机器人 / 具身智能

Sim-to-Real Transfer of Robot Learning with Variable Length Inputs

Vibhavari Dasagi, Robert Lee, Serena Mou, Jake Bruce, Niko Sünderhauf, Jürgen Leitner

专题命中 机器人数据与评测 ：robot learning(title)；manipulation(abstract)；robotic(abstract)；分类 cs.LG

The blockchain: a new framework for robotic swarm systems

Eduardo Castelló Ferrer

专题命中 机器人数据与评测 ：robotic(title,abstract)；robotics(abstract)；分类 cs.RO

Comments 12 pages, 13 figures

Jacquard: A Large Scale Dataset for Robotic Grasp Detection

Amaury Depierre, Emmanuel Dellandréa, Liming Chen

专题命中 机器人数据与评测 ：robotic(title,abstract)；robotics(abstract)；分类 cs.RO

Journal ref IEEE/RSJ International Conference on Intelligent Robots and Systems, Oct 2018, Madrid, Spain

The Limits and Potentials of Deep Learning for Robotics

Niko Sünderhauf, Oliver Brock, Walter Scheirer, Raia Hadsell, Dieter Fox, Jürgen Leitner, Ben Upcroft, Pieter Abbeel, Wolfram Burgard, Michael Milford, Peter Corke

专题命中 机器人数据与评测 ：robotics(title,abstract)；robotic(abstract)；分类 cs.RO

Unsupervised robotic sorting: Towards autonomous decision making robots

Joris Guérin, Stéphane Thiery, Eric Nyiri, Olivier Gibaru

专题命中 机器人数据与评测 ：robotic(title,abstract)；robotics(abstract)；分类 cs.RO

Comments Paper published in International Journal of Artificial Intelligence and Applications (IJAIA), March 2018, Volume 9, Number 2 17 pages, 5 figures, 7 tables. arXiv admin note: text overlap with arXiv:1707.01700

Journal ref International Journal of Artificial Intelligence and Applications (IJAIA), March 2018, Volume 9, Number 2

Behaviour Trees for Evolutionary Robotics

Kirk Y. W. Scheper, Sjoerd Tijmons, Coen C. de Visser, Guido C. H. E. de Croon

专题命中 机器人数据与评测 ：robotics(title,abstract)；robotic(abstract)；分类 cs.RO

Comments Preprint version of article accepted for publication in Artificial Life, MIT Press. http://www.mitpressjournals.org/loi/artl

Simulation leagues: Enabling replicable and robust investigation of complex robotic systems

David M Budden, Peter Wang, Oliver Obst, Mikhail Prokopenko

专题命中 机器人数据与评测 ：robotic(title,abstract)；robotics(abstract)；分类 cs.RO

Comments 9 pages, 4 figures. arXiv admin note: text overlap with arXiv:1403.4023

Proceedings of the Fifth International Workshop on Domain-Specific Languages and Models for Robotic Systems (DSLRob 2014)

Luca Gherardi, Nico Hochgeschwender, Christian Schlegel, Ulrik Pagh Schultz, Serge Stinckwich

专题命中 机器人数据与评测 ：robotic(title,abstract)；robotics(abstract)；分类 cs.RO

CAD-based approach for identification of elasto-static parameters of robotic manipulators

Alexandr Klimchik, Anatol Pashkevich, Damien Chablat

专题命中 机器人数据与评测 ：robotic(title,abstract)；robotics(abstract)；分类 cs.RO

Comments arXiv admin note: substantial text overlap with arXiv:0909.1460

Journal ref Finite Elements in Analysis and Design 75 (2013) 19-30

Proceedings of the Third International Workshop on Domain-Specific Languages and Models for Robotic Systems (DSLRob 2012)

Christian Schlegel, Ulrik P. Schultz, Serge Stinckwich

专题命中 机器人数据与评测 ：robotic(title,abstract)；robotics(abstract)；分类 cs.RO

Comments Index submission

ReaDy-Go: Real-to-Sim Dynamic 3D Gaussian Splatting Simulation for Environment-Specific Visual Navigation with Moving Obstacles

ReaDy-Go: 面向动态障碍物环境特定视觉导航的实到仿动态3D高斯泼溅仿真

Seungyeon Yoo, Youngseok Jang, Dabin Kim, Youngsoo Han, Seungwoo Jung, H. Jin Kim

机构 * Department of Aerospace Engineering, Seoul National University（首尔国立大学航空航天工程系） ； InnoCORE AI-Transformed Aerospace Research Center, KAIST（韩国科学技术院（KAIST）人工智能赋能航空航天研究中心） 纠错

专题命中 机器人数据与评测 ：navigation(title,abstract)；分类 cs.RO、cs.AI、cs.CV；robotics(comments)

