An open-source medical physics framework combines GPU acceleration, physics simulation, and generative AI to help developers build, train, and validate healthcare robotics in virtual environments.
Medical Physics Simulation is a free software framework developed by NVIDIA to speed up the creation of healthcare robots using GPU-enabled simulations. As part of Isaac for Healthcare, it allows users to develop simulations for anatomy-device interactions, create challenging situations, train robot policies, and test systems in simulations before conducting any hardware tests.
This framework integrates anatomical models, medical device behaviors, sensor simulations, and robot learning capabilities in reusable simulation environments. Users can view, edit, and customize the simulation framework for their own purposes while also taking advantage of GPU acceleration. Free access to models and simulation workflows helps make the development process more transparent, reproducible, and easier to validate for regulatory approval.
The simulation framework is designed for medical robotics and it simulates anatomy, device interactions, friction, and sensor signals to assess robot behavior in various scenarios. Developed using CUDA, Warp, Newton, Cosmos, and Isaac for Healthcare technologies, it is able to run hundreds of simulations in parallel. According to NVIDIA, running 8,192 robot training simulation environments at once cuts down training time from more than five hours to less than two minutes.
Classical physics simulation incorporates both classic physics simulation as well as generative AI-based physics modeling. While the former takes into account known physics effects, such as contact, dynamics, and friction, the latter allows developers to generate realistic scene dynamics based on procedural data. In combination, they make it possible for developers to test extensively their robotics systems for the healthcare sector prior to creating prototypes.
Medical Physics Simulation has already been implemented across the medical robotics sector. For example, companies such as CMR Surgical and Cambridge Consultants apply it to creating patient-specific simulations for soft-tissue manipulation, whereas Johnson & Johnson MedTech, XCath, Inner Logic, and Medtronic Structural Heart use the technology in digital twins, endovascular robotics, generation of synthetic clinical data, and catheter navigation, respectively.
In any case, Medical Physics Simulation can be used as a modular component of Isaac for Healthcare either as a standalone component or in combination with digital twin pipeline, medical sensor simulation, Isaac Lab robot learning framework, and open models and policies of NVIDIA.
