arXiv：cs.LG· Kaiyuan Chen, Shuangyu Xie, Uksang Yoo, Xinyue Zhu, Cael Magner, Alvin Zhu, Daehwa Kim, Eric Heiden, Erwin Coumans, Miles Macklin, Spencer Huang, Ken Goldberg·· 10 小时前
RoboSimStudio：面向机器人操作任务的人与智能体快速 Real2Sim 交互工具包
RoboSimStudio: An Interactive Toolkit for Human and Agent Rapid Real2Sim of Robot Manipulation Tasks
AI 导读
RoboSimStudio（RSS）是一个交互式工具包，将求解器、接触模型和物理参数的选择显式化并可编辑，让人和编码智能体都能基于观测到的物理行为快速创建并迭代优化仿真。RSS 基于开源 Newton 物理仿真系统实现，并开展了三项人类引导的 real2sim 实验：视觉评估、力反馈以及智能体化 Real2Sim2Real。
正文
Authors:Kaiyuan Chen, Shuangyu Xie, Uksang Yoo, Xinyue Zhu, Cael Magner, Alvin Zhu, Daehwa Kim, Eric Heiden, Erwin Coumans, Miles Macklin, Spencer Huang, Ken Goldberg
Abstract:It has been difficult to accurately model the physics of the interaction between a robot and the objects it manipulates, including contact mechanics, coupled contact dynamics, deformations, stiffness and friction. We present RoboSimStudio (RSS), an interactive toolkit that makes choices of solver, contact model, and physical parameters explicit and editable, allowing both humans and coding agents to quickly create and iteratively refine simulations based on observed physical behavior. We implement RSS with the open Newton physics simulation system and describe experiments with human-guided real2sim using (1) visual evaluation, (2) force-feedback and (3) agentic Real2Sim2Real. Code, video and additional information can be found on the project website: this https URL
| Comments: | 13 pages, 7 figures, 1 table. Project website: this https URL |
| Subjects: | Robotics (cs.RO); Artificial Intelligence (cs.AI); Graphics (cs.GR); Machine Learning (cs.LG) |
| Cite as: | arXiv:2610.18835 [cs.RO] |
| (or arXiv:2610.18835v2 [cs.RO] for this version) | |
| https://doi.org/10.48550/arXiv.2610.18835 arXiv-issued DOI via DataCite |
Submission history
From: Kaiyuan Chen [view email]
[v1]
Tue, 13 Oct 2026 17:55:14 UTC (5,969 KB)
[v2]
Wed, 14 Oct 2026 17:02:18 UTC (5,968 KB)
来源：arXiv：cs.LG · arxiv.org