Abstract
The high potential impact of soft robotics is hampered by a lack of actuators that combine high-force, high-work and high-power capabilities, limiting application in real-world problems. Typically, soft actuators are tuned to an application by gearing - for example, trading power for strain. An example of a recently developed soft-actuator which exploits such gearing is the dielectrophoretic liquid zipping (DLZ) actuator. DLZs can produce large strains ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$>\!99\%$</tex-math></inline-formula> ) and power densities comparable to biological muscles, but cannot achieve both in a single actuator. In this work, we introduce a muscle-mimetic DLZ ratcheting actuator (DLZ-R) that allows multiple DLZ-R heads to operate in parallel, thereby increasing force output without sacrificing stroke or power. We first characterise the effect of geometry on the performance of a 1-head DLZ-R, before demonstrating that the force, work, and power output of the DLZ-R scale linearly with the number of active DLZ heads. Next, we investigate the relationship between driving frequency and power output. Finally, we demonstrate a 12-head DLZ ratchet. We believe the DLZ-R represents a step towards soft actuators that can provide both high-work and high-power and the widespread use of soft technologies.
Highlights
T HE development of soft machines and robots could enable a new generation of autonomous systems that can operate in unpredictable and unstructured environments [1]– [3]
DISCUSSION & CONCLUSIONS In this paper, we have introduced the dielectrophoretic liquid zipping (DLZ)-R, a ratcheting actuator inspired by the sarcomeric structure of biological muscle
We have introduced the shape parameter, L∗, which characterises the degree of bending in a resting head, and have shown that best performance is achieved with L∗ = 0.4
Summary
T HE development of soft machines and robots could enable a new generation of autonomous systems that can operate in unpredictable and unstructured environments [1]– [3]. This could enable new applications in bio-medicine [4], ecology [5] and virtual reality [6]. JR was supported through EPSRC research grants EP/T020792/1, EP/V026518/1, EP/S026096/1, EP/R02961X/1, and by the Royal Academy of Engineering as a Chair in Emerging Technologies
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