IsaacIPC: Coupling High-Fidelity Simulation and Realistic Rendering for Contact-Rich Robotic Systems

Qixin Liang; Zhongqing Han

cs.ROMay 23, 2026

IsaacIPC: Coupling High-Fidelity Simulation and Realistic Rendering for Contact-Rich Robotic Systems

Authors: Qixin Liang, Zhongqing Han

Organizations: Anker Humanoid Lab · Shenzhen, China · The University of Hong Kong · Hong Kong SAR, China

Abstract

We present IsaacIPC, a robotic simulation framework that couples GPU accelerated incremental potential contact (IPC) with IsaacSim/Lab. IsaacIPC maps simulated deformation between simulation and visual meshes, enabling real-time realistic rendering with applications to data collection and policy evaluation. For tactile sensing, we introduce the geometric mortar contact potential (GMCP), which defines a barrier potential over contact samples on tactile surfaces to better resolve contact-pressure distributions. We evaluate GMCP on contact benchmarks and demonstrate IsaacIPC on rigid-deformable robotic simulations including a quadruped robot, a dexterous hand, and a universal manipulation interface (UMI) gripper.

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TaCauchy: An Extensible FEM Framework for Vision-Based Tactile Simulation

Hengfei Zhao, Yifan Xie, Junhao Gong, Yue Sun+5

Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China · Huawei Inc., Shenzhen, China

Vision-based tactile sensors require high-fidelity simulation for reinforcement learning, yet existing approaches struggle to provide accurate mechanical stress fields within GPU-accelerated robotics platforms. We present TaCauchy, an extensible Finite Element Method (FEM) framework that integrates rigorous physics-based force computation into Isaac Sim. Built on the Unified Incremental Potential Contact (UIPC) solver, TaCauchy directly computes Cauchy stress tensors from hyperelastic constitutive laws and projects them onto contact surfaces to obtain traction forces and pressure distributions, providing mechanical ground truth from first principles rather than empirical estimation. Our framework features automatic mesh generation with geometry-aware adaptive refinement and a modular sensor interface enabling rapid integration of diverse sensors (GelSight Mini, DIGIT, 9DTact) with minimal configuration. Performance benchmarks demonstrate 33.40 FPS for single environments and 555 FPS aggregate throughput across 60 parallel environments, with stress extraction overhead under 1 ms. Physical validation experiments show strong agreement between simulated and real tactile responses across force ranges from 1.2556 N to 4.7332 N, achieving SSIM above 0.93, confirming the framework's capability to provide accurate, physically-grounded force supervision for downstream robotic manipulation tasks.

Tactile Sensors Generalizable Robotic Manipulations Finite Element Method Robotics

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Abstract

Explore similar work

TaCauchy: An Extensible FEM Framework for Vision-Based Tactile Simulation

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