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The Enhanced Adaptive Grasping of a Soft Robotic Gripper Using Rigid Supports

Zhikang Peng, Dongli Liu, Xiaoyun Song, Meihua Wang, Yiwen Rao, Yanjie Guo, Jun Peng

Year
2024
Citations
7
Access
Open access

Abstract

Soft pneumatic grippers can grasp soft or irregularly shaped objects, indicating potential applications in industry, agriculture, and healthcare. However, soft grippers rarely carry heavy and dense objects due to the intrinsic low modulus of soft materials in nature. This paper designed a soft robotic gripper with rigid supports to enhance lifting force by 150 ± 20% in comparison with that of the same gripper without supports, which successfully lifted a metallic wrench (672 g). The soft gripper also achieves excellent adaptivity for irregularly shaped objects. The design, fabrication, and performance of soft grippers with rigid supports are discussed in this paper.

Keywords

Soft roboticsComputer scienceRobotMaterials scienceArtificial intelligence

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