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Advances in Soft Robotics: Design, Sensing and Control

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: closed (15 May 2023) | Viewed by 5362

Special Issue Editors


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Guest Editor
Automation & Robotics Research Group, University of Luxembourg, Luxembourg, Luxembourg
Interests: soft robotics; reconfigurable robotics; robot control; robotic manipulation and grasping
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Mechanical Engineering, National University of Singapore, Singapore
Interests: soft robotics; applied mathematics; shell theory; fracture mechanics; continuum mechanics & elasticity

Special Issue Information

Dear Colleagues,

In the last decade, soft robots have attracted considerable research interest in the robotics community. They can generate different biomimetic locomotion such as rolling, jumping, crawling, and swimming. Moreover, to address different deformation modes such as bending, rotation, twisting, and contraction/expansion, a variety of soft robots have been designed and fabricated. On the other hand, soft material robotics relies on compliant materials that are inherently impedance matched to natural environments. Accordingly, extensive applications ranging from biomedical and wearable technologies to architecture, art, and education have been explored.

Soft robots have the ability to achieve any kinematic configuration through deformations, with this benefit being derived from compliant materials. This increases the complexity within existing modelling, sensing, and control frameworks, motivating researchers to develop novel techniques for soft robots. The aim of this collection is to bring together papers focusing on recent advances in soft robotics. It explicitly aims to collect papers with three main scopes, i.e., i) the design and manufacturing of soft robotics. This can include recent development in the design and fabrication of soft actuators and soft robotics. ii) Sensing in soft robotics, which welcomes papers developing soft sensing-like stretchable sensors, resistive and capacitive stretchable sensing, magnetic sensing, and optoelectronic sensing for soft robotics. Iii) The control of soft robotics, with papers being on both the model-based and model-free control of soft robotics being of interest. Papers that study data-driven methods or machine learning for the modelling and control of soft robotics are highly encouraged for submission.

The original research and results within the scope of this section will be peer-reviewed, and these novel studies will be published to be shared with other experts in the soft robotics, sensors, and control communities. This section is also a platform through which comprehensive review papers on more recent areas in the design, sensing and control of soft robotics can be shared.

Topics of interest for this collection include but are not limited to:

  • Topology-optimized design in soft robotics;
  • Manufacturing methods in soft robotics;
  • Additive and shape deposition manufacturing in soft robotics;
  • Shape memory alloys;
  • Soft smart structures;
  • Soft and stretchable sensors;
  • Resistive and capacitive stretchable sensing;
  • Magnetic and optoelectronic sensing;
  • Model-based control of soft robotics;
  • Static and dynamic control of soft robotics;
  • Data-driven models in soft robotics;
  • Machine learning in soft robotics.

Dr. Hamed Rahimi Nohooji
Dr. Amirreza Fahim Golestaneh
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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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 (2 papers)

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16 pages, 5502 KiB  
Article
A Geometric Approach towards Inverse Kinematics of Soft Extensible Pneumatic Actuators Intended for Trajectory Tracking
by Mahboubeh Keyvanara, Arman Goshtasbi and Irene A. Kuling
Sensors 2023, 23(15), 6882; https://doi.org/10.3390/s23156882 - 3 Aug 2023
Viewed by 1052
Abstract
Soft robots are interesting examples of hyper-redundancy in robotics. However, the nonlinear continuous dynamics of these robots and the use of hyper-elastic and visco-elastic materials make modeling these robots more complicated. This study presents a geometric inverse kinematics (IK) model for trajectory tracking [...] Read more.
Soft robots are interesting examples of hyper-redundancy in robotics. However, the nonlinear continuous dynamics of these robots and the use of hyper-elastic and visco-elastic materials make modeling these robots more complicated. This study presents a geometric inverse kinematics (IK) model for trajectory tracking of multi-segment extensible soft robots, where each segment of the soft actuator is geometrically approximated with a rigid links model to reduce the complexity. In this model, the links are connected with rotary and prismatic joints, which enable both the extension and rotation of the robot. Using optimization methods, the desired configuration variables of the soft actuator for the desired end-effector positions were obtained. Furthermore, the redundancy of the robot is applied for second task applications, such as tip angle control. The model’s performance was investigated through kinematics and dynamics simulations and numerical benchmarks on multi-segment soft robots. The results showed lower computational costs and higher accuracy compared to most existing models. The method is easy to apply to multi-segment soft robots in both 2D and 3D, and it was experimentally validated on 3D-printed soft robotic manipulators. The results demonstrated the high accuracy in path following using this technique. Full article
(This article belongs to the Special Issue Advances in Soft Robotics: Design, Sensing and Control)
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24 pages, 1144 KiB  
Article
Comparison of Modern Control Methods for Soft Robots
by Malte Grube, Jan Christian Wieck and Robert Seifried
Sensors 2022, 22(23), 9464; https://doi.org/10.3390/s22239464 - 3 Dec 2022
Cited by 5 | Viewed by 2673
Abstract
With the rise in new soft robotic applications, the control requirements increase. Therefore, precise control methods for soft robots are required. However, the dynamic control of soft robots, which is required for fast movements, is still an open topic and will be discussed [...] Read more.
With the rise in new soft robotic applications, the control requirements increase. Therefore, precise control methods for soft robots are required. However, the dynamic control of soft robots, which is required for fast movements, is still an open topic and will be discussed here. In this contribution, one kinematic and two dynamic control methods for soft robots are examined. Thereby, an LQI controller with gain scheduling, which is new to soft robotic applications, and an MPC controller are presented. The controllers are compared in a simulation regarding their accuracy and robustness. Additionally, the required implementation effort and computational effort is examined. For this purpose, the trajectory tracking control of a simple soft robot is studied for different trajectories. The soft robot is beam-shaped and tendon-actuated. It is modeled using the piecewise constant curvature model, which is one of the most popular modeling techniques in soft robotics. In this paper, it is shown that all three controllers are able to follow the examined trajectories. However, the dynamic controllers show much higher accuracy and robustness than the kinematic controller. Nevertheless, it should be noted that the implementation and computational effort for the dynamic controllers is significantly higher. Therefore, kinematic controllers should be used if movements are slow and small oscillations can be accepted, while dynamic controllers should be used for faster movements with higher accuracy or robustness requirements. Full article
(This article belongs to the Special Issue Advances in Soft Robotics: Design, Sensing and Control)
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