Empirically Adapted Model for the Handling of Variable Geometries with Vacuum-Based Granulate Grippers

Abstract

AbstractCurrent industrial trends show an increasing demand for individualized products, which require highly flexible yet automated production systems. Universal handling systems offer an efficient solution for the flexible and safe handling of differing component geometries and shapes. An innovative gripper for form-flexible handling combining vacuum systems with the flexibility of granulate grippers was established in previous research and has continued to prove its flexibility by gripping wide varieties of object geometries. The current challenge of modelling and predicting gripping forces for this new gripper is addressed in this research. Multiple object geometries are selected and examined, with the parameters affecting the air permeability being the most important influence for the gripping forces. Along with an overview of influencing factors and parameters, a framework for a linear model enabling the prediction of gripping forces for different object shapes is developed. The basis for automated prediction of gripping strengths for different types of objects is established with this research and could be adapted with other, non-analytical models such as machine learning in the future.