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performing **suturing (single loop)** on **ex-vivo porcine tissue**. The setup uses DeBakey forceps (left) and a needle driver (right) to execute a single needle pass through tissue, including a bimanual needle extraction handover. + + +--- + +## Dataset Overview + +This dataset contains teleoperated trajectories of trained operators using the dVRK to perform a single-loop suturing action on ex-vivo animal tissue. The goal is to perform one needle pass through tissue with correct needle orientation and controlled interaction with deformable, wet tissue. + +**Task Logic & Execution:** +The operator utilises the **Patient Side Manipulators (PSMs)** equipped with DeBakey forceps (left) and a needle driver (right). +* **Needle Hold (Right Hand):** The right tool grasps the needle in a suturing-ready pose. +* **Single Pass + Extraction (Left Hand):** The right hand drives the needle through the tissue, then the left hand grasps and extracts the needle from the far side. + +**Key Features:** +* **Real Ex-Vivo Needle-Tissue Interaction:** Uses **porcine tissue** to capture compliance and deformation during needle driving. +* **Bimanual Needle Handover:** Demonstrations include the right-to-left extraction handover required to complete a single pass. + +| | | +| :--- | :--- | +| **Total Trajectories** | `180` | +| **Total Hours** | `0.476` | +| **Data Type** | `[ ] Clinical` `[x] Ex-Vivo` `[ ] Table-Top Phantom` `[ ] Digital Simulation` `[ ] Physical Simulation` `[ ] Other` | +| **License** | CC BY 4.0 | +| **Version** | `1.0` | + +## **Hamlyn dVRK Dataset Overview** + +This is part of the **Hamlyn dVRK Dataset**, which encompasses **six distinct surgical tasks**. All data were collected through teleoperation on bimanual tasks performed on ex-vivo animal samples and phantoms. + +### **Task Conditioning** +The tasks are categorized into two types: +- **Non-conditioned**: Single sentence task descriptions +- **Language-conditioned**: Multiple variants of task descriptions across episodes + +### **Dataset Statistics** +- **Total Episodes**: 972 +- **Total Frames**: 545k @ 30Hz +- **Dataset Duration**: 5.04 hours + +### **Episode Outcomes** +| Outcome Category | Episodes | Description | +|------------------|----------|-------------| +| **Success** | 780 | Task completed successfully with specified conditions | +| **Recovery** | 110 | Task finished with recovery behavior | +| **Failed** | 82 | Task failed to complete | + +*Success rates vary across tasks due to varying difficulty levels for operators during teleoperation. + + +--- + +## Tasks & Domain + +### Domain + +*Select the primary domain for this dataset.* + +- [x] **Surgical Robotics** +- [ ] **Ultrasound Robotics** +- [ ] **Other Healthcare Robotics** + +### Demonstrated Skills + +This specific dataset subset focuses on **Suturing (Single Loop)**. + +*Note: This is part of the Hamlyn dVRK Data Collection which also includes:* +- Tissue Retraction / Exposure +- Knot Tying +- Suturing (Single Loop) +- Suturing (Dual Loop) +- Peg Transfer +- Needle Grasp and Handover + +--- + +## Data Collection Details + +### Collection Method + +*How was the data collected?* + +- [x] **Human Teleoperation** +- [ ] **Programmatic/State-Machine** +- [ ] **AI Policy / Autonomous** +- [ ] **Other** + + +### Operator Details + +| | Description | +| :--- | :--- | +| **Operator Count** | 2 | +| **Operator Skill Level** | `[ ] Expert (e.g., Surgeon, Sonographer)`
`[x] Intermediate (e.g., Trained Researcher)`
`[x] Novice (e.g., ML Researcher with minimal experience)`
