The cloud computing giant unveiled its Nvidia Medical Physics Simulation framework, a new capability with its Isaac for Healthcare platform, at SRS 2026. It aims to help medical robotics developers model anatomy-device interaction, generate hard-to-capture scenarios, test in silico, and train or evaluate robot policies before hardware-heavy testing.
Nvidia says its framework brings together anatomy and medical device behavior with sensor simulation and robot learning. It helps teams create reusable simulation environments instead of rebuilding custom scenes for every workflow.
The company said the open-source element helps robotics developers inspect the framework and adapt it to their own devices and workflows. Then, they can build on a GPU-accelerated foundation that works seamlessly with the broader Nvidia stack.
Medical Physics Simulation helps developers simulate anatomy, device contact, friction and sensor inputs. Then, they can test in interactions and environments to evaluate how robots perform across these changes. The framework can run hundreds of parallel simulation environments. It can help teams explore more scenarios and identify failure modes earlier in development.
Developers can can now connect vascular anatomy, flexible instruments such as catheters and guidewires, simulated X-ray imaging and reinforcement learning.
CMR Surgical is one example using the simulation technology for soft-tissue surgical robotics. Xcath is also using Medical Physics Simulation for endovascular autonomy policy training.
Johnson & Johnson MedTech, Karl Storz’s Asensus, Moon Surgical, Virtual Incision, Neptune Surgical and Stereotaxis also have ongoing surgical robotic collaborations with Nvidia.
Chris Fryer, CMR Surgical’s chief technology officer, said:
“Open source models allow us to build on shared knowledge, accelerating responsible innovation and, ultimately, gives us the potential to deliver more consistent care and better outcomes for patients worldwide.”
