arXivDaily arXiv每日学术速递 周一至周五更新

视觉与机器人

机器人 / 具身智能

机器人、具身智能、机器人学习、操作、导航和具身世界模型。

2026-06-24 至 2026-06-24 共收录 15 信号源:cs.RO, cs.AI, cs.CV, cs.LG

1. 机器人操作 7 篇

2512.00324 2026-06-24 cs.RO cs.CV cs.HC 版本更新 88%

MILE: A Mechanically Isomorphic Hand Exoskeleton and Visuotactile Robotic Hand for Data Collection in Dexterous Manipulation

MILE:一种用于灵巧操作的指尖视觉触觉传感的机械同构外骨骼数据采集系统

Jinda Du, Jieji Ren, Qiaojun Yu, Ningbin Zhang, Yu Deng, Xingyu Wei, Yufei Liu, Guoying Gu, Xiangyang Zhu

机构 * State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China(机械系统与振动国家重点实验室,上海交通大学机械工程学院,上海200240,中国) Shanghai Key Laboratory of Intelligent Robotics, Shanghai Jiao Tong University, Shanghai 200240, China(智能机器人上海重点实验室,上海交通大学,上海200240,中国) Shanghai Artificial Intelligence Laboratory, Shanghai, China(上海人工智能实验室,上海,中国) Humanoid Robot (Shanghai) Co., Ltd., Shanghai, China(上海人形机器人有限公司,上海,中国)

专题命中 机器人操作 :manipulation(title,abstract);robotic(title,abstract);分类 cs.RO、cs.CV

AI总结 针对现有灵巧操作数据采集系统运动重定向不准确、效率低、缺乏高分辨率指尖触觉传感的问题,提出MILE系统,通过从人手到外骨骼再到机械手的机械同构设计,实现无重定向精确控制,并集成指尖视觉触觉模块,采集多模态数据集,显著提升遥操作成功率。

Comments 18 pages including supplementary material. Main manuscript and supplementary material included in this version

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2503.05226 2026-06-24 cs.RO cs.AI 版本更新 88%

Reward-Centered ReST-MCTS: A Robust Decision-Making Framework for Robotic Manipulation in High Uncertainty Environments

以奖励为中心的ReST-MCTS:高不确定性环境下机器人操作的鲁棒决策框架

Xibai Wang

机构 * Xibai Wang(王西拜)

专题命中 机器人操作 :manipulation(title,abstract);robotic(title,abstract);分类 cs.RO、cs.AI

AI总结 提出Reward-Centered ReST-MCTS框架,通过分解中间反馈为中心信号并引导搜索,解决高不确定性环境下MCTS因稀疏奖励和噪声导致的决策脆弱性问题,实验验证其在同骨干VLA上的鲁棒性。

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2505.21916 2026-06-24 cs.RO 版本更新 83%

Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials

Prior Reinforce: 有限试验下的目标条件动态操控

Yihang Hu, Pingyue Sheng, Yuyang Liu, Shengjie Wang, Yang Gao

机构 * IIIS, Tsinghua University(清华大学智能学院) Shanghai Qi Zhi Institute(上海启智研究院) Spirit AI

专题命中 机器人操作 :manipulation(title,abstract);robotics(abstract);分类 cs.RO

AI总结 提出Prior Reinforce框架,利用条件扩散模型从少量演示学习运动流形,并在低维条件空间通过反馈驱动优化适应新目标,实现少至十次试验内的动态操控。

Comments Accepted to the 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2026)

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2504.17070 2026-06-24 cs.RO cs.AI 版本更新 73%

MuTRAP: Multi-trigger Trojans Attacking Robot Task Planning Systems

MuTRAP: 攻击机器人任务规划系统的多触发器木马

Mohaiminul Al Nahian, Zainab Altaweel, David Reitano, Sabbir Ahmed, Shiqi Zhang, Adnan Siraj Rakin

机构 * Binghamton University (SUNY)(宾夕法尼亚州立大学布林顿分校)

专题命中 机器人操作 :robotics(abstract);robotic(abstract);分类 cs.RO、cs.AI

AI总结 提出首个针对LLM辅助机器人任务规划器的多触发器木马攻击MuTRAP,通过少量任务特定参数注入后门,并优化触发器词以激活特定恶意行为,揭示当前基于LLM的规划器的安全漏洞。

