Evidence map›Paper›PMID 42505499›Full record

ArticleBiomimetics (Basel, Switzerland)2026

Biomimetic Origami-Based Soft Robotic Grippers with Two-Stage Grasping.

Ana Botrić, Goran Gregov

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ana BotrićUniversity of Rijeka, Faculty of Engineering, Vukovarska 58, 51000 Rijeka, Croatia.ORCID 0009-0006-1537-6045
Goran GregovUniversity of Rijeka, Faculty of Engineering, Vukovarska 58, 51000 Rijeka, Croatia.ORCID 0000-0001-7662-5793

Funding

University of Rijeka uniri-iz-25-231
6 · The paper itself

Abstract

This study presents the innovative design and development of biomimetic origami-based soft robotic grippers capable of two-stage grasping. Inspired by the biological structure of the sea urchin mouth, which combines external rigid teeth with an internal soft membrane, the proposed grippers employ origami architectures to achieve coordinated two-stage grasping. Novel waterbomb and Miura-ori origami architectures were introduced, enabling the formation of external and internal teeth. The developed grippers integrate an elastomeric membrane with an internal origami structure that enables contraction-driven folding under negative-pressure actuation. Multiple gripper configurations with varying dimensions are fabricated using paper and polymer-laminated paper skeletons. An energy-based modeling framework is introduced to describe the pressure-force relationship while accounting for the effects of structural deformation. Experimental evaluations conducted at different negative-pressure values quantified grasping performance and holding force. Imprint-based analysis confirmed the two-stage grasping mechanism, while grasping capability investigations demonstrated compliant interaction with delicate objects. Holding forces were measured using cylindrical metal and spherical wooden test objects of varying sizes and orientations. The waterbomb-based gripper achieved the most consistent performance, particularly for cylindrical objects, reaching a maximum holding force of 70 N, whereas the Miura-ori provided improved adaptability and higher holding forces for spherical objects, reaching 74.8 N, and maximum force-to-weight ratios of 327.2 and 346.6 were achieved for the waterbomb- and Miura-ori-based grippers, respectively.

Indexed as

biomimeticsorigamirobotic grippersoft roboticstwo-stage grasping

Identifiers

PMID42505499
PMCPMC13406422

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.