DOI: 10.1108/ijcst-08-2025-0136 ISSN: 0955-6222

Calculation model of critical buckling force of plain weave fabric for textile grasping by soft gripper

Sen Zhu, Yawei Ren, Junqiang Su, Fenglin Huang, Nan Wang

Purpose

This study proposes a prediction model for buckling force of plain-woven fabrics, aiming to optimize parameter settings for robotic grasping manipulators in layer-by-layer separation of stacked fabric plies, thereby enhancing the success rates of first-attempt grasping.

Design/methodology/approach

At the soft gripper-fabric contact interface, the prediction accuracy of grasping parameters is insufficient. To investigate the underlying causes, this study conducts a theoretical analysis based on the limitations of existing textile buckling force standards (ASTM D1388 and ISO 9073–7) and conventional prediction methodologies in this specific application scenario. It revealed limitations in applying Euler's formula-derived buckling values and standard testing protocols to practical grasping scenarios involving stacked textile layers, underscoring the necessity for specialized characterization approaches.

Findings

Subsequently focusing on plain-woven fabrics, we conducted grasping experiments coupled with finite element analysis to elucidate buckling manifestation mechanisms at fabric-manipulator interfaces. Through multivariate analysis of fabric thickness, yarn density and critical buckling force parameters, thickness emerged as the predominant predictor of buckling behavior. This investigation yielded an empirical buckling force prediction model Pcr-simulated derived from fundamental fabric properties.

Originality/value

Based on the above research results, the plain weave fabric prediction model is proposed as Pcr = 0.238 + 2.634t3 – 0.228E/ρ. These findings establish a framework for intelligent grasping system development in textile handling applications. The proposed model advances current methodologies for plain woven fabrics by (1) introducing thickness-driven buckling prediction and (2) quantifying system correction factors.

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