Comments Accepted for publication at the 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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2510.00814 2026-06-24 cs.RO 版本更新 70%

RTFF: Random-to-Target Fabric Flattening Policy using Dual-Arm Manipulator

RTFF:使用双臂机械手的随机到目标织物展平策略

Kai Tang, Dipankar Bhattacharya, Hang Xu, Fuyuki Tokuda, Norman C. Tien, Kazuhiro Kosuge

机构 * Department of Electrical and Electronic Engineering, Faculty of Engineering, The University of Hong Kong(香港大学电子与电气工程系) Dyson School of Design Engineering, Imperial College London(帝国理工学院设计工程学院) Unprecedented-scale Data Analytics Center, Tohoku University(东北大学大规模数据分析中心) Graduate School of Information Sciences, Tohoku University(东北大学信息科学研究生院) Department of Mechanical Engineering, City University of Hong Kong(香港城市大学机械工程系)

专题命中 机器人操作 :manipulation(abstract);robotic(abstract);分类 cs.RO

AI总结 提出随机到目标织物展平任务,通过模板网格对齐和混合模仿学习-视觉伺服策略,实现双臂机器人对任意目标姿态的织物展平与对齐。

Comments 8 pages, 7 figures, conference

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2603.12120 2026-06-24 cs.RO cs.AI cs.CV 版本更新 67%

CRAFT: A Tendon-Driven Hand with Hybrid Hard-Soft Compliance

CRAFT: 一种具有混合硬-软柔顺性的腱驱动手

Leo Lin, Shivansh Patel, Jay Moon, Svetlana Lazebnik, Unnat Jain

机构 * University of Illinois Urbana-Champaign(伊利诺伊大学厄巴纳-香槟分校) UC Irvine(uci)

专题命中 机器人操作 :manipulation(abstract);分类 cs.RO、cs.AI、cs.CV

AI总结 提出CRAFT手,一种腱驱动拟人手,通过关节软材料与连杆刚性结合实现混合柔顺性,在接触丰富操作中提升强度、耐久性和抓取能力,覆盖Feix分类全部33种抓取。

Comments In RSS 2026. Website: https://roboticsconference.org/program/papers/192/

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2603.04560 2026-06-24 cs.RO 版本更新 57%

From Local Corrections to Generalized Skills: Improving Neuro-Symbolic Policies with MEMO

从局部修正到通用技能:利用MEMO改进神经符号策略

Benjamin A. Christie, Yinlong Dai, Mohammad Bararjanianbahnamiri, Simon Stepputtis, Dylan P. Losey

机构 * Collab Dept. of Mechanical Engineering, Virginia Tech, Blacksburg, USA.(机械工程系,弗吉尼亚理工学院,黑斯堡,美国) TEA Lab(TEA实验室)

专题命中 机器人操作 :manipulation(abstract);分类 cs.RO

AI总结 针对机器人神经符号策略中技能不足的问题,提出MEMO框架,通过收集、聚类和改写多用户自然语言修正,构建检索增强的技能手册,动态扩展技能库,实现新任务泛化。

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2. 具身导航 5 篇

2604.17473 2026-06-24 cs.CV cs.AI 版本更新 84%

Dual-Anchoring: Addressing State Drift in Vision-Language Navigation

双锚定:解决视觉语言导航中的状态漂移问题

Kangyi Wu, Pengna Li, Kailin Lyu, Xi Lin, Lin Zhao, Qingrong He, Jinjun Wang, Jianyi Liu

机构 * National Key Laboratory of Human-Machine Hybrid Augmented Intelligence(人机混合增强智能国家重点实验室) National Engineering Research Center for Visual Information and Applications(视觉信息与应用国家工程研究中心) Institute of Artificial Intelligence and Robotics(人工智能与机器人研究院) Xi’an Jiaotong University(西安交通大学) Institute of Automation, Chinese Academy of Sciences(中国科学院自动化研究所) School of Artificial Intelligence, University of Chinese Academy of Sciences(中国科学院大学人工智能学院) Johns Hopkins University(约翰霍普金斯大学) Joy Future Academy, JD(京东探索研究院)

