Automated design of pneumatic soft grippers through design-dependent multi-material topology optimization

TL;DR

This paper introduces a novel topology optimization method that automatically designs multi-material soft robotic grippers, leveraging 3D printing and pressure boundary considerations to enhance design space and simulation accuracy.

Contribution

It presents a new topology optimization formulation for multi-material soft grippers that accounts for internal and external pressures, enabling automated, bespoke design for applications like fruit-picking.

Findings

The method generates multi-material soft grippers with expanded design options.

It accurately models internal and external pressure boundaries.

The approach improves simulation fidelity and manufacturability of soft robotic devices.

Abstract

Soft robotic grasping has rapidly spread through the academic robotics community in recent years and pushed into industrial applications. At the same time, multimaterial 3D printing has become widely available, enabling the monolithic manufacture of devices containing rigid and elastic sections. We propose a novel design technique that leverages both technologies and can automatically design bespoke soft robotic grippers for fruit-picking and similar applications. We demonstrate the novel topology optimisation formulation that generates multi-material soft grippers, can solve internal and external pressure boundaries, and investigate methods to produce air-tight designs. Compared to existing methods, it vastly expands the searchable design space while increasing simulation accuracy.