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This content will become publicly available on August 1, 2022

Title: A Novel Variable Stiffness Soft Robotic Gripper
Compliant grasping is crucial for secure handling objects not only vary in shapes but also in mechanical properties. We propose a novel soft robotic gripper with decoupled stiffness and shape control capability for performing adaptive grasping with minimum system complexity. The proposed soft fingers conform to object shapes facilitating the handling of objects of different types, shapes, and sizes. Each soft gripper finger has a length constraining mechanism (an articulable rigid backbone) and is powered by pneumatic muscle actuators. We derive the kinematic model of the gripper and use an empirical approach to simultaneously map input pressures to stiffness control and bending deformation of fingers. We use these mappings to demonstrate decoupled stiffness and shape (bending) control of various grasping configurations. We conduct tests to quantify the grip quality when holding objects as the gripper changes orientation, the ability to maintain the grip as the gripper is subjected to translational and rotational movements, and the external force perturbations required to release the object from the gripper under various stiffness and shape (bending) settings. The results validate the proposed gripper’s performance and show how the decoupled stiffness and shape control can improve the grasping quality in soft robotic grippers.
Authors:
; ; ;
Award ID(s):
1718075
Publication Date:
NSF-PAR ID:
10296223
Journal Name:
IEEE International Conference on Automation Science and Engineering CASE
Page Range or eLocation-ID:
2222-2227
ISSN:
2161-8070
Sponsoring Org:
National Science Foundation
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