专题命中 具身导航 :navigation(title,abstract);world model(abstract);分类 cs.AI、cs.CV

AI总结 提出双锚定框架,通过指令进度锚定和记忆地标锚定分别解决进度漂移和记忆漂移,显著提升长场景导航成功率。

Comments Accepted by ECCV26

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2602.23324 2026-06-24 physics.bio-ph cond-mat.stat-mech q-bio.QM 版本更新 78%

Discrete turn strategies emerge in information-limited navigation

离散转向策略在信息受限导航中的涌现

Jose M. Betancourt, Matthew P. Leighton, Thierry Emonet, Benjamin B. Machta, Michael C. Abbott

专题命中 具身导航 :navigation(title,abstract)

AI总结 通过信息速率最大化框架,发现无方向信息时离散动作策略优于连续转向,并揭示了最优策略随信息量增加的系列相变。

Comments 7 pages, 4 figures, plus appendices. v2 has extended introduction, new figures, minor corrections

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2512.08766 2026-06-24 physics.flu-dyn 版本更新 78%

Optimal navigation in two-dimensional flows: Control theory and reinforcement learning

二维流动中的最优导航:控制理论与强化学习

Vladimir Parfenyev

专题命中 具身导航 :navigation(title,abstract)

AI总结 研究在二维流动中,受平流和自推进的智能体(如漂浮无人机)的最小时间路径问题,利用最优控制理论求解,并应用强化学习(Q学习和演员-评论家算法)设计鲁棒导航策略,在规则流中接近最优解,在湍流中偏差增大,且粗粒化训练可泛化至全流场。

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2602.22346 2026-06-24 cs.RO 版本更新 70%

A Pairwise Human-Human Interaction Detection and Recognition Framework for Mobile Service Robots

面向移动服务机器人的成对人-人交互检测与识别框架

Mengyu Liang, Iolanda Leite, Sarah Gillet

机构 * Wallenberg AI, Autonomous Systems and Software Program – Humanity and Society(瓦伦贝格人工智能、自主系统和软件计划—人类与社会)

专题命中 具身导航 :navigation(abstract);robotic(abstract);分类 cs.RO

AI总结 提出两阶段框架,先利用轻量几何和运动线索识别交互对,再通过关系网络分类交互类型,在JRDB数据集上以较低计算成本取得竞争性能,并在CAD和零样本数据集上验证泛化性。

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2605.19257 2026-06-24 cs.RO 版本更新 57%

PRISM-SLAM: Probabilistic Ray-Grounded Inference for Scale-aware Metric SLAM

PRISM-SLAM: 面向尺度感知度量SLAM的概率射线基础推理

Eunsoo Im, Gyeonggwan Lee, Seunghwan Hong, Junghun Suh

机构 * KakaoMobility, South Korea(韩国 KakaoMobility)

专题命中 具身导航 :robotic(abstract);分类 cs.RO

AI总结 提出PRISM-SLAM框架,通过将视觉基础模型先验集成到贝叶斯因子图中,利用Plücker射线距离因子和动态场景不确定性门控机制,实现无尺度漂移的实时单目度量SLAM。

