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Surgical Robotics AI

Our mission is to advance the application of machine learning in robotic surgery. Our primary application domain is the telesurgical approach exemplified in operating rooms by the da Vinci surgical system and in research labs by the da Vinci Research Kit (dVRK) and Raven II open platforms.

Surgical Robotics Simulator

Our surgical robotics simulator is based on the Asynchronous Multi-Body Framework (AMBF), for which we have created the Surgical Robotics Challenge Assets. This environment was created for the AccelNet Surgical Robotics Challenges (see below), but also serves as a simulator for surgical robotic suturing.

AccelNet Surgical Robotics Challenges



A tutorial was presented at the ISMR 2023 Workshop, Hands-On Machine Learning in Simulation and Reality with the da Vinci Research Kit and is being adapted as an online tutorial.


NSF Logo This effort is supported by the US National Science Foundation (NSF), via AccelNet 1927354 (JHU) and 1927275 (WPI).