`[ ] N/A`| +| **Collection Period** | From `2025-12-01` to `2026-01-15` | +| **Input Interface** | `Teleoperation interface with bimanual Force Dimension Sigma 7 haptic device` + +### Recovery Demonstrations + +*Does this dataset include examples of recovering from failure?* + +- [x] **Yes** +- [ ] **No** + +**If yes, please briefly describe the recovery process:** + +In the single-loop suturing task, failure modes typically involve an incorrect bite, needle drop, loss of needle control during extraction, or unstable tissue interaction. In these instances, the operator does not abort the episode but performs a **recovery manoeuvre**: re-grasping the needle, re-aligning the approach, and repeating the pass and extraction steps to complete the stitch. + + +--- + +## Diversity Dimensions + +*Check all dimensions that were intentionally varied during data collection.* + +- [ ] **Camera Position / Angle** +- [ ] **Lighting Conditions** +- [x] **Target Object** (Varied tissue geometry and stitch location) +- [x] **Spatial Layout** (Randomised tissue placement) +- [ ] **Robot Embodiment** +- [x] **Task Execution** (Left vs. Right hand dominance / Approach angle) +- [ ] **Background / Scene** +- [x] **Initial Robot Configuration** (Ex-Vivo domain randomisation) + +*Elaboration on Diversity:* + +* **Target Object:** Fresh **porcine tissue** was used to capture deformation during needle driving. Diversity is achieved through variations in tissue stiffness/geometry and stitch location. +* **Spatial Layout:** The tissue pose was manually randomised within the workspace between sets to reduce overfitting to absolute coordinates. +* **Task Execution:** Operators vary entry angle, wrist orientation, and extraction strategy to maintain stable needle control. +* **Initial Robot Configuration:** End-effectors were reset to a randomised "home" position above the workspace before each trajectory. + + +--- + +## 🛠️ Equipment & Setup + +### Robotic Platform(s) + +*List the primary robot(s) used.* + +- **Robot 1:** `dVRK (da Vinci Research Kit) - Patient Side Manipulators (PSM1, PSM2)` + + +### Sensors & Cameras + +*List the sensors and cameras used. Specify model names where possible.* + +| Type | Model/Details | +| :--- | :--- | +| **Primary Camera** | `Intel RealSense D405 (RGB + Depth), 848x480 @ 30fps` | +| **Wrist Camera** | `INSKAM 5.5mm USB Endo-Cam (Right/Left Arm) with custom built mount, view angle 66 degree, focal length 4-10cm, 640x480 @ 24fps` | +| **Kinematics** | `dVRK High-Frequency Joint Encoders (100Hz)` | + + + +--- + +## 🎯 Action & State Space Representation + +*The dataset follows the standard LeRobot format for bimanual manipulation.* + +### Action Space Representation + +**Primary Action Representation:** +- [x] **Absolute Cartesian** (position/orientation relative to robot base) +- [ ] **Relative Cartesian** +- [ ] **Joint Space** + +**Orientation Representation:** +- [x] **Quaternions** (x, y, z, w) +- [ ] **Euler Angles** +- [ ] **Rotation Matrix** + +**Reference Frame:** +- [x] **Robot Base Frame** (Base of each PSM arm) +- [ ] **Camera Frame** + +**Action Dimensions:** + +action: [x, y, z, qx, qy, qz, qw, gripper_angle, x, y, z, qx, qy, qz, qw, gripper_angle] + +- The first 8 dimensions are for the *left* arm and last 8 dimensions are for the *right* arm +- x, y, z: Absolute position in PSM base frame (meters) +- qx, qy, qz, qw: Absolute orientation as quaternion +- gripper_angle: Normalized jaw opening angle (1 = opened, 0 = closed) + + +### State Space Representation + +**State Information Included:** +- [x] **Joint Positions** +- [x] **Joint Velocities** +- [ ] **End-Effector Pose** (No extra end-effector used with dVRK) +- [x] **Gripper State** + +**Primary State:** + +*observation.state*: [x, y, z, qx, qy, qz, qw, gripper_angle, x, y, z, qx, qy, qz, qw, gripper_angle] + +- The first 8 dimensions are for the *left* arm and last 8 dimensions are for the *right* arm +- x, y, z: Absolute position in PSM base frame (meters) +- qx, qy, qz, qw: Absolute orientation as quaternion +- gripper_angle: Normalized jaw opening angle (1 = opened, 0 = closed) + +**State Dimensions:** + +`observation.state.left_arm_cartesian`: [x, y, z, qx, qy, qz, qw, gripper_angle] + +`observation.state.right_arm_cartesian`: [x, y, z, qx, qy, qz, qw, gripper_angle] + +`observation.state.left_arm_joint`: [j1, j2, j3, j4, j5, j6, gripper_angle] + +`observation.state.right_arm_joint`: [j1, j2, j3, j4, j5, j6, gripper_angle] + +- j1-j6: Joint positions for 6-DOF PSM arm (radians) +- gripper_angle: Normalized jaw opening angle (1 = opened, 0 = closed) + + +--- + +## ⏱️ Data Synchronization Approach + +*Describe how you achieved proper data synchronization.