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3. 具身推理 1 篇

2606.02800 2026-06-24 cs.CV cs.AI cs.LG cs.MM cs.RO 版本更新 85%

Cosmos 3: Omnimodal World Models for Physical AI

Cosmos 3:面向物理AI的全模态世界模型

NVIDIA, :, Aditi, Niket Agarwal, Arslan Ali, Jon Allen, Martin Antolini, Adeline Aubame, Alisson Azzolini, Junjie Bai, Maciej Bala, Yogesh Balaji, Josh Bapst, Aarti Basant, Mukesh Beladiya, Mohammad Qazim Bhat, Zaid Pervaiz Bhat, Dan Blick, Vanni Brighella, Han Cai, Tiffany Cai, Eric Cameracci, Jiaxin Cao, Yulong Cao, Mark Carlson, Carlos Casanova, Ting-Yun Chang, Yan Chang, Yu-Wei Chao, Prithvijit Chattopadhyay, Roshan Chaudhari, Chieh-Yun Chen, Junyu Chen, Ke Chen, Qizhi Chen, Wenkai Chen, Xiaotong Chen, Yu Chen, An-Chieh Cheng, Click Cheng, Xiu Chia, Jeana Choi, Chaeyeon Chung, Wenyan Cong, Yin Cui, Magdalena Dadela, Nalin Dadhich, Wenliang Dai, Joyjit Daw, Alperen Degirmenci, Rodrigo Vieira Del Monte, Robert Denomme, Sameer Dharur, Marco Di Lucca, Ke Ding, Wenhao Ding, Yifan Ding, Yuzhu Dong, Nicole Drumheller, Yilun Du, Aigul Dzhumamuratova, Aleksandr Efitorov, Hamid Eghbalzadeh, Naomi Eigbe, Imad El Hanafi, Hassan Eslami, Benedikt Falk, Jiaojiao Fan, Jim Fan, Amol Fasale, Sergiy Fefilatyev, Liang Feng, Francesco Ferroni, Sanja Fidler, Xiao Fu, Vikram Fugro, Prashant Gaikwad, TJ Galda, Katelyn Gao, Yihuai Gao, Wenhang Ge, Sreyan Ghosh, Arushi Goel, Vivek Goel, Akash Gokul, Rama Govindaraju, Jinwei Gu, Miguel Guerrero, Elfie Guo, Aryaman Gupta, Siddharth Gururani, Hugo Hadfield, Song Han, Ankur Handa, Zekun Hao, Mohammad Harrim, Ali Hassani, Nathan Hayes-Roth, Yufan He, Chris Helvig, Cyrus Hogg, Madison Huang, Michael Huang, Sophia Huang, Yufan Huang, Jacob Huffman, DeLesley Hutchins, Suneel Indupuru, Boris Ivanovic, Arihant Jain, Joel Jang, Ryan Ji, Yanan Jian, Dongfu Jiang, Jingyi Jin, Atharva Joshi, Nikhilesh Joshi, Pranjali Joshi, Andy Ju, Jaehun Jung, Weiwei Kang, Scott Kassekert, Jan Kautz, Ashna Khetan, Julia Kiczka, Slawek Kierat, Gwanghyun Kim, Kuno Kim, Sunny Kim, Kezhi Kong, Xin Kong, Zhifeng Kong, Tomasz Kornuta, Egor Krivov, Hui Kuang, Saurav Kumar, Chia-Wen Kuo, George Kurian, Wojciech Kutak, JF Lafleche, Himangshu Lahkar, Omar Laymoun, Jayjun Lee, Sanggil Lee, Gabriele Leone, Boyi Li, Freya Li, Jiajun Li, Jinfeng Li, Ling Li, Pengcheng Li, Shangru Li, Tingle Li, Xiaolong Li, Xuan Li, Zhaoshuo Li, Zhiqi Li, Hao Liang, Maosheng Liao, Chen-Hsuan Lin, Tsung-Yi Lin, Ming-Yu Liu, Sifei Liu, Zihan Liu, Hai Loc Lu, Xiangyu Lu, Alice Luo, Ruipu Luo, Wenjie Luo, Jiangran Lyu, Martin Ding Ma, Nic Ma, Qianli Ma, Dawid Majchrowski, Louis Marcoux, Miguel Martin, Qing Miao, Ashkan Mirzaei, Shreyas Misra, Kaichun Mo, Durra Mohsin, Hyejin Moon, Pawel Morkisz, Saeid Motiian, Kirill Motkov, Seungjun Nah, Yashraj Narang, Deepak Narayanan, Thabang Ngazimbi, Julian Ouyang, Shubham Pachori, David Page, Yatian Pang, Sehwi Park, Mahesh Patekar, Mostofa Patwary, Marco Pavone, Trung Pham, Wei Ping, Soha Pouya, Shrimai Prabhumoye, Varun Praveen, Delin Qu, Hesam Rabeti, Morteza Ramezanali, Marilyn Reeb, Xuanchi Ren, Kristen Rumley, Wojciech Rymer, Jun Saito, Yeongho Seol, John Shao, Piyush Shekdar, Tianwei Shen, Humphrey Shi, Min Shi, Stella Shi, Kevin Shih, Mohammad Shoeybi, Mateusz Sieniawski, Shuran Song, Alexander Sotelo, Amir Sotoodeh, Sunil Srinivasa, Vignesh Srinivasakumar, Bartosz Stefaniak, Rahul Heinrich Steiger, Shangkun Sun, Jiaxiang Tang, Shitao Tang, Yangyang Tang, Yue Tang, Tolou Tavakkoli, Kayley Ting, Krzysztof Tomala, Wei-Cheng Tseng, Jibin Varghese, Sergei Vasilev, Thomas Volk, Raju Wagwani, Roger Waleffe, Andrew Z. Wang, Boxiang Wang, Haoxiang Wang, Qiao Wang, Shihao Wang, Shijie Wang, Ting-Chun Wang, Yan Wang, Yu Wang, Rohit Watve, David Wehr, Fangyin Wei, Xinshuo Weng, Jay Zhangjie Wu, Kedi Wu, Hongchi Xia, Summer Xiao, Tianjun Xiao, Kevin Xie, Daguang Xu, Jiashu Xu, Mengyao Xu, Ruqing Xu, Xingqian Xu, Yao Xu, Dinghao Yang, Dong Yang, Hans Yang, Xiaodong Yang, Xuning Yang, Yichu Yang, Yurong You, Zhiding Yu, Hao Yuan, Simon Yuen, Xiaohui Zeng, Pengcuo Zeren, Cindy Zha, Haotian Zhang, Jenny Zhang, Jing Zhang, Liangkai Zhang, Paris Zhang, Shun Zhang, Xuanmeng Zhang, Zhizheng Zhang, Ann Zhao, Yilin Zhao, Yuliya Zhautouskaya, Charles Zhou, Fengzhe Zhou, Shilin Zhu, Yuke Zhu, Dima Zhylko, Artur Zolkowski

