Digital Twin for Suturing Scenes

Overview

Development of high-fidelity digital twin environments for surgical suturing scenes, utilized for NSF AccelNet Surgical Robotics Challenges.

Key Contributions

• Develop high-fidelity environments with realistic dynamic feedback for suturing execution on an open-source 3D simulation platform (AMBF), utilized for NSF AccelNet Surgical Robotics Challenges
• Scan the real-world suturing training phantoms using MRI and import the segmented 3D models into the simulation environment
• Build photorealistic dVRK surgical instrument simulation models, sharing the models with the dVRK community
• Construct high-fidelity digital twin for suturing scenes in NVIDIA Omniverse Isaac Sim
• Develop an autonomous synthetic data generation pipeline using the high-fidelity simulation environment in the AMBF simulator

Simulation Scene Examples