Biorobotics: 2nd Edition

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

Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 8618

Special Issue Editors


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Guest Editor
Department of Computer Science, Aberystwyth University, Ceredigion SY23 3DB, UK
Interests: bio-inspired robotics; biomechanics; animal and robot navigation; artificial intelligence

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Guest Editor
Faculty of Technology and Bionics, Rhine-Waal University of Applied Sciences, D-47533 Kleve, Germany
Interests: biomimetics; biological sensors and sensing; soft robotics, biofilms and biofouling; surface engineering
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Special Issue Information

Dear Colleagues,

Biorobotics is a key contributor to the growing field of biomimetics. The use of soft materials, sensors, and sensing of an environment for decision making and further engagement particularity in natural unstructured environments is key to both robotics and biology. Biorobotics provides a unique and innovative platform for the development of successful agent–environment interactions. This topic has the potential to provide key transfers of knowledge in both directions, from technological advances to hypothesis testing on biological behaviors and function of structures.

This Special Issue aims to highlight the recent advances in the field of biorobotics and to bring together biologists, engineers, and roboticists. This theme is inherently interdisciplinary, and thus focuses on bioinspired and biological robots but extends the topic to elements of their construction such as design, materials, sensing, and control. To successfully achieve this, we warmly encourage both original and review contributions from the fields of computational biology, cognitive science, comparative biomechanics, evolutionary biorobotics, and bio-inspired robotics.

Dr. Otar Akanyeti
Prof. Dr. Lily Chambers
Guest Editors

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Keywords

  • biorobotics
  • bio-inspired robots
  • comparative biomechanics
  • computational biology
  • evolutionary biorobotics

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Published Papers (5 papers)

