Design and Development of Fin-Ray Finger using Topology Optimization with Multiple Load Cases

This research focuses on developing a soft robotic gripper using topology optimization method to address the need for soft and flexible grippers capable of delicately grasping complex objects with high conformability. The gripper design draws inspiration from the triangular shape of fin-ray fingers with rectangular crossbeams, mimicking the physiology of fish fins traditionally employed for soft grasping applications. However, existing design methods face limitations in high-load applications due to structural stiffness constraints. To overcome this limitation, this study proposes a mathematical reconstruction of the design framework using the topology optimization method. The objective function is formulated to maximize deflection, ensuring optimal wrapping capabilities of the finger. Constraints include the force vector, global stiffness, and volume fraction (v f ). The study incorporates multiple load cases to simulate the dynamic forces experienced by the robotic fingers during object manipulation in a changing environment. Using mathematical gradients, various fingers are developed for different volume fractions and rectangular crossbeams of fin-ray effect. The MATLAB code can adopt any mesh size and calculate the performance values of the finger. The optimized fingers exhibit maximum deflection with superior wrapping capabilities. The computational time for developed topology optimization algorithm is less than 100 sec. The best fingers are selected and 3D printed using TPU 95A material for validating simulation results and demonstrating the grasping tasks using Ultimaker S3 printer and Universal robot (UR3e). The simulation and experimental results exhibit a strong agreement, affirming the effectiveness of the proposed design approach.