns Hopkins University]` |
+| **Contact Email** | `[cliu250@jh.edu, zchiu@jhu.edu]` |
+| **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> |

Surgical/jhu/lcsr/miracle/needle_regrasp/meta/episodes.jsonl

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Surgical/jhu/lcsr/miracle/needle_regrasp/meta/episodes_stats.jsonl

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Surgical/jhu/lcsr/miracle/needle_regrasp/meta/info.json

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+{
+    "codebase_version": "v2.1",
+    "robot_type": "dvrk",
+    "total_episodes": 1,
+    "total_frames": 300,
+    "total_tasks": 1,
+    "total_videos": 2,
+    "total_chunks": 1,
+    "chunks_size": 1000,
+    "fps": 15,
+    "splits": {
+        "train": "0:1"
+    },
+    "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
+    "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4",
+    "features": {
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+                "ECM j2",
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+                "ECM j4",
+                "ECM x",
+                "ECM y",
+                "ECM z",
+                "ECM qx",
+                "ECM qy",
+                "ECM qz",
+                "ECM qw",
+                "PSM1 j1",
+                "PSM1 j2",
+                "PSM1 j3",
+                "PSM1 j4",
+                "PSM1 j5",
+                "PSM1 j6",
+                "PSM1 jaw",
+                "PSM1 x",
+                "PSM1 y",
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+                "PSM1 qw",
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+                "PSM2 j5",
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+}

Surgical/jhu/lcsr/miracle/needle_regrasp/meta/modality.json

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+{
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+      "end": 25,
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+      "original_key": "action"
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+    "psm2_pose": {
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+      "end": 39,
+      "original_key": "observation.state"
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+    "psm2_gripper": {
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+      "end": 14,
+      "original_key": "action"
+    }
+  },
+  "video": {
+    "camera_left": {
+      "original_key": "observation.images.left"
+    },
+    "camera_right": {
+      "original_key": "observation.images.right"
+    }
+  },
+  "annotation": {
+    "task": {
+      "original_key": "task_index"
+    }
+  }
+}

Surgical/jhu/lcsr/miracle/needle_regrasp/meta/percentile_stats.json

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