Dataset Information

Adaptive Self-Sealing Suction-Based Soft Robotic Gripper.

ABSTRACT: While suction cups prevail as common gripping tools for a wide range of real-world parts and surfaces, they often fail to seal the contact interface when engaging with irregular shapes and textured surfaces. In this work, the authors propose a suction-based soft robotic gripper where suction is created inside a self-sealing, highly conformable and thin flat elastic membrane contacting a given part surface. Such soft gripper can self-adapt the size of its effective suction area with respect to the applied load. The elastomeric membrane covering edge of the soft gripper can develop an air-tight self-sealing with parts even smaller than the gripper diameter. Such gripper shows 4 times higher adhesion than the one without the membrane on various textured surfaces. The two major advantages, underactuated self-adaptability and enhanced suction performance, allow the membrane-based suction mechanism to grip various three-dimensional (3D) geometries and delicate parts, such as egg, lime, apple, and even hydrogels without noticeable damage, which can have not been gripped with the previous adhesive microstructures-based and active suction-based soft grippers. The structural and material simplicity of the proposed soft gripper design can have a broad use in diverse fields, such as digital manufacturing, robotic manipulation, transfer printing, and medical gripping.

SUBMITTER: Song S

PROVIDER: S-EPMC8425915 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Adaptive Self-Sealing Suction-Based Soft Robotic Gripper.

Song Sukho S Drotlef Dirk-Michael DM Son Donghoon D Koivikko Anastasia A Sitti Metin M

Advanced science (Weinheim, Baden-Wurttemberg, Germany) 20210703 17

While suction cups prevail as common gripping tools for a wide range of real-world parts and surfaces, they often fail to seal the contact interface when engaging with irregular shapes and textured surfaces. In this work, the authors propose a suction-based soft robotic gripper where suction is created inside a self-sealing, highly conformable and thin flat elastic membrane contacting a given part surface. Such soft gripper can self-adapt the size of its effective suction area with respect to th ...[more]

PMID: 34218533

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Project description:With the purpose of making soft robotic structures with embedded sensors, additive manufacturing techniques like fused deposition modeling (FDM) are popular. Thermoplastic polyurethane (TPU) filaments, with and without conductive fillers, are now commercially available. However, conventional FDM still has some limitations because of the marginal compatibility with soft materials. Material selection criteria for the available material options for FDM have not been established. In this study, an open-source soft robotic gripper design has been used to evaluate the FDM printing of TPU structures with integrated strain sensing elements in order to provide some guidelines for the material selection when an elastomer and a soft piezoresistive sensor are combined. Such soft grippers, with integrated strain sensing elements, were successfully printed using a multi-material FDM 3D printer. Characterization of the integrated piezoresistive sensor function, using dynamic tensile testing, revealed that the sensors exhibited good linearity up to 30% strain, which was sufficient for the deformation range of the selected gripper structure. Grippers produced using four different TPU materials were used to investigate the effect of the Shore hardness of the TPU on the piezoresistive sensor properties. The results indicated that the in situ printed strain sensing elements on the soft gripper were able to detect the deformation of the structure when the tentacles of the gripper were open or closed. The sensor signal could differentiate between the picking of small or big objects and when an obstacle prevented the tentacles from opening. Interestingly, the sensors embedded in the tentacles exhibited good reproducibility and linearity, and the sensitivity of the sensor response changed with the Shore hardness of the gripper. Correlation between TPU Shore hardness, used for the gripper body and sensitivity of the integrated in situ strain sensing elements, showed that material selection affects the sensor signal significantly.

Dataset Information

Adaptive Self-Sealing Suction-Based Soft Robotic Gripper.

Publications

Adaptive Self-Sealing Suction-Based Soft Robotic Gripper.

Similar Datasets

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