Sim2Real$^2$: Actively Building Explicit Physics Model for Precise Articulated Object Manipulation
Tsinghua University（清华大学）；Beijing University of Posts and Telecommunications（北京邮电大学）；AVIC Chengdu Aircraft Industrial (Group) Co., Ltd（中航工业成都飞机工业（集团）有限责任公司）
Accurately manipulating articulated objects is a challenging yet important task for real robot applications. In this paper, we present a novel framework called Sim2Real$^2$ to enable the robot to manipulate an unseen articulated object to the desired state precisely in the real world with no human demonstrations. We leverage recent advances in physics simulation and learning-based perception to build the interactive explicit physics model of the object and use it to plan a long-horizon manipulation trajectory to accomplish the task. However, the interactive model cannot be correctly estimated from a static observation. Therefore, we learn to predict the object affordance from a single-frame point cloud, control the robot to actively interact with the object with a one-step action, and capture another point cloud. Further, the physics model is constructed from the two point clouds. Experimental results show that our framework achieves about 70% manipulations with <30% relative error for common articulated objects, and 30% manipulations for difficult objects. Our proposed framework also enables advanced manipulation strategies, such as manipulating with different tools. Code and videos are available on our project webpage: https://ttimelord.github.io/Sim2Real2-site/
SMART: Zero-Shot Sim-to-Real Articulated Object Manipulation via Large-Scale Synthetic Pretraining
Institute of Artificial Intelligence, China Telecom（中国电信人工智能研究院）；Technical University of Munich（慕尼黑工业大学）；Harbin Institute of Technology（哈尔滨工业大学）；Shanghai Jiao Tong University（上海交通大学）；Tsinghua University（清华大学）；Zhejiang University（浙江大学）
Adaptive Articulated Object Manipulation On The Fly with Foundation Model Reasoning and Part Grounding
Beijing University of Posts and Telecommunications（北京邮电大学）；School of Computer Science, Peking University（北京大学计算机学院）；School of EECS, Peking University（北京大学电子工程学院）
GAPartManip: A Large-scale Part-centric Dataset for Material-Agnostic Articulated Object Manipulation
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）；CFCS, School of Computer Science, Peking University（北京大学计算机科学系）；Carnegie Mellon University（卡内基梅隆大学）；University of California, Berkeley（加州大学伯克利分校）；Xi’an Jiaotong-Liverpool University（西安交通大学利物浦大学）；Galbot
Part-Guided 3D RL for Sim2Real Articulated Object Manipulation
Beijing National Research Center for Information Science and Technology (BNRist)（北京信息科学与技术国家研究中心（BNRist））；Shanghai AI Laboratory（上海人工智能实验室）；University of California San Diego（加利福尼亚大学圣迭戈分校）；Tsinghua University（清华大学）
ArtGS:3D Gaussian Splatting for Interactive Visual-Physical Modeling and Manipulation of Articulated Objects
Shanghai Jiao Tong University（上海交通大学）；Shanghai AI Laboratory（上海人工智能实验室）；National University of Singapore（国立新加坡大学）；Princeton University（普林斯顿大学）；Stanford University（斯坦福大学）；Hefei University of Technology（合肥工业大学）
ManiPose: A Comprehensive Benchmark for Pose-aware Object Manipulation in Robotics
Shanghai Jiao Tong University（上海交通大学）；Hefei University of Technology（合肥工业大学）；The University of Hong Kong（香港大学）；Stanford University（斯坦福大学）；National University of Singapore（新加坡国立大学）
FoLD: Force-Informed Learning for Dexterous Articulated Object Manipulation
University of Science and Technology of China（中国科学技术大学）；Institute of AI for Industries, Chinese Academy of Sciences（中国科学院人工智能产业研究院）；Shenzhen University（深圳大学）
DexSim2Real$^{2}$: Building Explicit World Model for Precise Articulated Object Dexterous Manipulation
Department of Mechanical Engineering, Tsinghua University（清华大学机械工程系）；Institute for Robotics and Intelligent Machines (IRIM), Georgia Institute of Technology（机器人与智能机器研究所（IRIM），佐治亚理工学院）；JD Explore Academy, Beijing, China（京东探索研究院，北京，中国）
