A Robotic Testing Platform for Pipelined Discovery of Resilient Soft Actuators

TL;DR

This paper introduces a robotic testing platform that systematically scans and optimizes the lifetime of dielectric elastomer actuators, significantly enhancing their durability and performance for robotic applications.

Contribution

It presents a novel automated testing robot that enables high-throughput lifetime scanning and optimization of soft actuators, pioneering a self-driving lab approach in this field.

Findings

Optimized parameters doubled actuator lifetime.

Achieved higher force and displacement outputs.

Demonstrated resilient quadruped robot with high payload capacity.

Abstract

Short lifetime under high electrical fields hinders the widespread robotic application of linear dielectric elastomer actuators (DEAs). Systematic scanning is difficult due to time-consuming per-sample testing and the high-dimensional parameter space affecting performance. To address this, we propose an optimization pipeline enabled by a novel testing robot capable of scanning DEA lifetime. The robot integrates electro-mechanical property measurement, programmable voltage input, and multi-channel testing capacity. Using it, we scanned the lifetime of Elastosil-based linear actuators across parameters including input voltage magnitude, frequency, electrode material concentration, and electrical connection filler. The optimal parameter combinations improved operational lifetime under boundary operating conditions by up to 100% and were subsequently scaled up to achieve higher force and displacement output. The final product demonstrated resilience on a modular, scalable quadruped walking robot with payload carrying capacity (>100% of its untethered body weight, and >700% of combined actuator weight). This work is the first to introduce a self-driving lab approach into robotic actuator design.