Editorial Board Members' Collection Series: "Soft Robotics"

A special issue of Robotics (ISSN 2218-6581). This special issue belongs to the section "Soft Robotics".

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 10834

Special Issue Editors


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Guest Editor
Maryland Robotic Center, Department of Chemical & Biomolecular Engineering, University of Maryland, College Park, MD 20742, USA
Interests: multifunctional robotic materials; 2D materials applied to next-generation wearable technologies, deformable electronics and smart soft robotics
Department of Mechanical Engineering, University of Auckland, Auckland 1142, New Zealand
Interests: wearable soft sensors and actuators; soft robots; rehabilitation robots
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This series will focus on mechanics, control, design, conceptualization, fabrication, and applications of soft robotic systems. Papers especially addressing the theoretical, experimental, practical, and technological aspects of soft robotics and extending concepts and methodologies, from classical robotics to soft robotics, will be highly suitable for this series. Potential topics include but are not limited to:

  • Materials (e.g., smart, responsive, and structural) for soft robotics;
  • Application of the programmable matter concept to soft robotics;
  • Soft smart materials amenable to additive manufacturing, with programmable mechanical (stiffness, damping and similar) and electrical (resistance, capacitance) properties;
  • Novel fabrication techniques such as additive manufacturing for soft robotics;
  • Actuation, locomotion, manipulation, and sensing concepts for soft robotics;
  • Soft or compliant mechanisms for soft robotics;
  • Composite structures with programmable stiffness and damping;
    Modeling, analysis, and control of soft robotic systems;
  • Stretchable and flexible power sources and electronics for soft robotics;
    Compliance matching and interface for human-machine interaction;
  • Design optimization techniques for soft robotics;
  • Biologically inspired concepts for soft robotics;
  • Mechanics of soft robotic mechanisms and devices;
  • Simulation and analysis tools for soft robotics;
  • Design concepts based on embodied intelligence and morphological computation;
  • Applications, case studies and prototyping of soft robotics.

Dr. Po-Yen Chen
Dr. Kean Aw
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Robotics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (5 papers)

