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Surgical/hamlyn/knot_tying/Readme-Knot Tying.md

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+<!--
+Open-H Embodiment Dataset README Template (v1.0)
+Hamlyn Centre dVRK Dataset Submission
+-->
+
+# Hamlyn-dVRK: Ex-Vivo Knot Tying - README
+
+---
+
+## At a Glance
+
+High-fidelity teleoperated demonstrations of a bimanual **da Vinci Research Kit (dVRK)** robot performing **knot tying** on **ex-vivo porcine tissue**. The setup uses DeBakey forceps (left) and a needle driver (right) to manipulate suture strands and form stable surgical knots on deformable, wet tissue.
+
+
+---
+
+## Dataset Overview
+
+This dataset contains teleoperated trajectories of trained operators using the dVRK to perform knot tying on ex-vivo animal tissue. The goal is to reliably form a stable knot while maintaining appropriate strand tension and avoiding strand slip on wet tissue.
+
+**Task Logic & Execution:**
+The operator utilises the **Patient Side Manipulators (PSMs)** equipped with DeBakey forceps (left) and a needle driver (right).
+*   **Initial Condition:** The needle has already been passed through the tissue slit, and both suture ends are visible outside the tissue.
+*   **Knot Tying:** The robot grasps and manipulates the two strand ends bimanually to create the required crossings and throws, then tightens the knot while controlling tension and strand alignment.
+
+**Key Features:**
+*   **Pre-Threaded Start State:** The needle is already passed through the tissue slit and both suture ends are outside the tissue at the start of each trajectory, isolating knot tying from needle driving.
+*   **Bimanual Throw Formation and Tightening:** Demonstrations capture coordinated grasping, crossing, and controlled tightening required to form consistent knot throws on ex-vivo porcine tissue.
+
+| | |
+| :--- | :--- |
+| **Total Trajectories** | `77` |
+| **Total Hours** | `0.254` |
+| **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 **Knot Tying**.
+
+*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)` <br> `[x] Intermediate (e.g., Trained Researcher)` <br> `[x] Novice (e.g., ML Researcher with minimal experience)` <br> `[ ] 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 knot tying task, failure modes typically involve losing strand tension, or an unstable throw formation. In these instances, the operator does not abort the episode but performs a **recovery manoeuvre**: re-grasping one or both strands, re-establishing tension, and repeating the throw and tightening steps to complete the knot.
+
+
+---
+
+## Diversity Dimensions
+
+*Check all dimensions that were intentionally varied during data collection.*
+
+- [ ] **Camera Position / Angle**
+- [ ] **Lighting Conditions**
+- [x] **Target Object** (Varied tissue geometry and suture configuration)
+- [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 wet-surface interaction. Diversity is achieved through variations in tissue stiffness/geometry and suture strand configuration (e.g., visible strand lengths and relative positioning).
+*   **Spatial Layout:** The tissue pose was manually randomised within the workspace between sets to reduce overfitting to absolute coordinates.
+*   **Task Execution:** Operators vary grasp points, crossing direction, and tightening strategy to maintain tension and produce stable throws.
+*   **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.  **Clutch Masking:** As clutch is frequently used in teleoperation, sudden and meaningless breaks in the trajectory were removed to reduce stops during operation to improve trajectory smoothness.
+5.  **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)** | <pre><code>@misc{hamlyn_dvrk_openh_2026,<br>  author = {Su, Jianhao and Deng, Kaizhong and Hu, Zhaoyang Jacopo and Rodriguez y Baena, Ferdinando and Giannarou, Stamatia},<br>  title = {Hamlyn dVRK Surgical Manipulation Dataset for Open-H},<br>  year = {2026},<br>  publisher = {Open-H-Embodiment},<br>  note = {Ex-Vivo Domain: Knot Tying}<br>}</code></pre> |
+

Surgical/hamlyn/knot_tying/meta/episodes.jsonl

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Surgical/hamlyn/knot_tying/meta/info.json

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+}

Surgical/hamlyn/knot_tying/meta/modality.json

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+}

Surgical/hamlyn/knot_tying/meta/relative_stats.json

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+{}

Surgical/hamlyn/knot_tying/meta/stats.json

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