AI总结 提出ReaDy-Go仿真管线，通过将静态3D高斯场景与动态人体高斯障碍物结合生成逼真动态场景，并训练导航策略，有效缩小仿真到现实的差距并处理移动障碍物。

Comments Accepted by IEEE Robotics and Automation Letters (RA-L). Project page: https://syeon-yoo.github.io/ready-go-site/

Permissive Safety Through Trusted Inference: Verifiable Belief-Space Neural Safety Filters for Assured Interactive Robotics

通过可信推理实现许可安全：可验证的信念空间神经安全滤波器用于保证交互式机器人

Haimin Hu

机构 * Department of Computer Science, Johns Hopkins University, USA（约翰霍普金斯大学计算机科学系） 纠错

专题命中 机器人数据与评测 ：robotics(title,abstract)；分类 cs.RO、cs.AI、cs.LG

AI总结 针对交互式机器人中人类不确定性带来的安全问题，提出一种基于共形预测的信念空间安全滤波器验证方法，在考虑推理可靠性的前提下保证高概率安全，并减少保守性。

Comments Accepted to the 17th World Symposium on the Algorithmic Foundations of Robotics (WAFR 2026)

Benchmarking the Sim-to-Real Gap in Cloth Manipulation

在织物操控中评估仿真到现实的差距基准测试

David Blanco-Mulero, Oriol Barbany, Gokhan Alcan, Adrià Colomé, Carme Torras, Ville Kyrki

专题命中 机器人数据与评测 ：manipulation(title,abstract)；分类 cs.RO、cs.CV、cs.LG；robotics(comments)

AI总结 本文提出一个开源基准数据集，用于评估织物操控中仿真与现实之间的差距，测试四个主流模拟器的性能与稳定性。

Comments Accepted to IEEE Robotics and Automation Letters (RA-L). 8 pages, 6 figures. Supplementary material available at https://sites.google.com/view/cloth-sim2real-benchmark

Multi-Step Guided Diffusion for Image Restoration on Edge Devices: Toward Lightweight Perception in Embodied AI

Aditya Chakravarty

专题命中 机器人数据与评测 ：embodied AI(title,abstract)；分类 cs.RO、cs.CV、cs.LG

Comments Accepted in CVPR 2025 Embodied AI Workshop

DR-MPC: Deep Residual Model Predictive Control for Real-world Social Navigation

James R. Han, Hugues Thomas, Jian Zhang, Nicholas Rhinehart, Timothy D. Barfoot

专题命中 机器人数据与评测 ：navigation(title,abstract)；分类 cs.RO、cs.AI、cs.LG；robotics(comments)

Comments 8 pages, 8 figures, accepted to IEEE Robotics and Automation Letters (RA-L) February 2025

Think Step by Step: Chain-of-Gesture Prompting for Error Detection in Robotic Surgical Videos

Zhimin Shao, Jialang Xu, Danail Stoyanov, Evangelos B. Mazomenos, Yueming Jin

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.AI、cs.CV；robotics(journal_ref)

Comments 8 pages, 4 figures

Journal ref IEEE Robotics and Automation Letters, vol. 9, no. 12, pp. 11513-11520, Dec. 2024

Constrained Equation Learner Networks for Precision-Preserving Extrapolation of Robotic Skills

Hector Perez-Villeda, Justus Piater, Matteo Saveriano

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.AI、cs.LG；robotics(comments)

Comments 18 pages, 10 figures. To be submitted to IEEE Transactions on Robotics (T-RO)

RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Xi Chen, Krzysztof Choromanski, Tianli Ding, Danny Driess, Avinava Dubey, Chelsea Finn, Pete Florence, Chuyuan Fu, Montse Gonzalez Arenas, Keerthana Gopalakrishnan, Kehang Han, Karol Hausman, Alexander Herzog, Jasmine Hsu, Brian Ichter, Alex Irpan, Nikhil Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Isabel Leal, Lisa Lee, Tsang-Wei Edward Lee, Sergey Levine, Yao Lu, Henryk Michalewski, Igor Mordatch, Karl Pertsch, Kanishka Rao, Krista Reymann, Michael Ryoo, Grecia Salazar, Pannag Sanketi, Pierre Sermanet, Jaspiar Singh, Anikait Singh, Radu Soricut, Huong Tran, Vincent Vanhoucke, Quan Vuong, Ayzaan Wahid, Stefan Welker, Paul Wohlhart, Jialin Wu, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.CV、cs.LG；robotics(comments)

Comments Website: https://robotics-transformer.github.io/

IROS 2019 Lifelong Robotic Vision Challenge -- Lifelong Object Recognition Report