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Research

18 pages, 8386 KiB  
Article
Fiber Jamming of Magnetorheological Elastomers as a Technique for the Stiffening of Soft Robots
by Taylan Atakuru, Fatih Kocabaş, Niccolò Pagliarani, Matteo Cianchetti and Evren Samur
Robotics 2024, 13(1), 16; https://doi.org/10.3390/robotics13010016 - 17 Jan 2024
Viewed by 1649
Abstract
There has been a notable focus on the adoption of jamming-based technologies, which involve increasing the friction between grains, layers, or fibers to achieve variable stiffness capability in soft robots. Additionally, magnetorheological elastomers (MREs) that show magnetic-field-dependent viscoelasticity have great potential as a [...] Read more.
There has been a notable focus on the adoption of jamming-based technologies, which involve increasing the friction between grains, layers, or fibers to achieve variable stiffness capability in soft robots. Additionally, magnetorheological elastomers (MREs) that show magnetic-field-dependent viscoelasticity have great potential as a material for varying stiffness. This study proposes a hybrid method (magnetic jamming of MRE fibers) for enhancing the stiffness of soft robots, combining a jamming-based with a viscosity-based method. First, a fiber jamming structure is developed and integrated into a soft robot, the STIFF-FLOP manipulator, to prove the concept of the magnetic jamming of MRE fibers. Then, based on the proposed method, a variable stiffness device actuated by electro-permanent magnets is developed. The device is integrated into the same manipulator and the electronically controlled magnetic jamming and stiffening of the manipulator is demonstrated. The experimental results show that stiffness gain in bending and compression is achieved with the proposed method. The outcomes of this investigation demonstrate that the proposed hybrid stiffening technique presents a promising avenue for realizing variable and controllable stiffness in soft robots. Full article
(This article belongs to the Special Issue Editorial Board Members' Collection Series: "Soft Robotics")
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30 pages, 5705 KiB  
Article
Length Modelling of Spiral Superficial Soft Strain Sensors Using Geodesics and Covering Spaces
by Abdullah Al-Azzawi, Peter Stadler, He Kong and Salah Sukkarieh
Robotics 2023, 12(6), 164; https://doi.org/10.3390/robotics12060164 - 01 Dec 2023
Viewed by 1565
Abstract
Piecewise constant curvature soft actuators can generate various types of movements. These actuators can undergo extension, bending, rotation, twist, or a combination of these. Proprioceptive sensing provides the ability to track their movement or estimate their state in 3D space. Several proprioceptive sensing [...] Read more.
Piecewise constant curvature soft actuators can generate various types of movements. These actuators can undergo extension, bending, rotation, twist, or a combination of these. Proprioceptive sensing provides the ability to track their movement or estimate their state in 3D space. Several proprioceptive sensing solutions were developed using soft strain sensors. However, current mathematical models are only capable of modelling the length of the soft sensors when they are attached to actuators subjected to extension, bending, and rotation movements. Furthermore, these models are limited to modelling straight sensors and incapable of modelling spiral sensors. In this study, for both the spiral and straight sensors, we utilise concepts in geodesics and covering spaces to present a mathematical length model that includes twist. This study is limited to the Piecewise constant curvature actuators and demonstrates, among other things, the advantages of our model and the accuracy when including and excluding twist. We verify the model by comparing the results to a finite element analysis. This analysis involves multiple simulation scenarios designed specifically for the verification process. Finally, we validate the theoretical results with previously published experimental results. Then, we discuss the limitations and possible applications of our model using examples from the literature. Full article
(This article belongs to the Special Issue Editorial Board Members' Collection Series: "Soft Robotics")
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19 pages, 1052 KiB  
Article
A Novel Actor—Critic Motor Reinforcement Learning for Continuum Soft Robots
by Luis Pantoja-Garcia, Vicente Parra-Vega, Rodolfo Garcia-Rodriguez and Carlos Ernesto Vázquez-García
Robotics 2023, 12(5), 141; https://doi.org/10.3390/robotics12050141 - 09 Oct 2023
Cited by 1 | Viewed by 2828
Abstract
Reinforcement learning (RL) is explored for motor control of a novel pneumatic-driven soft robot modeled after continuum media with a varying density. This model complies with closed-form Lagrangian dynamics, which fulfills the fundamental structural property of passivity, among others. Then, the question arises [...] Read more.
Reinforcement learning (RL) is explored for motor control of a novel pneumatic-driven soft robot modeled after continuum media with a varying density. This model complies with closed-form Lagrangian dynamics, which fulfills the fundamental structural property of passivity, among others. Then, the question arises of how to synthesize a passivity-based RL model to control the unknown continuum soft robot dynamics to exploit its input–output energy properties advantageously throughout a reward-based neural network controller. Thus, we propose a continuous-time Actor–Critic scheme for tracking tasks of the continuum 3D soft robot subject to Lipschitz disturbances. A reward-based temporal difference leads to learning with a novel discontinuous adaptive mechanism of Critic neural weights. Finally, the reward and integral of the Bellman error approximation reinforce the adaptive mechanism of Actor neural weights. Closed-loop stability is guaranteed in the sense of Lyapunov, which leads to local exponential convergence of tracking errors based on integral sliding modes. Notably, it is assumed that dynamics are unknown, yet the control is continuous and robust. A representative simulation study shows the effectiveness of our proposal for tracking tasks. Full article
(This article belongs to the Special Issue Editorial Board Members' Collection Series: "Soft Robotics")
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17 pages, 6331 KiB  
Article
Grasping Profile Control of a Soft Pneumatic Robotic Gripper for Delicate Gripping
by Gridsada Phanomchoeng, Patchara Pitchayawetwongsa, Nattaphat Boonchumanee, Saravut Lin and Ratchatin Chancharoen
Robotics 2023, 12(4), 107; https://doi.org/10.3390/robotics12040107 - 17 Jul 2023
Cited by 2 | Viewed by 2409
Abstract
Soft pneumatic grippers (SPGs) have garnered significant attention and recognition in various industries owing to their remarkable flexibility, safety, and adaptability. They excel in manipulating delicate, irregularly shaped, and soft objects, surpassing the limitations of conventional grippers. However, effective control techniques for managing [...] Read more.
Soft pneumatic grippers (SPGs) have garnered significant attention and recognition in various industries owing to their remarkable flexibility, safety, and adaptability. They excel in manipulating delicate, irregularly shaped, and soft objects, surpassing the limitations of conventional grippers. However, effective control techniques for managing the grasping profile of SPGs are still under development. Simple on–off pressure control using a regulator valve is inadequate for delicate gripping with pneumatic robot grippers. To address this, a synergy pressure control system was implemented. In addition, a proportional–integral–derivative control technique, complemented by an unknown input observer, was devised to control the volume of the soft pneumatic robotic gripper, ensuring its alignment with the desired volume level. The simulation and experimental results provide substantial evidence of the effectiveness of the developed control technique and the unknown input observer in managing the volume and pressure of the gripper. Consequently, this breakthrough empowers precise and delicate gripping actions, enabling the handling of delicate objects such as tofu. Full article
(This article belongs to the Special Issue Editorial Board Members' Collection Series: "Soft Robotics")
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10 pages, 5106 KiB  
Article
Stretchable and Compliant Sensing of Strain, Pressure and Vibration of Soft Deformable Structures
by Darren Zi Hian Yeo, Catherine Jiayi Cai, Po-Yen Chen and Hongliang Ren
Robotics 2022, 11(6), 146; https://doi.org/10.3390/robotics11060146 - 06 Dec 2022
Cited by 1 | Viewed by 1604
Abstract
Soft robotic and medical devices will greatly benefit from stretchable and compliant pressure sensors that can detect deformation and contact forces for control and task safety. In addition to traditional 2D buckling via planar substrates, 3D buckling via curved substrates has emerged as [...] Read more.
Soft robotic and medical devices will greatly benefit from stretchable and compliant pressure sensors that can detect deformation and contact forces for control and task safety. In addition to traditional 2D buckling via planar substrates, 3D buckling via curved substrates has emerged as an alternative approach to generate tunable and highly convoluted hierarchical wrinkle morphologies. Such wrinkles may provide advantages in pressure sensing, such as increased sensitivity, ultra-stretchability, and detecting changing curvatures. In this work, we fabricated stretchable sensors using wrinkled MXene electrodes obtained from 3D buckling. We then characterized the sensors’ performance in detecting strain, pressure, and vibrations. The fabricated wrinkled MXene electrode exhibited high stretchability of up to 250% and has a strain sensitivity of 0.1 between 0 and 80%. The fabricated bilayer MXene pressure sensor exhibited a pressure sensitivity of 0.935 kPa−1 and 0.188 kPa−1 at the lower (<0.25 kPa) and higher-pressure regimes (0.25 kPa–2.0 kPa), respectively. The recovery and response timing of the wrinkled MXene pressure sensor was found to be 250 ms and 400 ms, respectively. The sensor was also capable of detecting changing curvatures upon mounting onto an inflating balloon. Full article
(This article belongs to the Special Issue Editorial Board Members' Collection Series: "Soft Robotics")
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