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CRESSim-Neo: A Batched GPU Simulation Engine for Surgical Robotics and Robot Learning

arXiv · AI, language, vision and robotics · article · Aug 25, 2026 · UTC

We introduce CRESSim-Neo, a batched GPU simulation engine for surgical robotics and robot learning. CRESSim-Neo combines position-based simulation of rigid bodies, deformable tissues, fluids, and strands with batched rendering, surgery-specific sensing, and a GPU-resident data pipeline. The engine supports applications including tissue manipulation, fluid suction, suturing, cable-driven robots, and ultrasound image synthesis. Direct access to physics and rendering buffers enables GPU-resident robot learning and zero-copy PyTorch integration using DLPack. We demonstrate CRESSim-Neo across rigid

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Evidence & attribution

First collected: 2026-09-21T09:42:05.193Z. This is not the publication date.