* + +**Distributed Synchronization Architecture:** +The data collection setup involves a distributed system with a robot control machine that teleop the dVRK and a sensor recording machine that stream kinematics, and videos from camers. +1. **Clock Sync:** We utilize **Chrony (NTP)** to enforce strict time alignment between the two workstations, minimizing clock skew to < 3.3 ms. +2. **Timestamping:** All data streams (camera RGB and depth images, wrist camer images, robot kinematics) are timestamped with **ROS wall-time** headers at the exact moment of capture. +3. **Delay Compensattion and Trimming:** The different cameras can introduce small relative delays. These delays are first estimated and compensated by applying a common temporal offset to each stream. Subsequently, all streams are temporally trimmed to their common interval, bounded by the latest start time and the earliest end time across all modalities. +4. **Alignment:** During the LeRobot conversion process, frames from all data streams are aligned to a reference timeline at 30 Hz30 Hz. This is achieved via nearest-neighbor temporal interpolation based on the synchronized ROS timestamps. + +--- + +## Attribution & Contact + +*Please provide attribution for the dataset creators and a point of contact.* + +| | | +| :--- | :--- | +| **Dataset Lead** | `Jianhao Su, Kaizhong Deng, Zhaoyang Jacopo Hu` | +| **Institution** | `The Hamlyn Centre for Robotic Surgery, Imperial College London` | +| **Contact Email** | `k.deng21@imperial.ac.uk (for technical issues), stamatia.giannarou@imperial.ac.uk (for correspondence)` | +| **Citation (BibTeX)** |
@misc{hamlyn_dvrk_openh_2026,
author = {Su, Jianhao and Deng, Kaizhong and Hu, Zhaoyang Jacopo and Rodriguez y Baena, Ferdinando and Giannarou, Stamatia},
title = {Hamlyn dVRK Surgical Manipulation Dataset for Open-H},
year = {2026},
publisher = {Open-H-Embodiment},
note = {Ex-Vivo Domain: Suturing (Single Loop)}
}
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100644 index 0000000000000000000000000000000000000000..16aaff6991b2ea33a8ec0326b529b95e887d1023 --- /dev/null +++ b/Surgical/hamlyn/tissue_lifting/meta/tasks.jsonl @@ -0,0 +1,15 @@ +{"task_index": 0, "task": "Retract the partially dissected tissue flap using the right instrument (left-side grasp)."} +{"task_index": 1, "task": "Retract the partially dissected tissue flap using the right instrument (center grasp)."} +{"task_index": 2, "task": "Retract the partially dissected tissue flap using the right instrument (right-side grasp)."} +{"task_index": 3, "task": "Retract the partially dissected tissue flap using the left instrument (left-side grasp)."} +{"task_index": 4, "task": "Retract the partially dissected tissue flap using the left instrument (center grasp)."} +{"task_index": 5, "task": "Retract the partially dissected tissue flap using the left instrument (right-side grasp)."} +{"task_index": 6, "task": "Lift the intact tissue block using the right instrument (left-side grasp)."} +{"task_index": 7, "task": "Re-orient and grasp the intact tissue block at the center using the right instrument."} +{"task_index": 8, "task": "Lift the intact tissue block using the right instrument (center grasp)."} +{"task_index": 9, "task": "Re-orient and grasp the intact tissue block at the right region using the right instrument."} +{"task_index": 10, "task": "Lift the intact tissue block using the right instrument (right-side grasp)."} +{"task_index": 11, "task": "Lift the intact tissue block using the left instrument (left-side grasp)."} +{"task_index": 12, "task": "Lift the intact tissue block using the left instrument (center grasp)."} +{"task_index": 13, "task": "Retract the partially dissected tissue flap from the left side using the right instrument."} +{"task_index": 14, "task": "Retract the partially dissected tissue flap from the right side using the right instrument."}