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Main Authors: Hu, Wenkang, Tang, Xincheng, E, Yanzhi, Li, Yitong, Shu, Zhengjie, Li, Wei, Wang, Huamin, Yang, Ruigang
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2511.06434
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author Hu, Wenkang
Tang, Xincheng
E, Yanzhi
Li, Yitong
Shu, Zhengjie
Li, Wei
Wang, Huamin
Yang, Ruigang
author_facet Hu, Wenkang
Tang, Xincheng
E, Yanzhi
Li, Yitong
Shu, Zhengjie
Li, Wei
Wang, Huamin
Yang, Ruigang
contents 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/
format Preprint
id arxiv_https___arxiv_org_abs_2511_06434
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Real Garment Benchmark (RGBench): A Comprehensive Benchmark for Robotic Garment Manipulation featuring a High-Fidelity Scalable Simulator
Hu, Wenkang
Tang, Xincheng
E, Yanzhi
Li, Yitong
Shu, Zhengjie
Li, Wei
Wang, Huamin
Yang, Ruigang
Robotics
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/
title Real Garment Benchmark (RGBench): A Comprehensive Benchmark for Robotic Garment Manipulation featuring a High-Fidelity Scalable Simulator
topic Robotics
url https://arxiv.org/abs/2511.06434