Tac-Man: Tactile-Informed Prior-Free Manipulation of Articulated Objects
Institute for Artificial Intelligence, Peking University（北京大学人工智能研究院）；Beijing Institute for General Artificial Intelligence（北京人工智能研究院）；Department of Automation, Tsinghua University（清华大学自动化系）；College of Engineering, Peking University（北京大学工程学院）；PKU-Wuhan Institute for Artificial Intelligence（北大-武汉人工智能研究院）
TacMan-Turbo: Proactive Tactile Control for Robust and Efficient Articulated Object Manipulation
Peking University（北京大学）；State Key Lab of General AI at Peking University（北京大学通用人工智能国家重点实验室）；PKU-BingJi Joint Laboratory for Artificial Intelligence（北京大学-百度智云人工智能联合实验室）；Wuhan Major Scientific and Technological Special Program（武汉重大科技专项）；Hubei Embodied Intelligence Foundation Model Research and Development Program（湖北省具身智能基础模型研发计划）；National Comprehensive Experimental Base for Governance of Intelligent Society（智能社会治理国家综合实验基地）；LeapZenith AI Research（LeapZenith人工智能研究）；Tsinghua University（清华大学）；Embodied Intelligence Lab（具身智能实验室）；PKU-Wuhan Institute for Artificial Intelligence（北京大学-武汉人工智能研究院）；University of Chinese Academy of Sciences（中国科学院大学）
Hierarchical Reinforcement Learning for Articulated Tool Manipulation with Multifingered Hand
State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University（机械系统与振动国家重点实验室，机械工程学院，上海交通大学）；Shanghai Key Laboratory of Intelligent Robotics, Meta Robotics Institute, Shanghai Jiao Tong University（智能机器人上海重点实验室，元机器人研究院，上海交通大学）
Articulated Object Manipulation with Coarse-to-fine Affordance for Mitigating the Effect of Point Cloud Noise
Hyperplane Lab, School of CS, Peking University（北京大学计算机学院超平面实验室）；National Key Laboratory for Multimedia Information Processing（多媒体信息处理国家重点实验室）；Huawei（华为）
Vi-TacMan: Articulated Object Manipulation via Vision and Touch
Shenyang Institute of Automation, Chinese Academy of Sciences（中国科学院沈阳自动化研究所）；University of Chinese Academy of Sciences（中国科学院大学）；Institute for Artificial Intelligence, Peking University（北京大学人工智能研究院）；School of Psychological and Cognitive Sciences, Peking University（北京大学心理与认知科学学院）；State Key Lab of General AI, Peking University（北京大学通用人工智能国家重点实验室）；Beijing Key Laboratory of Behavior and Mental Health, Peking University（北京大学行为与心理健康北京市重点实验室）；LeapZenith AI Research（跃臻人工智能研究院）；Embodied Intelligence Lab, PKU-Wuhan Institute for Artificial Intelligence（北京大学武汉人工智能研究院具身智能实验室）
AdaManip: Adaptive Articulated Object Manipulation Environments and Policy Learning
Peking University（北京大学）；Beijing University of Posts and Telecommunications（北京邮电大学）；Inst. for Artificial Intelligence, Peking University（北京大学人工智能研究院）；Nat’l Eng. Research Center of Visual Technology, Peking University（北京大学视觉技术国家工程研究中心）；State Key Laboratory of General Artificial Intelligence, Peking University（北京大学通用人工智能国家重点实验室）
Kinematic-aware Prompting for Generalizable Articulated Object Manipulation with LLMs
Gaoling School of Artificial Intelligence, Renmin University of China（中国人民大学高瓴人工智能学院）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；Northwestern Polytechnical University（西北工业大学）；Institute of Artificial Intelligence, China Telecom Corp Ltd（中国电信股份有限公司人工智能研究院）
Online Estimation and Manipulation of Articulated Objects
RIPL-Lab, University of Waterloo, Canada（滑铁卢大学）；Robot Learning Lab, University of Freiburg, Germany（弗赖堡大学）；School of Informatics, University of Edinburgh, UK（爱丁堡大学）
GSAM: A Generalizable and Safe Robotic Framework for Articulated Object Manipulation
College of Computer Science, Chongqing University, Chongqing, China（重庆大学计算机学院）；Lumos Robotics, China（Lumos机器人中国）；Xi'an Jiaotong-Liverpool University, China（西安交通大学利物浦大学）；Fudan University, China（复旦大学）；Department of Information Engineering and Computer Science, University of Trento, Trento, Italy（特伦托大学信息工程与计算机科学系）
