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CERTIS: Common Environments for Robotic Training in Surgery

CERTIS is a collection of high-quality robotic surgery environments and tasks for NVIDIA Isaac Lab and NVIDIA Isaac Sim. It brings reusable surgical simulation work into one project while acting as a feeder for the upstream projects on which it builds.

Mission

CERTIS aims to provide a reference collection of environments representing the most frequent tasks in robotic surgery. Each environment will support teleoperation, model training and reproducible evaluation.

CERTIS is intended to serve two complementary purposes:

  • to act as a set of gold-standard benchmark environments and tasks, or gyms, for surgical robotics
  • and to provide a library of compositional primitives from which more complex surgical tasks and workflows can be assembled.

Design goals

  • Isaac-native: environments are implemented in Isaac Lab and Isaac Sim using shared conventions and reusable components.
  • Teleoperation-ready: tasks are designed for demonstration collection, human control and embodied policy development.
  • Benchmark-quality: environments provide clear task definitions, success and failure conditions, metrics and reproducible evaluation protocols.
  • Composable: robots, scenes, assets, task logic and interaction primitives can be combined without rebuilding complete environments from scratch.
  • Visually excellent: environments use high-quality assets, materials, lighting and rendering suitable for both model training and compelling visualisation.
  • Upstream-oriented: mature environments and general-purpose components are prepared for contribution to relevant upstream projects.

Intended users

CERTIS is for researchers and engineers working on surgical robotics, teleoperation, imitation learning, reinforcement learning, vision-language-action models, simulation and embodied evaluation.

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Common Environments for Robotic Training in Surgery

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