Cross-sectional Topology Optimization of Slender Soft Pneumatic Actuators using Genetic Algorithms and Geometrically Exact Beam Models

TL;DR

This paper presents a simulation-driven topology optimization method using genetic algorithms and geometrically exact beam models to design slender soft pneumatic actuators, reducing manual trial-and-error in the design process.

Contribution

It introduces a black-box topology optimization approach for soft actuators that efficiently finds designs meeting target workspaces, streamlining the design process.

Findings

Genetic algorithms effectively optimize actuator cross-sections for target workspaces.

The method reduces the need for multiple prototypes and manual trial-and-error.

Validated with three case studies demonstrating successful design generation.

Abstract

The design of soft robots is still commonly driven by manual trial-and-error approaches, requiring the manufacturing of multiple physical prototypes, which in the end, is time-consuming and requires significant expertise. To reduce the number of manual interventions in this process, topology optimization can be used to assist the design process. The design is then guided by simulations and numerous prototypes can be tested in simulation rather than being evaluated through laborious experiments. To implement this simulation-driven design process, the possible design space of a slender soft pneumatic actuator is generalized to the design of the circular cross-section. We perform a black-box topology optimization using genetic algorithms to obtain a cross-sectional design of a soft pneumatic actuator that is capable of reaching a target workspace defined by the end-effector positions at different pressure values. This design method is evaluated for three different case studies and target workspaces, which were either randomly generated or specified by the operator of the design assistant. The black-box topology optimization based on genetic algorithms proves to be capable of finding good designs under given plausible target workspaces. We considered a simplified simulation model to verify the efficacy of the employed method. An experimental validation has not yet been performed. It can be concluded that the employed black-box topology optimization can assist in the design process for slender soft pneumatic actuators. It supports at searching for possible design prototypes that reach points specified by corresponding actuation pressures. This helps reduce the trial-and-error driven iterative manual design process and enables the operator to focus on prototypes that already offer a good viable solution.