构建高保真服装模拟基准，提升机器人抓取柔性衣物的仿真精度与效率。
Real Garment Benchmark (RGBench): A Comprehensive Benchmark for Robotic Garment Manipulation featuring a High-Fidelity Scalable Simulator
- 构建包含6000+服装模型的高保真仿真环境，支持真实动态测量。
- 新模拟器误差降低20%，速度比现有工具快3倍。
- 适合研究机器人柔性物体操作的学者和工程师使用。
尽管基于仿真数据学习刚体操作已取得显著进展，但将该成果应用于可变形物体仍受限于缺乏高质量的可变形物体模型与真实的非刚体物理模拟器。本文提出真实服装基准（RGBench），一个面向机器人服装操作的综合性评估基准。其包含超过6000个服装网格模型、一个高性能新模拟器，以及一套系统性评估协议，用于精确衡量真实服装动态的仿真质量。实验表明，本模拟器在保持3倍加速的同时，将仿真误差降低了20%。我们将公开发布RGBench，以推动机器人服装操作领域的发展。网站：https://rgbench.github.io/
原文摘要 · Abstract (English)
While there has been significant progress to use simulated data to learn robotic manipulation of rigid objects, applying its success to deformable objects has been hindered by the lack of both deformable object models and realistic non-rigid body simulators. In this paper, we present Real Garment Benchmark (RGBench), a comprehensive benchmark for robotic manipulation of garments. It features a diverse set of over 6000 garment mesh models, a new high-performance simulator, and a comprehensive protocol to evaluate garment simulation quality with carefully measured real garment dynamics. Our experiments demonstrate that our simulator outperforms currently available cloth simulators by a large margin, reducing simulation error by 20% while maintaining a speed of 3 times faster. We will publicly release RGBench to accelerate future research in robotic garment manipulation. Website: https://rgbench.github.io/
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。