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arXiv · 2511.17441

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 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
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Abstract

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.

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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. 2025-11-21. RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation. https://arxiv.org/abs/2511.17441

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