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NYU · embodied AI & robot learning纽约大学 · 具身智能与机器人学习

8 curated papers, code, datasets and hardware from NYU (6 with code), with one-line takeaways.8 个来自纽约大学的精选论文、代码、数据集与硬件(6 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。

By topic:按主题: Manipulation & Dexterous Hands操作与灵巧手 (3) · Tactile & Visuotactile Sensing触觉与视触觉感知 (1) · Locomotion & Humanoids运动控制与人形机器人 (1) · World Models世界模型 (1) · Navigation & Embodied Agents导航与具身智能体 (1) · Robot Learning: RL & Imitation机器人学习:强化学习与模仿学习 (2) · Hardware & Open-Source Robots硬件与开源机器人 (3)

All entries全部条目 (8)

Hardware硬件 2025 · NYU RSS 2025

RUKA: Rethinking the Design of Humanoid Hands with Learning

A human-sized, tendon-driven hand (5 fingers, 15 underactuated DoF) from 3D-printed and off-the-shelf parts; joint-to-actuator control is learned from MANUS-glove mocap data instead of hand-modelled.人手大小的腱驱动灵巧手(5 指、15 个欠驱动自由度),由 3D 打印件和现成零件制成;关节到电机的控制映射用 MANUS 数据手套的动捕数据学习得到,而非手工建模。

BibTeX
@misc{zorin2025ruka,
  title = {{RUKA: Rethinking the Design of Humanoid Hands with Learning}},
  author = {Anya Zorin and Irmak Guzey and Billy Yan and Aadhithya Iyer and Lisa Kondrich and Nikhil X. Bhattasali and Lerrel Pinto},
  year = {2025},
  eprint = {2504.13165},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2504.13165},
}
Paper论文 2024 · NYU, Meta AI

AnySkin: Plug-and-play Skin Sensing for Robotic Touch

A replaceable magnetic tactile skin whose learned policies keep working after the skin is swapped.可更换的磁性触觉皮肤,更换皮肤后训练好的策略仍能继续使用。

BibTeX
@misc{bhirangi2024anyskin,
  title = {{AnySkin: Plug-and-play Skin Sensing for Robotic Touch}},
  author = {Raunaq Bhirangi and Venkatesh Pattabiraman and Enes Erciyes and Yifeng Cao and Tess Hellebrekers and Lerrel Pinto},
  year = {2024},
  eprint = {2409.08276},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2409.08276},
}
Paper论文 2024 · NYU

DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning

Predicts future DINOv2 patch features instead of pixels, so a world model trained on offline data can plan to new visual goals at test time.预测未来的 DINOv2 图像块特征而非像素,使基于离线数据训练的世界模型能在测试时规划到新的视觉目标。

BibTeX
@misc{zhou2024dino,
  title = {{DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning}},
  author = {Gaoyue Zhou and Hengkai Pan and Yann LeCun and Lerrel Pinto},
  year = {2024},
  eprint = {2411.04983},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2411.04983},
}
World Models世界模型planningrepresentationoffline
Paper论文 2024 · NYU, Meta AI

OK-Robot: What Really Matters in Integrating Open-Knowledge Models for Robotics

Combines off-the-shelf open-vocabulary models into a pick-and-drop system that works in real homes without training.组合现成的开放词汇模型,构建无需训练即可在真实家庭中抓取放置的系统。

BibTeX
@misc{liu2024ok,
  title = {{OK-Robot: What Really Matters in Integrating Open-Knowledge Models for Robotics}},
  author = {Peiqi Liu and Yaswanth Orru and Jay Vakil and Chris Paxton and Nur Muhammad Mahi Shafiullah and Lerrel Pinto},
  year = {2024},
  eprint = {2401.12202},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2401.12202},
}
Paper论文 2023 · NYU, Meta

On Bringing Robots Home

Dobb-E collects home demonstrations with a cheap reacher-grabber "stick", pretrains on them, then adapts to a new household task from a few minutes of data.Dobb-E 用低成本的手持夹取“棒”采集家庭示范数据并预训练,在新家庭任务上只需几分钟数据即可适配。

BibTeX
@misc{shafiullah2023bringing,
  title = {{On Bringing Robots Home}},
  author = {Nur Muhammad Mahi Shafiullah and Anant Rai and Haritheja Etukuru and Yiqian Liu and Ishan Misra and Soumith Chintala and Lerrel Pinto},
  year = {2023},
  eprint = {2311.16098},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2311.16098},
}
Manipulation & Dexterous Hands操作与灵巧手home-robotlow-cost-dataimitationopen-source
Paper论文 2022 · NYU NeurIPS 2022

Behavior Transformers: Cloning $k$ modes with one stone

BeT — clusters actions into k bins plus a continuous offset so a transformer can imitate multimodal demonstrations instead of averaging them.BeT:把动作聚成 k 个类别再加连续偏移,让 Transformer 能模仿多模态示教,而不是把不同模式平均掉。

BibTeX
@misc{shafiullah2022behavior,
  title = {{Behavior Transformers: Cloning $k$ modes with one stone}},
  author = {Nur Muhammad Mahi Shafiullah and Zichen Jeff Cui and Ariuntuya Altanzaya and Lerrel Pinto},
  year = {2022},
  eprint = {2206.11251},
  archivePrefix = {arXiv},
  primaryClass = {cs.LG},
  url = {https://arxiv.org/abs/2206.11251},
}
Paper论文 2021 · NYU, Meta AI ICLR 2022

Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning

DrQ-v2 - a simple model-free actor-critic with image augmentation that learns continuous control from pixels (incl. humanoid tasks in the DeepMind Control Suite) on a single GPU; a common visual-RL baseline.DrQ-v2:带图像增强的简单无模型 actor-critic,单 GPU 即可从像素学习连续控制(包括 DeepMind Control Suite 的人形任务),是常用的视觉强化学习基线。

BibTeX
@misc{yarats2021mastering,
  title = {{Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning}},
  author = {Denis Yarats and Rob Fergus and Alessandro Lazaric and Lerrel Pinto},
  year = {2021},
  eprint = {2107.09645},
  archivePrefix = {arXiv},
  primaryClass = {cs.AI},
  url = {https://arxiv.org/abs/2107.09645},
}
Robot Learning: RL & Imitation机器人学习:强化学习与模仿学习Humanoid人形simpixelsdata-augmentationoff-policy
Hardware硬件 2019 · MPI-IS, NYU (Open Dynamic Robot Initiative)

An Open Torque-Controlled Modular Robot Architecture for Legged Locomotion Research

The open-source Solo quadruped and its modular torque-controlled actuators, built from off-the-shelf and 3D-printed parts so labs can reproduce a dynamic legged robot.开源四足机器人 Solo 及其模块化力矩控制关节,采用现成件和 3D 打印件,便于各实验室复现动态腿式机器人。

BibTeX
@misc{grimminger2019open,
  title = {{An Open Torque-Controlled Modular Robot Architecture for Legged Locomotion Research}},
  author = {Felix Grimminger and Avadesh Meduri and Majid Khadiv and Julian Viereck and Manuel Wüthrich and Maximilien Naveau and Vincent Berenz and Steve Heim and Felix Widmaier and Thomas Flayols and Jonathan Fiene and Alexander Badri-Spröwitz and Ludovic Righetti},
  year = {2019},
  eprint = {1910.00093},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/1910.00093},
}
Hardware & Open-Source Robots硬件与开源机器人Locomotion & Humanoids运动控制与人形机器人Quadruped / legged四足 / 足式quadrupedopen-sourcetorque-controllow-cost