Exploring Concurrent Multi-materials and Multiscale Hybrid Topology Optimization for Lightweight Porous Gripping Mechanism

Our research focuses on optimizing soft robotic gripper designs by employing an innovative hybrid topology approach with the aim of creating lightweight and porous grippers. Addressing the complex challenge of multiscale, multilateral topology optimization, we use a hybrid technique that combines SIMP (Solid Isotropic Material with Penalization) for macroscale optimization and MSB (Metaheuristic Structural Binary Distribution) for microscale optimization. At the microscale, our efforts are directed towards enhancing Young's modulus for weight reduction, considering orthotropic materials. Numerical examples in our study illustrate the adaptability of the microscale design to spatial configurations within both macro and microstructures. Various scenarios in macrostructure design demonstrate an advanced approach to strain energy distribution at the macroscale. Our innovative hybrid approach, integrating SIMP as for the macro-scale and MSB for micro-scale design, enables optimal designs while significantly reducing computational costs. This design methodology has the potential to yield novel, durable, lightweight, and porous soft robotic grippers with exceptional elastic flexibility.