SimTO: A simulation-based topology optimization framework for bespoke soft robotic grippers

TL;DR

SimTO is a simulation-based topology optimization framework that automatically extracts contact forces to design highly customized soft robotic grippers for complex, feature-rich objects, improving grasping safety and effectiveness.

Contribution

Introduces SimTO, a novel framework that automates load case extraction from physics simulation for topology optimization of soft grippers, enabling customization for complex objects without manual load specification.

Findings

Designs are highly specialized to target objects

Generated grippers generalize well to unseen objects

Framework automates load case extraction for topology optimization

Abstract

Soft robotic grippers are essential for grasping delicate, geometrically complex objects in manufacturing, healthcare and agriculture. However, existing grippers struggle to grasp feature-rich objects with high topological variability, including gears with sharp tooth profiles on automotive assembly lines, corals with fragile protrusions, or vegetables with irregular branching structures like broccoli. Unlike simple geometric primitives such as cubes or spheres, feature-rich objects lack a clear "optimal" contact surface, making them both difficult to grasp and susceptible to damage when grasped by existing gripper designs. Safe handling of such objects therefore requires specialized soft grippers whose morphology is tailored to the object's features. Topology optimization offers a promising approach for producing specialized grippers, but its utility is limited by the requirement for pre-defined load cases. For soft grippers interacting with feature-rich objects, these loads arise from hundreds of unpredictable gripper-object contact forces during grasping and are unknown a priori. To address this problem, we introduce SimTO, a framework that enables high-resolution topology optimization by automatically extracting load cases from a contact-based physics simulator, eliminating the need for manual load specification. Given an arbitrary feature-rich object, SimTO produces highly customized soft grippers with fine-grained morphological features tailored to the object geometry. Numerical results show our designs are not only highly specialized to feature-rich objects, but also generalize to unseen objects.