Surgical instruments
Forceps, scalpels, hemostats, retractors. Sub-100g, precise grip geometry.
SimReady Assets for Medical Equipment
Precision instruments, patient-care fixtures, and lab consumables, with calibrated mass, friction, and collision geometry — ready for surgical, hospital-logistics, and lab-automation simulators.
Updated 2026-06-06
Medical robotics simulation needs assets simulators can trust: surgical robots picking 2g instruments off cluttered trays, mobile platforms navigating IV stands in narrow corridors, lab arms manipulating sterile glassware where one slip means contamination. Generic 3D libraries do not contain these objects, and the curated SimReady libraries do not either. Rigyd converts CAD-derived geometry, reference images, or text descriptions into validated OpenUSD and MJCF in minutes per asset, validated in both formats, with physics verified by test to the precision medical robotics demands.
Objects
What's in this category.
Patient monitors
Bedside monitors, telemetry units, vital-signs displays. Stable bases, articulated mounts.
IV stands and infusion pumps
Wheeled bases, telescoping poles, swing arms. Tip-over physics matters for navigation training.
Patient beds and stretchers
Articulated frames, side rails, casters. Mass distribution depends on patient + bedding state.
Lab consumables
Pipettes, beakers, Petri dishes, vials, racks. Fragile, low-restitution, precise placement tasks.
Ventilators and defibrillators
Heavy, wheeled, articulated controls. Cable management impacts navigation paths.
PPE dispensers and gown carts
Glove boxes, mask dispensers, hand-sanitiser stations. Manipulation targets for supply-runner robots.
Hospital trolleys and carts
Loaded vs unloaded mass differences. Multi-drawer articulation for med-dispensing tasks.
Imaging equipment props
C-arm fixtures, portable X-ray bases, ultrasound probes. Used for robot pre-op staging scenarios.
Physics
Physics characteristics.
Precision mass for small instruments
Surgical instruments are sub-100g and their physics matters at the gram level. Rigyd computes mass from volume × material density (stainless steel for most instruments) with consistency tighter than the domain-randomization band most robotic-surgery policies wrap around.
Low-friction smooth surfaces
Sterilisable surfaces are polished metal or medical-grade plastic, friction coefficient typically 0.10–0.25 dynamic. Rigyd keys friction to surface material classification, getting the right band for in-hand manipulation, tray placement, and slip detection during a procedure.
Articulated devices and tip-over modelling
IV stands, monitors on arms, patient beds — all articulated. Articulation hierarchy (PhysicsArticulationRootAPI for USD, MJCF native joints) is generated automatically. Centre-of-mass placement is critical for tip-over scenarios that appear constantly in mobile-robot navigation tasks.
Materials
Common materials.
Stainless steel · instruments, frames, trolleysMedical-grade plastic (PP, PE, ABS)Glass · consumables, displaysLatex / nitrile rubber · wheels, gasketsAluminium · lightweight frames
Robot tasks
What these assets enable.
Surgical and assistive manipulation
Pick, place, hand-off, and tray-organise instruments under teleoperated or autonomous control. Sterile-tray scenarios with 10–30 instruments at known positions are a standard benchmark.
Hospital logistics navigation
Mobile robots delivering medications, supplies, and patient samples. IV stands, beds, and unattended trolleys are the dominant obstacles; physics-accurate collision matters because rolling-equipment contacts differ from rigid-wall contacts.
Lab automation
Pipetting robots, sample-handling arms, and centrifuge loaders. Consumables are fragile (low restitution, brittle); rack-based placement tasks need millimetre-grade collision accuracy.
~5 min
per asset from input to SimReady output
±15-20%
mass accuracy, inside surgical-robot DR variance
OpenUSD + MJCF
native outputs for Isaac Sim, MuJoCo, Genesis
FAQ
Frequently asked questions
How accurate is mass for sub-100g surgical instruments?
Mass is computed as volume × material density from the source geometry. For stainless-steel surgical instruments, that places typical instruments (forceps, scalpels, hemostats) within 5–10% of measured mass — tighter than the domain-randomization variance most surgical-robot policies already wrap around. Where you have catalog masses from the manufacturer, override the AI estimate and lock the value; for the long tail of instruments without a catalog, AI calibration is inside the bracket policy training requires.
Can Rigyd handle articulated medical devices like adjustable IV stands?
Yes. Articulation hierarchy (telescoping poles, swing arms, casters, adjustable bed frames) is described in the source geometry, and Rigyd outputs OpenUSD with PhysicsArticulationRootAPI or MJCF with native joint declarations as appropriate. Joint stiffness, damping, and limits are configurable. The articulation is what makes tip-over and reachability scenarios accurate in simulation.
What about sterile and fluid-handling scenarios?
Rigid-body physics (instruments, racks, trays) is fully supported. Fluid simulation for IV drips, blood handling, or aerosolisation is not part of Rigyd's output — those need a fluid-simulation extension on top of the rigid-body asset, configured per scenario. For most medical-robot training the rigid-body asset library is the bottleneck; fluid scenarios are typically reserved for narrow validation experiments.
Are outputs accepted by hospital regulatory simulation standards?
Output is industry-standard OpenUSD with USDPhysics schemas and MJCF as defined by MuJoCo — both are accepted formats in the robotics-simulation community and used in academic papers and industry-grade simulation pipelines. Specific regulatory simulation requirements (FDA pre-cert robot simulation, IEC-class robot safety) are policy-level not asset-level; the Rigyd assets feed those workflows but compliance remains the integrator's responsibility.
Can I generate equipment specific to a hospital ward or surgical theatre?
Yes. Bring CAD exports of your actual equipment (most med-device manufacturers publish .glb / .fbx / .obj for VR / AR / training purposes) or reference photos of the equipment in use, and Rigyd produces the SimReady asset. For non-catalog items (custom carts, hospital-specific fixtures) the text-to-asset path produces a placeholder with calibrated physics; replace with measured CAD geometry once available.
Build medical robotics simulations with the equipment you actually use
Drop in CAD, images, or text descriptions of your equipment and get SimReady assets in minutes.