Structural optimization and modelling for a new topology-optimized compliant gripper

This article presents a novel design synthesis framework for a compliant gripper in the robotics industry. The proposed method integrates the physical information, such as yield strength and the safety factor. Case study 1 aims to predict the stroke of the gripper's arm while incorporating the yield strength and safety factor as physical constraints for PGNN. Case study 2 focuses on modelling the clamping force with the same physical constraints. Hunger game search is coupled with PGNN. The final geometries of the gripper are determined through a parametric optimization. The results indicated that the hybridized framework is an efficient method for initializing novel compliant gripper designs and modelling their behaviours. A prototype of the gripper is manufactured using 3D printing, and clamping tests are performed to verify its functionality. The error between the predicted results and the actual results is relatively small, at less than 6.02%.