{"ID":2860971,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.03022","arxiv_id":"2510.03022","title":"HumanoidExo: Scalable Whole-Body Humanoid Manipulation via Wearable Exoskeleton","abstract":"A significant bottleneck in humanoid policy learning is the acquisition of large-scale, diverse datasets, as collecting reliable real-world data remains both difficult and cost-prohibitive. To address this limitation, we introduce HumanoidExo, a novel system that transfers human motion to whole-body humanoid data. HumanoidExo offers a high-efficiency solution that minimizes the embodiment gap between the human demonstrator and the robot, thereby tackling the scarcity of whole-body humanoid data. By facilitating the collection of more voluminous and diverse datasets, our approach significantly enhances the performance of humanoid robots in dynamic, real-world scenarios. We evaluated our method across three challenging real-world tasks: table-top manipulation, manipulation integrated with stand-squat motions, and whole-body manipulation. Our results empirically demonstrate that HumanoidExo is a crucial addition to real-robot data, as it enables the humanoid policy to generalize to novel environments, learn complex whole-body control from only five real-robot demonstrations, and even acquire new skills (i.e., walking) solely from HumanoidExo data.","short_abstract":"A significant bottleneck in humanoid policy learning is the acquisition of large-scale, diverse datasets, as collecting reliable real-world data remains both difficult and cost-prohibitive. To address this limitation, we introduce HumanoidExo, a novel system that transfers human motion to whole-body humanoid data. Huma...","url_abs":"https://arxiv.org/abs/2510.03022","url_pdf":"https://arxiv.org/pdf/2510.03022v1","authors":"[\"Rui Zhong\",\"Yizhe Sun\",\"Junjie Wen\",\"Jinming Li\",\"Chuang Cheng\",\"Wei Dai\",\"Zhiwen Zeng\",\"Huimin Lu\",\"Yichen Zhu\",\"Yi Xu\"]","published":"2025-10-03T14:05:16Z","proceeding":"cs.RO","tasks":"[\"cs.RO\"]","methods":"[]","has_code":false}