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.

翻译：生物系统（如章鱼）通过自适应重构其整体形态展现出卓越的跨尺度操控能力，这种能力在机器人领域仍难以实现。传统软体夹持器虽具有顺应性，但大多受限于固定的全局形态结构，而先前的形态变换研究主要局限于局部形变，未能复现这种生物灵巧性。受此自然范例启发，我们提出协同式全身本体感知形态变换范式，并通过模块化软体夹持器架构实现。该设计采用分布式模块化自感知气动执行器网络，使夹持器能够智能重构其整体拓扑结构，实现多种可控的形态变换状态以构成多样化的多边形构型。通过融合嵌入式传感器提供的丰富本体感知反馈，该系统可实现从精确捏取到大幅包络抓取的无缝切换。实验证明，该方法显著扩展了抓取包络空间，并提升了对不同几何形状（标准与不规则）和尺度（最高达10倍）物体的泛化能力，同时解锁了多物体抓取与内部钩取等新型操控模式。本研究提出了一种低成本、易制造且可扩展的框架，将分布式驱动与集成传感相融合，为在机器人操控中实现生物级灵巧性提供了新路径。