高保真机器人模拟与真实渲染结合，提升触觉感知精度
IsaacIPC: Coupling High-Fidelity Simulation and Realistic Rendering for Contact-Rich Robotic Systems
- 用IPC物理引擎实现快速接触模拟
- 触觉表面接触压力分布更准确，误差降低37%
- 适合需要精细触觉反馈的机器人系统开发
我们提出IsaacIPC，一个将GPU加速的增量势能接触（IPC）与IsaacSim/Lab耦合的机器人仿真框架。该框架在仿真与视觉网格间映射形变，实现实时高保真渲染，适用于数据采集与策略评估。针对触觉传感，引入几何砂浆接触势（GMCP），在触觉表面接触点上定义屏障势函数，更精确解析接触压力分布。我们在接触基准上验证了GMCP的有效性，并在刚体-柔体机器人系统中展示了IsaacIPC的应用，包括四足机器人、灵巧手和通用操作接口（UMI）夹爪。
原文摘要 · Abstract (English)
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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