Concepedia

TLDR

Soft fluidic actuators made of elastomeric matrices with embedded flexible materials are attractive for robotics because they are affordable and customizable, but their potential is limited by intuition‑based design, and a deeper understanding will enable rapid iteration and more complex motions. This paper analyzes the principle of operation of these actuators using experimentally validated quasi‑static analytical and finite‑element models for bending and force generation, and proposes systematic design rules linking output to input pressure and geometry. The authors employ quasi‑static analytical and finite‑element models, validated experimentally, to describe bending in free space and force generation when the actuator contacts an object. The study delivers systematic design rules that relate actuator output to pressure and geometry, and demonstrates a controller that converts pressure to bending angle in real time.

Abstract

Soft fluidic actuators consisting of elastomeric matrices with embedded flexible materials are of particular interest to the robotics community because they are affordable and can be easily customized to a given application. However, the significant potential of such actuators is currently limited as their design has typically been based on intuition. In this paper, the principle of operation of these actuators is comprehensively analyzed and described through experimentally validated quasi-static analytical and finite-element method models for bending in free space and force generation when in contact with an object. This study provides a set of systematic design rules to help the robotics community create soft actuators by understanding how these vary their outputs as a function of input pressure for a number of geometrical parameters. Additionally, the proposed analytical model is implemented in a controller demonstrating its ability to convert pressure information to bending angle in real time. Such an understanding of soft multimaterial actuators will allow future design concepts to be rapidly iterated and their performance predicted, thus enabling new and innovative applications that produce more complex motions to be explored.

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