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Research

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19 pages, 2854 KiB  
Article
Deep CNN-Based Static Modeling of Soft Robots Utilizing Absolute Nodal Coordinate Formulation
by Haitham El-Hussieny, Ibrahim A. Hameed and Ayman A. Nada
Biomimetics 2023, 8(8), 611; https://doi.org/10.3390/biomimetics8080611 - 14 Dec 2023
Cited by 3 | Viewed by 1729
Abstract
Soft continuum robots, inspired by the adaptability and agility of natural soft-bodied organisms like octopuses and elephant trunks, present a frontier in robotics research. However, exploiting their full potential necessitates precise modeling and control for specific motion and manipulation tasks. This study introduces [...] Read more.
Soft continuum robots, inspired by the adaptability and agility of natural soft-bodied organisms like octopuses and elephant trunks, present a frontier in robotics research. However, exploiting their full potential necessitates precise modeling and control for specific motion and manipulation tasks. This study introduces an innovative approach using Deep Convolutional Neural Networks (CNN) for the inverse quasi-static modeling of these robots within the Absolute Nodal Coordinate Formulation (ANCF) framework. The ANCF effectively represents the complex non-linear behavior of soft continuum robots, while the CNN-based models are optimized for computational efficiency and precision. This combination is crucial for addressing the complex inverse statics problems associated with ANCF-modeled robots. Extensive numerical experiments were conducted to assess the performance of these Deep CNN-based models, demonstrating their suitability for real-time simulation and control in statics modeling. Additionally, this study includes a detailed cross-validation experiment to identify the most effective model architecture, taking into account factors such as the number of layers, activation functions, and unit configurations. The results highlight the significant benefits of integrating Deep CNN with ANCF models, paving the way for advanced statics modeling in soft continuum robotics. Full article
(This article belongs to the Special Issue Biorobotics: 2nd Edition)
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15 pages, 4612 KiB  
Article
An Admittance Control Method Based on Parameters Fuzzification for Humanoid Steering Wheel Manipulation
by Tuochang Wu, Junkai Ren, Chuang Cheng, Xun Liu, Hui Peng and Huimin Lu
Biomimetics 2023, 8(6), 495; https://doi.org/10.3390/biomimetics8060495 - 19 Oct 2023
Viewed by 1586
Abstract
Developing a human bionic manipulator to achieve certain humanoid behavioral skills is a rising problem. Enabling robots to operate the steering wheel to drive the vehicle is a challenging task. To address the problem, this work designs a novel 7-DOF (degree of freedom) [...] Read more.
Developing a human bionic manipulator to achieve certain humanoid behavioral skills is a rising problem. Enabling robots to operate the steering wheel to drive the vehicle is a challenging task. To address the problem, this work designs a novel 7-DOF (degree of freedom) humanoid manipulator based on the arm structure of human bionics. The 3-2-2 structural arrangement of the motors and the structural modifications at the wrist allow the manipulator to act more similar to a man. Meanwhile, to manipulate the steering wheel stably and compliantly, an admittance control approach is firstly applied for this case. Considering that the system parameters vary in configuration, we further introduce parameter fuzzification for admittance control. Designed simulations were carried out in Coppeliasim to verify the proposed control approach. As the result shows, the improved method could realize compliant force control under extreme configurations. It demonstrates that the humanoid manipulator can twist the steering wheel stably even in extreme configurations. It is the first exploration to operate a steering wheel similar to a human with a manipulator by using admittance control. Full article
(This article belongs to the Special Issue Biorobotics: 2nd Edition)
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13 pages, 4223 KiB  
Article
A Bio-Inspired Arched Foot with Individual Toe Joints and Plantar Fascia
by Stuart Burgess, Alex Beeston, Joshua Carr, Kallia Siempou, Maya Simmonds and Yasmin Zanker
Biomimetics 2023, 8(6), 455; https://doi.org/10.3390/biomimetics8060455 - 26 Sep 2023
Cited by 2 | Viewed by 2427
Abstract
This paper presents the design and testing of an arched foot with several biomimetic features, including five individual MTP (toe) joints, four individual midfoot joints, and plantar fascia. The creation of a triple-arched foot represents a step further in bio-inspired design compared to [...] Read more.
This paper presents the design and testing of an arched foot with several biomimetic features, including five individual MTP (toe) joints, four individual midfoot joints, and plantar fascia. The creation of a triple-arched foot represents a step further in bio-inspired design compared to other published designs. The arched structure creates flexibility that is similar to human feet with a vertical deflection of up to 12 mm. The individual toe joints enable abduction–adduction in the forefoot and therefore a natural pronation motion. Adult female bone data was obtained and converted into a CAD model to accurately identify the location of bones, joints, and arches. An analytical model is presented that gives the relationship between the vertical stiffness and horizontal stiffness of the longitudinal arches and therefore allows the optimization of stiffness elements. Experimental tests have demonstrated a vertical arch stiffness of 76 N/mm which is similar to adult human feet. The range of movement of the foot is similar to human feet with the following values: dorsi-plantarflexion (28°/37°), inversion-eversion (30°/15°), and abduction–adduction (30°/39°). Tests have also demonstrated a three-point contact with the ground that is similar to human feet. Full article
(This article belongs to the Special Issue Biorobotics: 2nd Edition)
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14 pages, 9838 KiB  
Article
A Fluid-Driven Loop-Type Modular Soft Robot with Integrated Locomotion and Manipulation Capability
by Xin Sui, Mingzhu Lai, Jian Qi, Zhiyuan Yang, Ning Zhao, Jie Zhao, Hegao Cai and Yanhe Zhu
Biomimetics 2023, 8(5), 390; https://doi.org/10.3390/biomimetics8050390 - 26 Aug 2023
Viewed by 1448
Abstract
In nature, some animals, such as snakes and octopuses, use their limited body structure to conduct various complicated tasks not only for locomotion but also for hunting. Their body segments seem to possess the intelligence to adapt to environments and tasks. Inspired by [...] Read more.
In nature, some animals, such as snakes and octopuses, use their limited body structure to conduct various complicated tasks not only for locomotion but also for hunting. Their body segments seem to possess the intelligence to adapt to environments and tasks. Inspired by nature, a modular soft robot with integrated locomotion and manipulation abilities is presented in this paper. A soft modular robot is assembled using several homogeneous cubic pneumatic soft actuator units made of silicone rubber. Both a mathematical model and backpropagation neural network are established to describe the nonlinear deformation of the soft actuator unit. The locomotion process of the chain-type soft robot is analyzed to provide a general rhythmic control principle for modular soft robots. A vision sensor is adopted to control the locomotion and manipulation processes of the modular soft robot in a closed loop. The experimental results indicate that the modular soft robot put forward in this paper has both locomotion and manipulation abilities. Full article
(This article belongs to the Special Issue Biorobotics: 2nd Edition)
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Review

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34 pages, 1910 KiB  
Review
A Review and Evaluation of Control Architectures for Modular Legged and Climbing Robots
by Carlos Prados, Miguel Hernando, Ernesto Gambao and Alberto Brunete
Biomimetics 2024, 9(6), 319; https://doi.org/10.3390/biomimetics9060319 - 27 May 2024
Viewed by 865
Abstract
Robotic control is a fundamental part of autonomous robots. Modular legged and climbing robots are complex machines made up of a variety of subsystems, ranging from a single robot with simple legs to a complex system composed of multiple legs (or modules) with [...] Read more.
Robotic control is a fundamental part of autonomous robots. Modular legged and climbing robots are complex machines made up of a variety of subsystems, ranging from a single robot with simple legs to a complex system composed of multiple legs (or modules) with computing power and sensitivity. Their complexity, which is increased by the fact of needing elements for climbing, makes a correct structure crucial to achieve a complete, robust, and versatile system during its operation. Control architectures for legged robots are distinguished from other software architectures because of the special needs of these systems. In this paper, we present an original classification of modular legged and climbing robots, a comprehensive review of the most important control architectures in robotics, focusing on the control of modular legged and climbing robots, and a comparison of their features. The control architecture comparison aims to provide the analytical tools necessary to make informed decisions tailored to the specific needs of your robotic applications. This article includes a review and classification of modular legged and climbing robots, breaking down each category separately. Full article
(This article belongs to the Special Issue Biorobotics: 2nd Edition)
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