Qi She, Fan Feng, Qi Liu, Rosa H. M. Chan, Xinyue Hao, Chuanlin Lan, Qihan Yang, Vincenzo Lomonaco, German I. Parisi, Heechul Bae, Eoin Brophy, Baoquan Chen, Gabriele Graffieti, Vidit Goel, Hyonyoung Han, Sathursan Kanagarajah, Somesh Kumar, Siew-Kei Lam, Tin Lun Lam, Liang Ma, Davide Maltoni, Lorenzo Pellegrini, Duvindu Piyasena, Shiliang Pu, Debdoot Sheet, Soonyong Song, Youngsung Son, Zhengwei Wang, Tomas E. Ward, Jianwen Wu, Meiqing Wu, Di Xie, Yangsheng Xu, Lin Yang, Qiaoyong Zhong, Liguang Zhou

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.CV、cs.LG；robotics(comments)

Comments 9 pages, 11 figures, 3 tables, accepted into IEEE Robotics and Automation Magazine. arXiv admin note: text overlap with arXiv:1911.06487

CityLearn: Diverse Real-World Environments for Sample-Efficient Navigation Policy Learning

Marvin Chancán, Michael Milford

专题命中 机器人数据与评测 ：navigation(title,abstract)；分类 cs.RO、cs.CV、cs.LG；robotics(journal_ref)

Comments Preprint version of article accepted to ICRA 2020

Journal ref 2020 IEEE International Conference on Robotics and Automation (ICRA)

Learning of Coordination Policies for Robotic Swarms

Qiyang Li, Xintong Du, Yizhou Huang, Quinlan Sykora, Angela P. Schoellig

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.AI、cs.LG；robotics(comments)

Comments 8 pages, 11 figures, submitted to 2018 IEEE International Conference on Robotics and Automation

GASE: Gaussian Splatting-Based Automated System for Reconstructing Embodied-Simulation Environments

GASE：基于高斯溅射的自动化系统用于重建具身仿真环境

Jiawei Zhang, Yiming Yan, Chao Liang, Nuo Xu, Seson Sun, Qichen Zhang, Yuhao Xu, Yantai Yang, Yingqiao Wang, Qin Jin, Zhipeng Zhang

机构 * AutoLab, SAI, Shanghai Jiao Tong University（上海交通大学SAI学院AutoLab实验室） ； AIM3 Lab, School of Information, Renmin University of China（中国人民大学信息学院AIM3实验室） ； Research Lab, Anyverse Dynamics（Anyverse Dynamics研究实验室） 纠错

专题命中 机器人数据与评测 ：robot learning(abstract)；embodied agent(abstract)；manipulation(abstract)；navigation(abstract)

AI总结 提出GASE系统，利用全景相机阵列和多视图视频流，通过相机位姿策略提取前景物体并修复场景，独立重建后导入物理仿真器，实现高效高保真仿真环境构建，分割精度提升超10%，真实机器人部署性能差距小于10%。

PhysX-Omni: Unified Simulation-Ready Physical 3D Generation for Rigid, Deformable, and Articulated Objects

PhysX-Omni: 为刚体、变形体和关节物体统一的模拟准备物理3D生成

Ziang Cao, Yinghao Liu, Haitian Li, Runmao Yao, Fangzhou Hong, Zhaoxi Chen, Liang Pan, Ziwei Liu

机构 * S-Lab, Nanyang Technological University（南洋理工大学S实验室） 纠错

专题命中 机器人数据与评测 ：embodied AI(abstract,abstract_cn)；robotic(abstract,abstract_cn)；分类 cs.RO、cs.CV

AI总结 本文提出PhysX-Omni，一种统一的模拟准备物理3D生成框架，通过开发针对视觉-语言模型的高效几何表示和首个通用模拟准备3D数据集PhysXVerse，以及评估生成和理解能力的PhysX-Bench，显著提升了生成和理解性能，推动下游应用如具身AI和物理模拟的发展。

Comments Project page: https://physx-omni.github.io/

SABER: A Scalable Action-Based Embodied Dataset for Real-World VLA Adaptation

SABER：一种可扩展的动作基于具身数据集用于真实世界VLA适应

Narsimha Menga, Parikshit Sakurikar, Amirreza Rouhi, Satya Sai Reddy, Anirudh Govil, Sri Harsha Chittajallu, Rajat Aggarwal, Anoop Namboodiri, Sashi Reddi

机构 * DreamVu 纠错

专题命中 机器人数据与评测 ：robotics(abstract)；manipulation(abstract)；robot foundation model(abstract)；robotic(abstract)

AI总结 SABER通过高保真零售机器人动作数据集提升真实世界零售任务的机器人性能，采用多流动作表示方法，实现29.3%的成功率，优于微调基线。

Can LLMs See Without Pixels? Benchmarking Spatial Intelligence from Textual Descriptions

