While the grasping capability of robotic grippers has shown significant development, the ability to manipulate objects within the hand is still limited. One explanation for this limitation is the lack of controlled contact variation between the grasped object and the gripper. For instance, human hands have the ability to firmly grip object surfaces, as well as slide over object faces, an aspect that aids the enhanced manipulation of objects within the hand without losing contact. In this letter, we present a parametric, origami-inspired thin surface capable of transitioning between a high friction and a low friction state, suitable for implementation as an epidermis in robotic fingers. A numerical analysis of the proposed surface based on its design parameters, force analysis, and performance in in-hand manipulation tasks is presented. Through the development of a simple two-fingered two-degree-of-freedom gripper utilizing the proposed variable-friction surfaces with different parameters, we experimentally demonstrate the improved manipulation capabilities of the hand when compared to the same gripper without changeable friction. Results show that the pattern density and valley gap are the main parameters that effect the in-hand manipulation performance. The origami-inspired thin surface with a higher pattern density generated a smaller valley gap and smaller height change, producing a more stable improvement of the manipulation capabilities of the hand.
ARTiS: An Adaptive Robotic Gripper for Enhanced Tool Manipulation in Disassembly Applications
National Institute of Advanced Industrial Science and Technology (AIST)（日本国立先进工业科学技术研究所（AIST））；The University of Osaka（大阪大学）；Graduate School of Engineering Science, The University of Osaka（大阪大学工程科学研究生院）
Whole-Body Proprioceptive Morphing: A Modular Soft Gripper for Robust Cross-Scale Grasping
Mechanical Engineering Department at the University of Michigan-Ann Arbor（密歇根大学安娜堡分校机械工程系）；Robotics Department at the University of Michigan-Ann Arbor（密歇根大学安娜堡分校机器人学系）
Benchmarking Dexterity of Multifingered Robot Hands: A Review and Perspective
US National Science Foundation HAND Engineering Research Center（美国国家科学基金会HAND工程研究中心）；Center for Robotics and Biosystems, Northwestern Univ.（西北大学机器人与生物系统中心）；Department of Mechanical Engineering, Texas A&M Univ.（德克萨斯A&M大学机械工程系）；Department of Electrical and Computer Engineering, Carnegie Mellon Univ.（卡内基梅隆大学电子与计算机工程系）；Department of Mechanical Engineering, Florida A&M Univ.（佛罗里达A&M大学机械工程系）
Manipulation Planning and Control for Shelf Replenishment
Dipartimento di Ingegneria, Università degli Studi della Campania Luigi Vanvitelli（坎帕尼亚路易吉·凡维泰利大学工程系）；Institute for Artificial Intelligence, Universität Bremen（不来梅大学人工智能研究所）
YUBI: Yielding Universal Bidigital Interface for Bimanual Dexterous Manipulation at Scale
AI Robot Association (AIRoA)（AI机器人协会）；Toyota Motor Corporation（丰田汽车公司）；National Institute of Advanced Industrial Science and Technology (AIST)（国家先进工业科学与技术研究院）；The University of Tokyo（东京大学）；Institute of Science Tokyo（东京科学研究所）；Waseda University（早稻田大学）
Adaptive and Multi-object Grasping via Deformable Origami Modules
Singapore MIT Alliance for Research and Technology (SMART) centre（新加坡-麻省理工联合研究与技术中心）；Department of Mechanical Engineering, National University of Singapore（国立新加坡大学机械工程系）
DexTOG: Learning Task-Oriented Dexterous Grasp with Language
School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University（上海交通大学电子信息与电气工程学院）；AI Institute, Shanghai Jiao Tong University（上海交通大学AI研究院）；Southeast University（东南大学）
Dexora: Open-source VLA for High-DoF Bimanual Dexterity
Tsinghua University（清华大学）；Beijing Academy of Artificial Intelligence（北京人工智能研究院）；The University of Hong Kong（香港大学）；Shanghai Jiao Tong University（上海交通大学）；ShanghaiTech University（上海科技大学）；Peking University（北京大学）
Southern University of Science and Technology（南方科技大学）；Harbin Institute of Technology (Shenzhen)（哈尔滨工业大学（深圳））；Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)（南方海洋科学与工程广东省实验室（广州））
MoDex: A Diffusion Policy for Sequential Multi-Object Dexterous Grasping
Department of Robotics, Perception and Learning, KTH Royal Institute of Technology（机器人、感知与学习系，皇家理工学院）；Robotics and Autonomous Systems at University of Turku（图尔库大学机器人与自主系统）
