CUHK · embodied AI & robot learning香港中文大学 · 具身智能与机器人学习
3 curated papers, code, datasets and hardware from CUHK (1 with code), with one-line takeaways.3 个来自香港中文大学的精选论文、代码、数据集与硬件（1 个附代码），均配一句话要点。
Labs are matched from each entry's affiliation field by simple name rules (data/labs.yaml); joint work appears under every lab named. Only curated entries are listed, because daily arXiv papers carry no affiliations.机构由每个条目的机构字段按名称规则匹配（data/labs.yaml），合作工作会出现在所有署名机构下。仅列出精选条目，因为每日 arXiv 论文不含机构信息。
Open-source whole-body humanoid teleoperation — an arm exoskeleton plus motion-sensing gloves, with a foot pedal steering an RL walking controller; the cockpit hardware costs about US$500.开源的人形机器人全身遥操作系统：手臂外骨骼加动作捕捉手套，脚踏板驱动强化学习行走控制器；整套座舱硬件约 500 美元。
@misc{ben2025homie,
title = {{HOMIE: Humanoid Loco-Manipulation with Isomorphic Exoskeleton Cockpit}},
author = {Qingwei Ben and Feiyu Jia and Jia Zeng and Junting Dong and Dahua Lin and Jiangmiao Pang},
year = {2025},
eprint = {2502.13013},
archivePrefix = {arXiv},
primaryClass = {cs.RO},
url = {https://arxiv.org/abs/2502.13013},
}
An early survey of VLA models, sorting them into component work (vision, language, world models), low-level control policies and high-level task planners, plus datasets, simulators and benchmarks; companion paper list.较早的 VLA 综述：把相关工作分为组件研究（视觉、语言、世界模型等）、底层控制策略与高层任务规划器，并汇总数据集、仿真器与基准；附配套论文列表。
@misc{ma2024survey,
title = {{A Survey on Vision-Language-Action Models for Embodied AI}},
author = {Yueen Ma and Zixing Song and Yuzheng Zhuang and Jianye Hao and Irwin King},
year = {2024},
eprint = {2405.14093},
archivePrefix = {arXiv},
primaryClass = {cs.RO},
url = {https://arxiv.org/abs/2405.14093},
}
Seer forecasts the next visual state and feeds it to an inverse dynamics model that outputs actions, trained end to end and pretrained on DROID; reports 4.28 avg. length on CALVIN ABC-D plus LIBERO and real-robot gains.Seer 先预测未来视觉状态，再由逆动力学模型据此输出动作，端到端训练并在 DROID 上预训练；报告 CALVIN ABC-D 平均任务长度 4.28，在 LIBERO-LONG 和真机任务上也有提升。
@misc{tian2024predictive,
title = {{Predictive Inverse Dynamics Models are Scalable Learners for Robotic Manipulation}},
author = {Yang Tian and Sizhe Yang and Jia Zeng and Ping Wang and Dahua Lin and Hao Dong and Jiangmiao Pang},
year = {2024},
eprint = {2412.15109},
archivePrefix = {arXiv},
primaryClass = {cs.RO},
url = {https://arxiv.org/abs/2412.15109},
}