大语言模型能否通过像素感知空间智能？基于文本描述的空间智能基准测试

Zhongbin Guo, Zhen Yang, Yushan Li, Xinyue Zhang, Wenyu Gao, Jiacheng Wang, Chengzhi Li, Xiangrui Liu, Ping Jian

机构 * School of Computer Science & Technology, Beijing Institute of Technology（计算机科学与技术学院，北京理工大学） 纠错

专题命中 机器人数据与评测 ：embodied agent(abstract)；manipulation(abstract)；navigation(abstract)；robotic(abstract)

AI总结 SiT-Bench通过文本描述评估大语言模型的空间智能，揭示其在全局一致性方面的不足，并表明显式空间推理可提升性能。

Deep Kernel and Image Quality Estimators for Optimizing Robotic Ultrasound Controller using Bayesian Optimization

Deepak Raina, SH Chandrashekhara, Richard Voyles, Juan Wachs, Subir Kumar Saha

专题命中 机器人数据与评测 ：robotic(title,abstract)；robotics(comments,journal_ref)；分类 cs.RO、cs.LG

Comments Accepted in IEEE International Symposium on Medical Robotics (ISMR) 2023

Journal ref IEEE International Symposium on Medical Robotics (ISMR) 2023

Optimal Sequential Task Assignment and Path Finding for Multi-Agent Robotic Assembly Planning

Kyle Brown, Oriana Peltzer, Martin A. Sehr, Mac Schwager, Mykel J. Kochenderfer

专题命中 机器人数据与评测 ：robotic(title,abstract)；robotics(comments,journal_ref)；分类 cs.RO、cs.AI

Comments Presented at International Conference on Robotics and Automation (ICRA) 2020

Journal ref International Conference on Robotics and Automation (ICRA) 2020

GRaD-Nav++: Vision-Language Model Enabled Visual Drone Navigation with Gaussian Radiance Fields and Differentiable Dynamics

GRaD-Nav++: 基于视觉-语言模型的视觉无人机导航：高斯辐射场与可微动力学

Qianzhong Chen, Naixiang Gao, Suning Huang, JunEn Low, Timothy Chen, Jiankai Sun, Mac Schwager

机构 * Department of Mechanical Engineering, Stanford University（斯坦福大学机械工程系） ； Department of Aeronautics and Astronautics, Stanford University（斯坦福大学航空航天工程系） 纠错

专题命中 机器人数据与评测 ：navigation(title,abstract)；robotics(comments,journal_ref)；分类 cs.RO

AI总结 GRaD-Nav++提出一种轻量级视觉-语言-动作框架，通过可微强化学习在3D高斯点云模拟器中训练，实现基于自然语言指令的实时无人机导航，展示在多任务和多环境下的高效导航能力。

Comments Published in: IEEE Robotics and Automation Letters ( Volume: 11, Issue: 2, February 2026)

Journal ref Chen, Qianzhong, et al. "Grad-nav++: Vision-language model enabled visual drone navigation with gaussian radiance fields and differentiable dynamics." IEEE Robotics and Automation Letters 11.2 (2025): 1418-1425

Towards the Harness of Embodied Agents

迈向具身智能体的管控

Qi Wang, Tianyi Wang, Chengyang Li, Shikun Ban, Yurun Chen, Yizhong Ge, Jason Qin, Chengtai Li, Wentao Zhu

专题命中 机器人数据与评测 ：embodied agent(title,abstract)；分类 cs.RO、cs.AI、cs.LG

AI总结 本文提出名为Thea的具身智能体管控系统，通过场景图和退出码评估弥合物理世界与智能体的差距，实现长程任务完成。

Comments Project page: https://eit-hai.github.io/thea

GAUGE: A Measurement-Grounded Benchmark for Physical Fidelity in Simulation Engines and Video World Models

GAUGE：面向仿真引擎与视频世界模型物理保真度的、基于测量的基准

Shuai Wang, Yaxin Feng, Xuekun Jiang, Shihan Tian, Ningyu Yan, Xing Shen, Chaoyang Lyu, Hui Wang, Yunsong Zhou, Hanqing Wang, Jiangmiao Pang, Yang Xiang, Xing Gao, Chunhua Shen, Weinan Zhang

专题命中 机器人数据与评测 ：world model(title,abstract)；分类 cs.RO、cs.AI、cs.CV

AI总结 本研究提出基于真实世界的GAUGE基准，联合评估数值仿真器与生成式视频世界模型的物理保真度，发现无统一保真的物理引擎，视频模型存在轨迹形式正确但物理量错误的问题，为开发高保真仿真器奠定基础。