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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.24310 |
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| _version_ | 1866914394579927040 |
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| author | Zheng, Yupeng Peng, Jichao Li, Weize Zheng, Yuhang Li, Xiang Jin, Yujie Wei, Julong Zhang, Guanhua Zheng, Ruiling Cao, Ming Gu, Songen Zou, Zhenhong Li, Kaige Wu, Ke Yang, Mingmin Liu, Jiahao Li, Pengfei Si, Hengjie Zhu, Feiyu Fu, Wang Wang, Likun Yao, Ruiwen Zhao, Jieru Chen, Yilun Ding, Wenchao |
| author_facet | Zheng, Yupeng Peng, Jichao Li, Weize Zheng, Yuhang Li, Xiang Jin, Yujie Wei, Julong Zhang, Guanhua Zheng, Ruiling Cao, Ming Gu, Songen Zou, Zhenhong Li, Kaige Wu, Ke Yang, Mingmin Liu, Jiahao Li, Pengfei Si, Hengjie Zhu, Feiyu Fu, Wang Wang, Likun Yao, Ruiwen Zhao, Jieru Chen, Yilun Ding, Wenchao |
| contents | We introduce World In Your Hands (WIYH), a large-scale open-source ecosystem comprising over 1,000 hours of human manipulation data collected in-the-wild with millimeter-scale motion accuracy. Specifically, WIYH includes (1) the Oracle Suite, a wearable data collection kit with an auto-labeling pipeline for accurate motion capture; (2) the WIYH Dataset, featuring over 1,000 hours of multimodal manipulation data across hundreds of skills in diverse real-world scenarios; and (3) extensive annotations and benchmarks supporting tasks from perception to action. Furthermore, experiments based on the WIYH ecosystem show that integrating WIYH's human-centric data improves robotic manipulation success rates from 8% to 60% in cluttered scenes. World In Your Hands provides a foundation for advancing human-centric data collection and cross-embodiment policy learning. All data and hardware design will be open-source. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_24310 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | World In Your Hands: A Large-Scale and Open-Source Ecosystem for Learning Human-Centric Manipulation in the Wild Zheng, Yupeng Peng, Jichao Li, Weize Zheng, Yuhang Li, Xiang Jin, Yujie Wei, Julong Zhang, Guanhua Zheng, Ruiling Cao, Ming Gu, Songen Zou, Zhenhong Li, Kaige Wu, Ke Yang, Mingmin Liu, Jiahao Li, Pengfei Si, Hengjie Zhu, Feiyu Fu, Wang Wang, Likun Yao, Ruiwen Zhao, Jieru Chen, Yilun Ding, Wenchao Robotics We introduce World In Your Hands (WIYH), a large-scale open-source ecosystem comprising over 1,000 hours of human manipulation data collected in-the-wild with millimeter-scale motion accuracy. Specifically, WIYH includes (1) the Oracle Suite, a wearable data collection kit with an auto-labeling pipeline for accurate motion capture; (2) the WIYH Dataset, featuring over 1,000 hours of multimodal manipulation data across hundreds of skills in diverse real-world scenarios; and (3) extensive annotations and benchmarks supporting tasks from perception to action. Furthermore, experiments based on the WIYH ecosystem show that integrating WIYH's human-centric data improves robotic manipulation success rates from 8% to 60% in cluttered scenes. World In Your Hands provides a foundation for advancing human-centric data collection and cross-embodiment policy learning. All data and hardware design will be open-source. |
| title | World In Your Hands: A Large-Scale and Open-Source Ecosystem for Learning Human-Centric Manipulation in the Wild |
| topic | Robotics |
| url | https://arxiv.org/abs/2512.24310 |