Gaze-based dual resolution deep imitation learning for high-precision dexterous robot manipulation
Laboratory for Intelligent Systems and Informatics, Graduate School of Information Science and Technology, The University of Tokyo（智能系统与信息学实验室，信息科学与技术研究生院，东京大学）
A high-precision manipulation task, such as needle threading, is challenging. Physiological studies have proposed connecting low-resolution peripheral vision and fast movement to transport the hand into the vicinity of an object, and using high-resolution foveated vision to achieve the accurate homing of the hand to the object. The results of this study demonstrate that a deep imitation learning based method, inspired by the gaze-based dual resolution visuomotor control system in humans, can solve the needle threading task. First, we recorded the gaze movements of a human operator who was teleoperating a robot. Then, we used only a high-resolution image around the gaze to precisely control the thread position when it was close to the target. We used a low-resolution peripheral image to reach the vicinity of the target. The experimental results obtained in this study demonstrate that the proposed method enables precise manipulation tasks using a general-purpose robot manipulator and improves computational efficiency. Data from this and related works are available at: https://sites.google.com/view/multi-task-fine.
Gaze-Guided Task Decomposition for Imitation Learning in Robotic Manipulation
The University of Tokyo（东京大学）；Graduate School of Information Science and Technology（信息科学与技术研究生院）；Laboratory for Intelligent Systems and Informatics（智能系统与信息学实验室）
Dexterous Manipulation through Imitation Learning: A Survey
Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System（天津智能集群技术与系统重点实验室）；School of Electrical and Information Engineering（电气与信息工程学院）；Shandong University（山东大学）；State Key Laboratory of General Artificial Intelligence（通用人工智能国家重点实验室）；Division of Robotics, Perception and Learning（机器人、感知与学习 division）；School of Control Science and Engineering（控制科学与工程学院）；Massachusetts Institute of Technology（麻省理工学院）；School of Computer Science（计算机科学学院）；State Key Laboratory of Multimodal Artificial Intelligence Systems（多模态人工智能系统国家重点实验室）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；School of Artificial Intelligence（人工智能学院）
A Wearable Robotic Hand for Hand-over-Hand Imitation Learning
Tsinghua-Berkeley Shenzhen Institute, Tsinghua University（清华大学清华-伯克利深圳学院）；Institute for Interdisciplinary Information Sciences, Tsinghua University（清华大学交叉信息研究院）；Shanghai AI Lab（上海人工智能实验室）；Shanghai Qi Zhi Institute（上海期智研究院）
DexCast: Learning Real-World Dexterous Control from Human Videos
Tsinghua University（清华大学）；TsingTec（清华科技园（注：TsingTec为清华大学相关科技产业机构，此处保留英文原名））；Fudan University（复旦大学）；Shenzhen University（深圳大学）；Nanyang Technological University（南洋理工大学）；Georgia Institute of Technology（佐治亚理工学院）
CordViP: Correspondence-based Visuomotor Policy for Dexterous Manipulation in Real-World
State Key Laboratory of Multimedia Information Processing, School of Computer Science, Peking University（多媒体信息处理国家重点实验室，计算机学院，北京大学）；The University of Hong Kong（香港大学）；Beijing Academy of Artificial Intelligence（北京人工智能研究院）
AutoFocus-IL: VLM-based Saliency Maps for Data-Efficient Visual Imitation Learning without Extra Human Annotations
Department of Electrical and Computer Engineering, University of California, Riverside, USA（电气与计算机工程系，加州大学河滨分校）；Thomas Lord Department of Computer Science, University of Southern California, USA（汤姆斯·劳德计算机科学系，南加州大学）
Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；Aalto University（阿alto大学）；University of Southern California（南加州大学）；Imperial College London（伦敦帝国理工学院）；University of Oulu（奥卢大学）；University of Alberta（阿尔伯塔大学）；Alberta Machine Intelligence Institute（阿尔伯塔人工智能研究所）
CDF-Glove: A Cable-Driven Force Feedback Glove for Dexterous Teleoperation
Center for Artificial Intelligence and Robotics, Shenzhen International Graduate School, Tsinghua University（人工智能与机器人中心，深圳国际研究生院，清华大学）；PKU-Psibot Joint Lab（北京大学-PsiBot联合实验室）；Department of Advanced Manufacturing, Shenzhen International Graduate School, Tsinghua University（先进制造系，深圳国际研究生院，清华大学）
Restoring Noisy Demonstration for Imitation Learning With Diffusion Models
Graduate Institute of Communication Engineering, National Taiwan University（国立台湾大学通信工程研究所）；Data Science Degree Program, National Taiwan University and Academia Sinica（国立台湾大学数据科学学士学位计划）；Department of Electrical Engineering, National Taiwan University（国立台湾大学电子工程系）
Learning Fine Pinch-Grasp Skills using Tactile Sensing from A Few Real-world Demonstrations
School of Informatics, University of Edinburgh（爱丁堡大学信息学院）；Touchlab Limited（Touchlab有限公司）；Department of Engineering Mathematics, University of Bristol（布里斯托尔大学工程数学系）；Department of Computer Science, University College London（伦敦大学学院计算机科学系）
