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Design of a Novel Soft Pneumatic Gripper with Variable Gripping Size and Mode

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Abstract

Soft grippers have attracted increasing attention due to safer and more adaptable human–machine and environment-machine interactions. However, it has always been a challenge for soft grippers to work under different sizes, shapes, and postures. This paper presents a four-finger soft gripper with two gripping sizes and four gripping modes. The fiber-reinforced bending actuator is used to mimic the finger of the soft gripper. A theoretical model is established to predict the relationship between the bending angle and pressure of the actuator. The single finger bending experiment is carried out to verify the theoretical model. The capability of variable gripping size of the soft gripper has been proofed, which has increased the gripping size range from 84 to 141 mm. The static gripping test and dynamic palletizing test have been performed. The results show that by varying the gripping modes, objects with various sizes, shapes, and postures can be steadily gripped. This study offers a promising solution for the design of multifunctional soft grippers.

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Data availability

The datasets generated and supporting the findings of this article are obtainable from the corresponding author upon reasonable request. The authors attest that all data for this study are included in the paper.

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Funding

This work was supported by the National Natural Science Foundation of China under grant no.52175125.

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Contributions

All authors contributed to the study conception and design. Structure design, data collection and analysis were performed by Yuze Ye, Bo Yan, and Peilin Cheng. The first draft of the manuscript was written by Yuze Ye and all authors commented on previous versions of the manuscript. Figures and Tables were performed by Yebo Lu and Chuanyu Wu. All authors read and approved the final manuscript.

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Correspondence to Bo Yan.

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Ye, Y., Cheng, P., Yan, B. et al. Design of a Novel Soft Pneumatic Gripper with Variable Gripping Size and Mode. J Intell Robot Syst 106, 5 (2022). https://doi.org/10.1007/s10846-022-01721-1

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