MobileH2R: Learning Generalizable Human to Mobile Robot Handover Exclusively from Scalable and Diverse Synthetic Data
Zifan Wang, Ziqing Chen, Junyu Chen, Jilong Wang, Yuxin Yang, Yunze Liu, Xueyi Liu, He Wang, Li Yi
2025Year
1Top-tier citations
Abstract
https://MobileH2R.github.io (a) (b) (c) (d) Figure 1. The overview of MobileH2R. We propose a framework for generalizable human-to-mobile-robot handover, including a scalable pipeline for diverse full-body human motion synthesis (a), an automatic method for producing safe, imitation-friendly demonstrations (b), an efficient 4D imitation learning approach to learn coordinated base-arm actions (c), and successful sim2real transfer (d).
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers1
Ask how each one uses itBuilds on12
- AMASS: Archive of Motion Capture As Surface ShapesNaureen Mahmood, Nima Ghorbani, Nikolaus F. Troje, Gerard Pons-Moll et al.ICCV 2019 · 1,784 citations
- Ego4D: Around the World in 3, 000 Hours of Egocentric VideoKristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis et al.CVPR 2022 · 525 citations
- Guided Motion Diffusion for Controllable Human Motion SynthesisKorrawe Karunratanakul, Konpat Preechakul, Supasorn Suwajanakorn, Siyu TangICCV 2023 · 240 citations
- Language Models Meet World Models: Embodied Experiences Enhance Language ModelsJiannan Xiang, Tianhua Tao, Yi Gu, Tianmin Shu et al.NeurIPS 2023 · 180 citations
- HOI4D: A 4D Egocentric Dataset for Category-Level Human-Object InteractionYunze Liu, Yun Liu, Che Jiang, Kangbo Lyu et al.CVPR 2022 · 126 citations
Related papers
- GenH2R: Learning Generalizable Human-to-Robot Handover via Scalable Simulation, Demonstration, and ImitationZifan Wang, Junyu Chen, Ziqing Chen, Pengwei Xie et al.CVPR 2024 · 15 citations
- Learning Human-to-Robot Handovers from Point CloudsSammy Joe Christen, Wei Yang, Claudia Pérez-D'Arpino, Otmar Hilliges et al.CVPR 2023
- InterMimic: Towards Universal Whole-Body Control for Physics-Based Human-Object InteractionsSirui Xu, Hung Yu Ling, Yu-Xiong Wang, Liang-Yan GuiCVPR 2025
- Learning Physics-Based Full-Body Human Reaching and Grasping from Brief Walking ReferencesYitang Li, Mingxian Lin, Zhuo Lin, Yipeng Deng et al.CVPR 2025
- Adversarial Locomotion and Motion Imitation for Humanoid Policy LearningJiyuan Shi, Xinzhe Liu, Dewei Wang, Ouyang Lu et al.NeurIPS 2025 · 30 citations
