Learning to solve complex manipulation tasks from visual observations is a dominant challenge for real-world robot learning. Although deep reinforcement learning algorithms have recently demonstrated impressive results in this context, they still require an impractical amount of time-consuming trial-and-error iterations. In this work, we consider the promising alternative paradigm of interactive learning in which a human teacher provides feedback to the policy during execution, as opposed to imitation learning where a pre-collected dataset of perfect demonstrations is used. Our proposed CEILing (Corrective and Evaluative Interactive Learning) framework combines both corrective and evaluative feedback from the teacher to train a stochastic policy in an asynchronous manner, and employs a dedicated mechanism to trade off human corrections with the robot's own experience. We present results obtained with our framework in extensive simulation and real-world experiments to demonstrate that CEILing can effectively solve complex robot manipulation tasks directly from raw images in less than one hour of real-world training.
Mani-GPT: A Generative Model for Interactive Robotic Manipulation
Southern University of Science and Technology（南方科技大学）；PLA General Hospital（中国人民解放军总医院）；National Clinical Research Center for Orthopedics, Sports Medicine and Rehabilitation（国家骨科、运动医学与康复医学临床研究中心）
GeniWorld: A Generalizable Interactive World Model for Robotic Manipulation via Visual Actions
Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）；Tencent Robotics X（腾讯Robotics X实验室）；The Hong Kong University of Science and Technology（香港科技大学）；Shenzhen Technology University（深圳技术大学）
DeltaWorld: Physically Consistent Interactive World Simulators via Action-Conditioned Latent Increment Learning
Imprintx Robotics（印迹机器人）；Electric Power Research Institute of State Grid Jibei Electric Power Co., Ltd.（国网冀北电力有限公司电力科学研究院）；North China Electric Power Research Institute Co., Ltd.（华北电力科学研究院有限责任公司）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）
LangGrasp: Leveraging Fine-Tuned LLMs for Language Interactive Robot Grasping with Ambiguous Instructions
School of Computer Science and Technology（计算机科学与技术学院）；Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System（湖北省智能信息处理与实时工业系统重点实验室）；Institute of Robotics and Intelligent Systems（机器人与智能系统研究院）；Wuhan University of Science and Technology（武汉理工大学）
RoboEXP: Action-Conditioned Scene Graph via Interactive Exploration for Robotic Manipulation
Peking University（北京大学）；National University of Singapore（新加坡国立大学）；Columbia University（哥伦比亚大学）；University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；Amazon（亚马逊公司）
Interactive Learning of Physical Object Properties Through Robot Manipulation and Database of Object Measurements
Czech Technical University in Prague（布拉格捷克技术大学）；Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University in Prague（布拉格捷克技术大学捷克信息学、机器人学与控制论研究所）；New York University Abu Dhabi（纽约大学阿布扎比分校）；Mondragon Unibertsitatea（蒙德拉贡大学）；Imperial College London（伦敦帝国学院）；Aalto University（阿尔托大学）
High-Fidelity Simulated Data Generation for Real-World Zero-Shot Robotic Manipulation Learning with Gaussian Splatting
Wuhan University（武汉大学）；DAMO Academy, Alibaba Group（达摩院，阿里巴巴集团）；Hupan Lab（虎扑实验室）；The Chinese University of Hong Kong（香港中文大学）；Tsinghua University（清华大学）；Huazhong University of Science and Technology（华中科技大学）；Zhejiang University（浙江大学）
SM2ITH: Safe Mobile Manipulation with Interactive Human Prediction via Task-Hierarchical Bilevel Model Predictive Control
Department of Computer, Control and Management Engineering, of Sapienza University of Rome（意大利萨皮恩扎大学计算机、控制与管理工程系）；University of Toronto Institute for Aerospace Studies (UTIAS) and the Vector Institute for Artificial Intelligence（多伦多大学航空航天研究所（UTIAS）和向量人工智能研究所）；Learning Systems and Robotics lab at the Technical University of Munich and the Munich Institute for Robotics and Machine Intelligence (MIRMI)（慕尼黑技术大学学习系统与机器人实验室及慕尼黑机器人与机器智能研究所（MIRMI））；School of Computing Science, Faculty of Applied Sciences, Simon Fraser University（西蒙·弗雷泽大学应用科学学院计算机科学系）
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）
Nanyang Technological University（南洋理工大学）；Institute of Advanced Intelligence and Computing, A*STAR（A*STAR先进智能与计算研究所）；Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；National University of Singapore（新加坡国立大学）
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）
