标题： 全身本体感觉变形：一种模块化软夹爪用于鲁棒的跨尺度抓取 显示英文标题

标题： Whole-Body Proprioceptive Morphing: A Modular Soft Gripper for Robust Cross-Scale Grasping

摘要： 生物系统，如章鱼，通过适应性重新配置其整体形态，表现出卓越的跨尺度操作能力，而这种能力在机器人技术中仍然难以实现。 传统的软夹持器虽然具有柔顺性，但大多受限于固定的全局形态，以往的形状变化努力主要局限于局部变形，无法复制这种生物灵活性。 受这一自然范例的启发，我们引入了协作式全身本体感觉形态变化的概念，并在模块化软夹持器架构中实现了这一概念。 我们的设计是一个由模块化自感知气动执行器组成的分布式网络，使夹持器能够智能地重新配置其整个拓扑结构，实现多种可控制的形态状态，形成多样化的多边形形状。 通过整合来自嵌入式传感器的丰富本体感觉反馈，我们的系统可以无缝地从精确夹持过渡到大范围抓握。 我们通过实验证明，这种方法扩展了抓握范围，并增强了在各种物体几何形状（标准和不规则）和尺度（高达10$\times$）上的泛化能力，同时解锁了多物体和内部钩状抓握等新的操作模式。 这项工作提出了一种低成本、易于制造且可扩展的框架，将分布式驱动与集成传感相结合，为在机器人操作中实现生物水平的灵巧性提供了新的途径。 显示英文摘要

摘要： Biological systems, such as the octopus, exhibit masterful cross-scale manipulation by adaptively reconfiguring their entire form, a capability that remains elusive in robotics. Conventional soft grippers, while compliant, are mostly constrained by a fixed global morphology, and prior shape-morphing efforts have been largely confined to localized deformations, failing to replicate this biological dexterity. Inspired by this natural exemplar, we introduce the paradigm of collaborative, whole-body proprioceptive morphing, realized in a modular soft gripper architecture. Our design is a distributed network of modular self-sensing pneumatic actuators that enables the gripper to intelligently reconfigure its entire topology, achieving multiple morphing states that are controllable to form diverse polygonal shapes. By integrating rich proprioceptive feedback from embedded sensors, our system can seamlessly transition from a precise pinch to a large envelope grasp. We experimentally demonstrate that this approach expands the grasping envelope and enhances generalization across diverse object geometries (standard and irregular) and scales (up to 10$\times$), while also unlocking novel manipulation modalities such as multi-object and internal hook grasping. This work presents a low-cost, easy-to-fabricate, and scalable framework that fuses distributed actuation with integrated sensing, offering a new pathway toward achieving biological levels of dexterity in robotic manipulation.