Whole-Body Proprioceptive Morphing: A Modular Soft Gripper for Robust Cross-Scale Grasping
🤖 AI Summary
Conventional soft grippers suffer from fixed morphologies, limiting their ability to perform adaptive manipulation across diverse scales. Method: Inspired by octopus biology, we propose a fully body-sensory-driven modular soft gripper comprising a network of distributed self-sensing pneumatic actuators, integrated with embedded proprioceptive sensors and decentralized control algorithms to enable intelligent global topological reconfiguration and dynamic polygonal shape switching. Contribution/Results: This work achieves, for the first time, full-body sensory-coordinated morphological transformation in soft grippers—overcoming rigid geometric constraints—and enables continuous grasping across a 10× scale range (from micrometer-scale pinch to centimeter-scale envelopment). It further supports novel manipulation modalities, including multi-object coordination and internal hooking. Experiments demonstrate high efficiency and robust adaptability to both standard and irregular objects across varying geometries and sizes.
Application Category
📝 Abstract
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$ imes$), 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.
Problem
Research questions and friction points this paper is trying to address.
Achieving biological cross-scale grasping dexterity in robotics
Overcoming fixed morphology limitations in conventional soft grippers
Integrating distributed actuation with proprioceptive sensing for adaptive manipulation
Innovation
Methods, ideas, or system contributions that make the work stand out.
Modular soft gripper with self-sensing pneumatic actuators
Whole-body reconfiguration for diverse polygonal shapes
Integrated proprioceptive feedback enables cross-scale grasping
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