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Biomimetics
Special Issues
Bio-Optimization-Based Soft Robot Design
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Bio-Optimization-Based Soft Robot Design

A special issue of Biomimetics (ISSN 2313-7673). This special issue belongs to the section "Locomotion and Bioinspired Robotics".

Deadline for manuscript submissions: closed (25 January 2024) | Viewed by 4714

Special Issue Editor

Dr. Yilun Sun

E-Mail Website
Guest Editor
School of Engineering and Design, Technical University of Munich, 85748 Garching, Germany
Interests: bio-inspired robotics; soft robotics; topology optimization; compliant mechanism; locomotion robot; medical robotics

Special Issue Information

Dear Colleagues,

Compared with the conventional rigid-link-based robots, soft robots exhibit much higher flexibility and compliance, which enables them to safely interact with humans and delicate objects, navigate challenging terrains, and adapt to dynamic environments. This unique property of soft robots makes them ideal for applications where traditional robots may be impractical or unsafe. However, due to their complex geometrical structure and material properties, the design of soft robots still faces great challenges. In order to improve the design efficiency of soft robots, many bio-inspired design methods have been developed in recent years, drawing inspiration from biological evolution or optimization processes. By using advanced techniques such as topology optimization algorithms, evolutionary algorithms and artificial neural networks, these methods can automatically generate the shape of soft robots to achieve specific functionalities. By mimicking nature's efficiency, these approaches enable the creation of highly adaptive and efficient soft robots with promising real-world applications. 

In this Special Issue, we seek to exhibit the latest research results and findings on bio-optimization methods for designing soft robots as well as their real-world applications. We invite computer scientists, mechanical and electrical engineers, material scientists, physicists and experts from diverse disciplines to present their pioneering work on bio-optimization-based soft robot design.

Topics for this Special Issue include but are not limited to:

  • Novel shape and topology optimization algorithms for designing soft robots
  • Novel evolutionary algorithms for designing soft robots
  • Learning-based methods for designing soft robots
  • Modeling of soft robots with novel materials and actuation strategies
  • Manufacturing methods for soft robots designed by bio-optimization methods
  • Control strategies for soft robots designed by bio-optimization methods
  • Real-world applications of soft robots designed by bio-optimization methods.

Dr. Yilun Sun
Guest Editor

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. Biomimetics 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 2200 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.

Keywords

  • bio-optimization-based design method
  • soft robotics
  • topology optimization
  • evolutionary algorithm
  • genetic algorithm
  • artificial neural network
  • material modeling
  • soft robot control
  • additive manufacturing

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Published Papers (2 papers)

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13 pages, 5845 KiB  
Article
Design Optimization of a Soft Robotic Rehabilitation Glove Based on Finger Workspace Analysis
by Yechan Lee and Hyung-Soon Park
Biomimetics 2024, 9(3), 172; https://doi.org/10.3390/biomimetics9030172 - 13 Mar 2024
Cited by 2 | Viewed by 1958
Abstract
The finger workspace is crucial for performing various grasping tasks. Thus, various soft rehabilitation gloves have been developed to assist individuals with paralyzed hands in activities of daily living (ADLs) or rehabilitation training. However, most soft robotic glove designs are insufficient to assist [...] Read more.
The finger workspace is crucial for performing various grasping tasks. Thus, various soft rehabilitation gloves have been developed to assist individuals with paralyzed hands in activities of daily living (ADLs) or rehabilitation training. However, most soft robotic glove designs are insufficient to assist with various hand postures because most of them use an underactuated mechanism for design simplicity. Therefore, this paper presents a methodology for optimizing the design of a high-degree-of-freedom soft robotic glove while not increasing the design complexity. We defined the required functional workspace of the index finger based on ten frequently used grasping postures in ADLs. The design optimization was achieved by simulating the proposed finger–robot model to obtain a comparable workspace to the functional workspace. In particular, the moment arm length for extension was optimized to facilitate the grasping of large objects (precision disk and power sphere), whereas a torque-amplifying routing design was implemented to aid the grasping of small objects (lateral pinch and thumb–two-finger pinch). The effectiveness of the optimized design was validated through testing with a stroke survivor and comparing the assistive workspace. The observed workspace demonstrated that the optimized glove design could assist with nine out of the ten targeted grasping posture functional workspaces. Furthermore, the assessment of the grasping speed and force highlighted the glove’s usability for various rehabilitation activities. We also present and discuss a generalized methodology to optimize the design parameters of a soft robotic glove that uses an underactuated mechanism to assist the targeted workspace. Overall, the proposed design optimization methodology serves as a tool for developing advanced hand rehabilitation robots, as it offers insight regarding the importance of routing optimization in terms of the workspace. Full article
(This article belongs to the Special Issue Bio-Optimization-Based Soft Robot Design)
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18 pages, 3400 KiB  
Article
Design Optimization of a Hybrid-Driven Soft Surgical Robot with Biomimetic Constraints
by Majid Roshanfar, Javad Dargahi and Amir Hooshiar
Biomimetics 2024, 9(1), 59; https://doi.org/10.3390/biomimetics9010059 - 21 Jan 2024
Cited by 1 | Viewed by 2206
Abstract
The current study investigated the geometry optimization of a hybrid-driven (based on the combination of air pressure and tendon tension) soft robot for use in robot-assisted intra-bronchial intervention. Soft robots, made from compliant materials, have gained popularity for use in surgical interventions due [...] Read more.
The current study investigated the geometry optimization of a hybrid-driven (based on the combination of air pressure and tendon tension) soft robot for use in robot-assisted intra-bronchial intervention. Soft robots, made from compliant materials, have gained popularity for use in surgical interventions due to their dexterity and safety. The current study aimed to design a catheter-like soft robot with an improved performance by minimizing radial expansion during inflation and increasing the force exerted on targeted tissues through geometry optimization. To do so, a finite element analysis (FEA) was employed to optimize the soft robot’s geometry, considering a multi-objective goal function that incorporated factors such as chamber pressures, tendon tensions, and the cross-sectional area. To accomplish this, a cylindrical soft robot with three air chambers, three tendons, and a central working channel was considered. Then, the dimensions of the soft robot, including the length of the air chambers, the diameter of the air chambers, and the offsets of the air chambers and tendon routes, were optimized to minimize the goal function in an in-plane bending scenario. To accurately simulate the behavior of the soft robot, Ecoflex 00-50 samples were tested based on ISO 7743, and a hyperplastic model was fitted on the compression test data. The FEA simulations were performed using the response surface optimization (RSO) module in ANSYS software, which iteratively explored the design space based on defined objectives and constraints. Using RSO, 45 points of experiments were generated based on the geometrical and loading constraints. During the simulations, tendon force was applied to the tip of the soft robot, while simultaneously, air pressure was applied inside the chamber. Following the optimization of the geometry, a prototype of the soft robot with the optimized values was fabricated and tested in a phantom model, mimicking simulated surgical conditions. The decreased actuation effort and radial expansion of the soft robot resulting from the optimization process have the potential to increase the performance of the manipulator. This advancement led to improved control over the soft robot while additionally minimizing unnecessary cross-sectional expansion. The study demonstrates the effectiveness of the optimization methodology for refining the soft robot’s design and highlights its potential for enhancing surgical interventions. Full article
(This article belongs to the Special Issue Bio-Optimization-Based Soft Robot Design)
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