Presentation + Paper
20 April 2022 Experimental investigation of boundary condition effects in bipennate fluidic artificial muscle bundles
Author Affiliations +
Abstract
In this study, the implementation and performance of bipennate topology fluidic artificial muscle (FAM) bundles operating under varying boundary conditions is investigated and quantified experimentally. Soft actuators are of great interest to design engineers due to their inherent flexibility and potential to improve safety in human robot interactions. McKibben fluidic artificial muscles are soft actuators which exhibit high force to weight ratios and dynamically replicate natural muscle movement. These features, in addition to their low fabrication cost, set McKibben FAMs apart as attractive components for an actuation system. Previous studies have shown that there are significant advantages in force and contraction outputs when using bipennate topology FAM bundles as compared to the conventional parallel topology1 . In this study, we will experimentally explore the effects of two possible boundary conditions imposed on FAMs within a bipennate topology. One boundary condition is to pin the muscle fiber ends with fixed pin spacings while the other is biologically inspired and constrains the muscle fibers to remain in contact. This paper will outline design considerations for building a test platform for bipennate fluidic artificial muscle bundles with varying boundary conditions and present experimental results quantifying muscle displacement and force output. These metrics are used to analyze the tradespace between the two boundary conditions and the effect of varying pennation angles.
Conference Presentation
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Rebecca Hart, Emily Duan, and Matthew Bryant "Experimental investigation of boundary condition effects in bipennate fluidic artificial muscle bundles", Proc. SPIE 12041, Bioinspiration, Biomimetics, and Bioreplication XII, 1204108 (20 April 2022); https://doi.org/10.1117/12.2615896
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KEYWORDS
Artificial muscles

Actuators

Connective tissue

Motion models

Safety

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