arXiv 2511.174412026-04-13cs.RO

RoboCOIN：一个开源的双臂机器人数据集用于集成操作

RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation

Shihan Wu, Xuecheng Liu, Shaoxuan Xie, Pengwei Wang, Xinghang Li, Bowen Yang, Zhe Li, Kai Zhu, Hongyu Wu, Yiheng Liu, Zhaoye Long, Runtian Xu, Yue Wang, Chong L… 展开作者

Shihan Wu, Xuecheng Liu, Shaoxuan Xie, Pengwei Wang, Xinghang Li, Bowen Yang, Zhe Li, Kai Zhu, Hongyu Wu, Yiheng Liu, Zhaoye Long, Runtian Xu, Yue Wang, Chong Liu, Dihan Wang, Ziqiang Ni, Xiang Yang, You Liu, Ruoxuan Feng, Lei Zhang, Denghang Huang, Chenghao Jin, Anlan Yin, Xinlong Wang, Zhenguo Sun, Junkai Zhao, Mengfei Du, Mingyu Cao, Xiansheng Chen, Hongyang Cheng, Xiaojie Zhang, Yankai Fu, Ning Chen, Cheng Chi, Sixiang Chen, Huaihai Lyu, Xiaoshuai Hao, Yequan Wang, Bo Lei, Dong Liu, Xi Yang, Yance Jiao, Tengfei Pan, Yunyan Zhang, Songjing Wang, Ziqian Zhang, Xu Liu, Ji Zhang, Caowei Meng, Zhizheng Zhang, Jiyang Gao, Song Wang, Xiaokun Leng, Zhiqiang Xie, Zhenzhen Zhou, Peng Huang, Wu Yang, Yandong Guo, Yichao Zhu, Suibing Zheng, Hao Cheng, Xinmin Ding, Yang Yue, Huanqian Wang, Chi Chen, Jingrui Pang, YuXi Qian, Haoran Geng, Lianli Gao, Haiyuan Li, Bin Fang, Gao Huang, Yaodong Yang, Hao Dong, He Wang, Hang Zhao, Yadong Mu, Di Hu, Hao Zhao, Tiejun Huang, Shanghang Zhang, Yonghua Lin, Zhongyuan Wang, Guocai Yao

备注：: Add experiments

阅读 PDF

arXiv 页面 ↗HTML 原文 ↗

AI总结：

本文提出RoboCOIN数据集，包含18万多个演示，涵盖15种机器人平台，通过分层能力金字塔提供精细标注，提升双臂操作模型性能。

摘要：

尽管双臂操作对赋予机器人类人灵活性至关重要，但大规模和多样化数据集稀缺，因双臂机器人平台存在显著硬件异质性。为填补这一差距，我们引入RoboCOIN，一个大规模多体双臂操作数据集，包含来自15种不同机器人平台的180,000多个演示。涵盖16种多样环境，包括住宅、商业和工业场景，包含421个双臂任务，系统分类为39种双臂协作动作和432个物体。我们工作的关键创新是分层能力金字塔，提供从轨迹级概念到片段级子任务和帧级动力学的精细标注。此外，我们提出CoRobot，一个高效的数据显示处理流程，由机器人轨迹标记语言（RTML）驱动，旨在促进质量评估、自动标注和统一的多体和数据管理。大量实验展示了RoboCOIN在提升各种双臂操作模型性能方面的有效性。整个数据集和代码库完全开源，为推进双臂和多体操作研究提供了宝贵的资源。

英文摘要：

Despite the critical role of bimanual manipulation in endowing robots with human-like dexterity, large-scale and diverse datasets remain scarce due to the significant hardware heterogeneity across bimanual robotic platforms. To bridge this gap, we introduce RoboCOIN, a large-scale multi-embodiment bimanual manipulation dataset comprising over 180,000 demonstrations collected from 15 distinct robotic platforms. Spanning 16 diverse environments-including residential, commercial, and industrial settings-the dataset features 421 bimanual tasks systematically categorized by 39 bimanual collaboration actions and 432 objects. A key innovation of our work is the hierarchical capability pyramid, which provides granular annotations ranging from trajectory-level concepts to segment-level subtasks and frame-level kinematics. Furthermore, we present CoRobot, an efficient data processing pipeline powered by the Robot Trajectory Markup Language (RTML), designed to facilitate quality assessment, automated annotation, and unified multi-embodiment and data management. Extensive experiments demonstrate the effectiveness of RoboCOIN in enhancing the performance of various bimanual manipulation models across a wide spectrum of robotic embodiments. The entire dataset and codebase are fully open-sourced, providing a valuable resource for advancing research in bimanual and multi-embodiment manipulation.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。