Development of robotic automation solutions for limp flexible material handling leveraging a finite element modelling technique

Fiber composite materials exhibit exceptional specific stiffness and strength compared to traditional engineering materials. Nevertheless, automating the handling of limp flexible materials like fabrics remains a challenging process, often relying on multi-stage manual operations for hand layups. In this study, carbon fabric properties were initially characterized through standard experiments to develop and calibrate a finite element (FE) model. The FE model was subsequently validated against real-world pick-and-place tests involving soft robotic grippers. The validation results demonstrated a high correlation between the FE model and experiments, achieving an average accuracy of 97.2% for fabric projected area and 84.6% for fabric vertices’ displacement. Additionally, the FE model was used to design, evaluate, and optimize alternative automation strategies. It was discovered that a convex surface improved fabric projection area and placement accuracy by 5.9% and 1.9%, respectively, compared to a concave surface with the same curvature radius. Larger concave surfaces contributed to increased projected area and placement accuracy as well. Longitudinal pick-and-place operations also enhanced the projection area and placement accuracy compared to transverse handling processes. Achieving successful fabric pick-and-place operations necessitates a comprehensive system’s approach, considering the interaction between grippers, fabric, and mold surface. The FE model developed in this study will be further employed by the current research team in designing innovative compliant grippers tailored to complex mold surface geometries and specific fabric material requirements. The presented FE model offers valuable insights and paves the way for rapid, efficient, cost-effective, and secure implementation of automation solutions for handling limp flexible materials.