Everything-Grasping (EG) Gripper: A Universal Gripper with Synergistic Suction-Grasping Capabilities for Cross-Scale and Cross-State Manipulation
Department of Mechanical Engineering, University of California, Berkeley（加州大学伯克利分校机械工程系）；Department of Biomedical Engineering, The Chinese University of Hong Kong（香港中文大学生物医学工程系）；Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong（香港中文大学机械与自动化工程系）；Multi-scale Medical Robotics Center, Hong Kong, China（香港医学机器人多尺度中心）；Department of Agricultural and Biological Engineering, Purdue University（普渡大学农业与生物工程系）
Grasping objects across vastly different sizes and physical states-including both solids and liquids-with a single robotic gripper remains a fundamental challenge in soft robotics. We present the Everything-Grasping (EG) Gripper, a soft end-effector that synergistically integrates distributed surface suction with internal granular jamming, enabling cross-scale and cross-state manipulation without requiring airtight sealing at the contact interface with target objects. The EG Gripper can handle objects with surface areas ranging from sub-millimeter scale 0.2 mm2 (glass bead) to over 62,000 mm2 (A4 sized paper and woven bag), enabling manipulation of objects nearly 3,500X smaller and 88X larger than its own contact area (approximated at 707 mm2 for a 30 mm-diameter base). We further introduce a tactile sensing framework that combines liquid detection and pressure-based suction feedback, enabling real-time differentiation between solid and liquid targets. Guided by the actile-Inferred Grasping Mode Selection (TIGMS) algorithm, the gripper autonomously selects grasping modes based on distributed pressure and voltage signals. Experiments across diverse tasks-including underwater grasping, fragile object handling, and liquid capture-demonstrate robust and repeatable performance. To our knowledge, this is the first soft gripper to reliably grasp both solid and liquid objects across scales using a unified compliant architecture.
VacuumVLA: Boosting VLA Capabilities via a Unified Suction and Gripping Tool for Complex Robotic Manipulation
The Chinese University of Hong Kong（香港中文大学）；Shanghai Jiao Tong University（上海交通大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；DiDi Global（滴滴出行）
A control scheme for collaborative object transportation between a human and a quadruped robot using the MIGHTY suction cup
Institute of Computer Science, Foundation for Research and Technology–Hellas（计算机科学研究所，希腊基础研究与技术研究院）；Department of Electrical and Computer Engineering, Hellenic Mediterranean University（电气与计算机工程系，希腊地中海大学）；Department of Computer Science, University of Crete（计算机科学系，希腊克里特大学）
RoTipBot: Robotic Handling of Thin and Flexible Objects using Rotatable Tactile Sensors
School of Aerospace Engineering, Beijing Institute of Technology（北京理工大学航天工程学院）；Department of Engineering, King’s College London（伦敦国王学院工程系）；Department of Data Science and AI, Monash University（墨尔本大学数据科学与人工智能系）
University of Liverpool（利物浦大学）；Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；Indian Institute of Science（印度科学学院）；The University of Tokyo（东京大学）；Zürcher Hochschule für Angewandte Wissenschaften（苏黎世应用科技大学）；University of Arkansas（阿肯色大学）；Physical Intelligence（物理智能公司）；Huazhong University of Science and Technology（华中科技大学）
MultiGraspNet: A Multitask 3D Vision Model for Multi-gripper Robotic Grasping
VANDAL Laboratory, Department of Control and Computer Engineering, Politecnico di Torino（沃纳达实验室，控制与计算机工程系，都灵理工大学）；Comau S.p.A., Advanced Automation Solutions（Comau S.p.A.，先进自动化解决方案）；Istituto Italiano di Tecnologia（意大利技术研究所）
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）
Grasp What You Want: Embodied Dexterous Grasping System Driven by Your Voice
Shenzhen Institute of Artificial Intelligence and Robotics for Society（深圳市人工智能与机器人研究院）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；South China University of Technology（华南理工大学）
An Integrated System for WEEE Sorting Employing X-ray Imaging, AI-based Object Detection and Segmentation, and Delta Robot Manipulation
THL (Tech Hive Labs)（Tech Hive Labs）；AI Innovation Centre, University of Essex（艾创新中心，埃塞克斯大学）；Control Systems Lab, School of Mechanical Engineering, NTUA（控制系统实验室，机械工程学院，NTUA）
