Fluid Mechanics of Pneumatic Soft Robots

Breitman, Peter; Matia, Yoav; Gat, Amir D.

doi:10.1089/soro.2020.0037

Cited by 26 publications

(13 citation statements)

References 28 publications

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“…acceleration in the development of control methods which aim to minimize the impact on robot mechanics via materials-centric design. Smart fluids and control via viscous effects are still nascent techniques for controlling soft robots, although recent advances in the modeling of the fluid mechanics within soft robots may lead to more sophisticated control in the future (Breitman et al, 2020). While among the best techniques for preserving a robot's compliance (with the exception of the field generating components in smart fluid control systems), their scalability has been underexplored.…”

Section: Discussionmentioning

confidence: 99%

Hardware Methods for Onboard Control of Fluidically Actuated Soft Robots

McDonald

Ranzani

2021

Front. Robot. AI

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Soft robots provide significant advantages over their rigid counterparts. These compliant, dexterous devices can navigate delicate environments with ease without damage to themselves or their surroundings. With many degrees of freedom, a single soft robotic actuator can achieve configurations that would be very challenging to obtain when using a rigid linkage. Because of these qualities, soft robots are well suited for human interaction. While there are many types of soft robot actuation, the most common type is fluidic actuation, where a pressurized fluid is used to inflate the device, causing bending or some other deformation. This affords advantages with regards to size, ease of manufacturing, and power delivery, but can pose issues when it comes to controlling the robot. Any device capable of complex tasks such as navigation requires multiple actuators working together. Traditionally, these have each required their own mechanism outside of the robot to control the pressure within. Beyond the limitations on autonomy that such a benchtop controller induces, the tether of tubing connecting the robot to its controller can increase stiffness, reduce reaction speed, and hinder miniaturization. Recently, a variety of techniques have been used to integrate control hardware into soft fluidic robots. These methods are varied and draw from disciplines including microfluidics, digital logic, and material science. In this review paper, we discuss the state of the art of onboard control hardware for soft fluidic robots with an emphasis on novel valve designs, including an overview of the prevailing techniques, how they differ, and how they compare to each other. We also define metrics to guide our comparison and discussion. Since the uses for soft robots can be so varied, the control system for one robot may very likely be inappropriate for use in another. We therefore wish to give an appreciation for the breadth of options available to soft roboticists today.

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Section: Discussionmentioning

confidence: 99%

Hardware Methods for Onboard Control of Fluidically Actuated Soft Robots

McDonald

Ranzani

2021

Front. Robot. AI

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“…Silicone elastomers and other polymers used in soft robotics literature, as well as the corresponding number of citations. For this graph, 45 articles were examined: Ecoflex [198][199][200][201][202][203][204][205], Dragon Skin 10/20/30/FX-Pro [206][207][208][209][210][211][212][213][214][215][216][217][218][219][220][221][222][223][224][225], Elastosil M4601 [199,202,218,[226][227][228][229], PDMS [198,208,[230][231][232][232][233][234], Smooth-Sil [200,207,209,218,222,…”

Section: Figurementioning

confidence: 99%

Soft Grippers for Automatic Crop Harvesting: A Review

Navas

Fernández

Sepúlveda

et al. 2021

Sensors

140

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Agriculture 4.0 is transforming farming livelihoods thanks to the development and adoption of technologies such as artificial intelligence, the Internet of Things and robotics, traditionally used in other productive sectors. Soft robotics and soft grippers in particular are promising approaches to lead to new solutions in this field due to the need to meet hygiene and manipulation requirements in unstructured environments and in operation with delicate products. This review aims to provide an in-depth look at soft end-effectors for agricultural applications, with a special emphasis on robotic harvesting. To that end, the current state of automatic picking tasks for several crops is analysed, identifying which of them lack automatic solutions, and which methods are commonly used based on the botanical characteristics of the fruits. The latest advances in the design and implementation of soft grippers are also presented and discussed, studying the properties of their materials, their manufacturing processes, the gripping technologies and the proposed control methods. Finally, the challenges that have to be overcome to boost its definitive implementation in the real world are highlighted. Therefore, this review intends to serve as a guide for those researchers working in the field of soft robotics for Agriculture 4.0, and more specifically, in the design of soft grippers for fruit harvesting robots.

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“…The deflection is written in terms of generalized coordinate and mode function as follows (Liu et al, 2017)Substituting equation (17) into equation (16) and using the orthogonality of normal modes shapes lead to discretized motion equations. The excitation force comes from the fluid pressure, while the pressure field can be written as follows (Breitman et al, 2020)where pin is inlet pressure and supposing that it is in the form pin(0,t)=pasin(ωt). By substituting pin into equations (18) and (20), the pressure field would be obtained as followsFinally, the motion equation can be found asand the coefficients of equation (22) are defined in Appendix A.…”

Section: System Description and Problem Formulationmentioning

confidence: 99%

“…It consists of elastomeric matrices with flexible embedded materials through the fluid–solid interface. This interface’s pressure and shear stress shape a deformation field within the elastic structure (Breitman et al, 2020; Matia et al, 2016). Researchers have considered the embedded fluidic network for grippers (Marchese et al, 2015), dual walking robot (Onal and Rus, 2013), and motion of fish robots (Liu et al, 2019; Wehner, 2016).…”

Section: Introductionmentioning

confidence: 99%

Steady-state dynamic analysis of a nonlinear fluidic soft actuator

Haji

Bamdad

2022

Journal of Vibration and Control

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The internal channel networks embedded within a soft structure can be a fruitful mechanism to create and activate actuators in the research fields of soft robotics. The deformation of the supporting elastic structure from the pressurized viscous fluid into the channels needs an accurate investigation. In this paper, accurate modeling and dynamic analysis of this nonlinear soft actuator is our goal. In this modeling, the soft actuator is considered the Euler–Bernoulli beam with large deflection and nonlinear strain. After implementing Hamilton’s principle, the assumed mode method is used to achieve the mathematical model in terms of the multi-mode system that is more similar to the flexible nature of the actuation system. Steady-state dynamics is investigated by a combination of the complex averaging method with arc-length continuation. The accuracy of the proposed modeling is validated by comparing simulation results to those obtained with a nonlinear finite element method and numerical method. It shows that only one-third of the degree-of-freedoms used for the finite element method are sufficient to obtain equivalent converged solutions with the proposed model. The effect of nonlinear strain and multi-mode consideration in the analysis of the proposed modeling is investigated. It is advantageous to analyze the system performance by looking into the geometrical parameters and fluid properties.

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Fluid Mechanics of Pneumatic Soft Robots

Cited by 26 publications

References 28 publications

Hardware Methods for Onboard Control of Fluidically Actuated Soft Robots

Hardware Methods for Onboard Control of Fluidically Actuated Soft Robots

Soft Grippers for Automatic Crop Harvesting: A Review

Steady-state dynamic analysis of a nonlinear fluidic soft actuator

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