机构 * NVIDIA

专题命中 具身推理 :world model(title,abstract);embodied agent(abstract);分类 cs.RO、cs.AI、cs.CV

AI总结 提出基于统一混合Transformer架构的全模态世界模型Cosmos 3,联合处理语言、图像、视频、音频和动作序列,在理解和生成任务上达到新最优,为具身智能体提供可扩展的通用骨干。

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4. 模仿学习与强化学习 1 篇

2509.21543 2026-06-24 cs.RO 版本更新 79%

Self-CriTeach: LLM Self-Teaching and Self-Critiquing for Improving Robotic Planning via Automated Domain Generation

Self-CriTeach: LLM 自我教学与自我批评用于通过自动领域生成提升机器人规划

Jinbang Huang, Zhiyuan Li, Yuanzhao Hu, Zhanguang Zhang, Mark Coates, Xingyue Quan, Yingxue Zhang

机构 * Huawei Noah's Ark Lab(华为诺亚实验室) University of Toronto(多伦多大学) University of British Columbia(不列颠哥伦比亚大学) McGill University(麦吉尔大学)

专题命中 模仿学习与强化学习 :robotic(title,abstract);分类 cs.RO

AI总结 本文提出Self-CriTeach框架,通过LLM自动生成符号规划领域,用于自我教学生成规划问题-计划对及自我批评生成结构化奖励信号,提升机器人规划性能与泛化能力。

Comments International Conference on Machine Learning (ICML) 2026

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5. 其他机器人 1 篇

2512.19755 2026-06-24 cond-mat.soft math-ph math.MP 版本更新 50%

The mechanics of anisotropic active plates with applications to cell alignment on curved substrates

各向异性活性板的力学及其在弯曲基底上细胞排列中的应用

Gabriele Fioretto, Giulio Lucci, Chiara Giverso, Luigi Preziosi

专题命中 其他机器人 :robotics(abstract)

AI总结 基于Föppl-von Kármán极限,发展活性各向异性板的连续介质力学框架,通过渐近展开推导耦合平衡方程,应用于弯曲基底诱导的细胞排列,预测从垂直到平行的超临界分岔,并解释不同细胞类型的实验现象。

Journal ref Journal of the Mechanics and Physics of Solids, vol. 216, 2026

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