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Biomimetics
Special Issues
Bio-Inspired and Biomimetic Intelligence in Robotics
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Bio-Inspired and Biomimetic Intelligence in Robotics

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 March 2024) | Viewed by 6113

Special Issue Editors

Dr. Pengcheng Liu

E-Mail Website
Guest Editor
Department of Computer Science, University of York, Heslington YO10 5GH, UK
Interests: robot learning; applied control; bioinspiration and biomimetics
Dr. Qinbing Fu

E-Mail Website
Guest Editor
Machine Life and Intelligence Research Centre, Guangzhou University, Guangzhou, China
Interests: brain-inspired intelligence; motion perception; machine vision; computational neuroscience
Dr. Tiong Hoo Lim

E-Mail Website
Guest Editor
Faculty of Engineering, Universiti Teknologi Brunei, Mukim Gadong A, Bandar Seri Begawan BE1410, Brunei
Interests: artificial intelligence; autonomous systems; embedded technologies

Special Issue Information

Dear Colleagues,

Robotics is a multidisciplinary research field that demonstrates enormous potential. It concerns developing intelligent robotic systems that are capable of making decisions and acting autonomously in real and dynamic environments to accomplish tasks and assist humans in relevant application domains for society. Recently, advances in the computational study of intelligent behaviors such as learning and adaptation have led to powerful insights about the nature of learning in both humans, animals, materials, and machines. However, new and challenging theoretical and technological problems are being posed. One can apply the computational metaphor in different ways, and computational learning has become an important topic within many paradigms, including artificial intelligence, pattern recognition, control theory, cognitive intelligence, behavioral intelligence, and statistics. Such a convergence of interests is encouraging, but few researchers in this active area communicate across disciplinary boundaries, and even fewer are skilled in the ‘language’ and techniques of more than one approach. With this new era of computational learning for robotics, much research is needed in order to continue to advance the field and also to evaluate the multidisciplinary concerns of the existence of learning and adaptation techniques.

The aim of this Special Issue is to highlight the roles of advanced bio-inspired and biomimetic intelligence for robotics applications and prior knowledge in achieving successes and, especially, how they contribute to the taming of the complexity of the linked domains. It includes but is not limited to the following topics:

  • Behavioral and biological learning and control;
  • Computational neuroscience;
  • Cognitive robotics and computation;
  • Evolutionary robotics, multi-robot systems, and swarm intelligence;
  • Computational modeling of biological systems;
  • Biomechanics, biomechatronics, and bioengineering;
  • Smart materials;
  • Soft robotics and sensing;
  • Human‒robot interaction and collaboration;
  • Bio-inspired approaches for robot design, control, and optimization;
  • Morphological computation and embodied intelligence;
  • Bio-inspired spiking neural networks;
  • Bio-inspired vision systems;
  • Imitation learning, Bayesian/probabilistic learning;
  • Bio-inspired legged robotics;
  • Bio-inspired/biomimetic underwater robotics;
  • Micro- and Nano-robotics;
  • Healthcare and rehabilitation;
  • Flexible electronics and piezoelectret actuators. 

Dr. Pengcheng Liu
Dr. Qinbing Fu
Dr. Tiong Hoo Lim
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. 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

  • biological inspiration
  • biomimetics
  • computational learning
  • robotics

Published Papers (6 papers)

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Research

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16 pages, 5249 KiB  
Article
How to Easily Make Self-Sensing Pneumatic Inverse Artificial Muscles
by Valentina Potnik, Gabriele Frediani and Federico Carpi
Biomimetics 2024, 9(3), 177; https://0-doi-org.brum.beds.ac.uk/10.3390/biomimetics9030177 - 15 Mar 2024
Cited by 1 | Viewed by 932
Abstract
Wearable mechatronics for powered orthoses, exoskeletons and prostheses require improved soft actuation systems acting as ‘artificial muscles’ that are capable of large strains, high stresses, fast response and self-sensing and that show electrically safe operation, low specific weight and large compliance. Among the [...] Read more.
Wearable mechatronics for powered orthoses, exoskeletons and prostheses require improved soft actuation systems acting as ‘artificial muscles’ that are capable of large strains, high stresses, fast response and self-sensing and that show electrically safe operation, low specific weight and large compliance. Among the diversity of soft actuation technologies under investigation, pneumatic devices have been the focus, during the last couple of decades, of renewed interest as an intrinsically soft artificial muscle technology, due to technological advances stimulated by applications in soft robotics. As of today, quite a few solutions are available to endow a pneumatic soft device with linear actuation and self-sensing ability, while also easily achieving these features with off-the-shelf materials and low-cost fabrication processes. Here, we describe a simple process to make self-sensing pneumatic actuators, which may be used as ‘inverse artificial muscles’, as, upon pressurisation, they elongate instead of contracting. They are made of an elastomeric tube surrounded by a plastic coil, which constrains radial expansions. As a novelty relative to the state of the art, the self-sensing ability was obtained with a piezoresistive stretch sensor shaped as a conductive elastomeric body along the tube’s central axis. Moreover, we detail, also by means of video clips, a step-by-step manufacturing process, which uses off-the-shelf materials and simple procedures, so as to facilitate reproducibility. Full article
(This article belongs to the Special Issue Bio-Inspired and Biomimetic Intelligence in Robotics)
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12 pages, 788 KiB  
Article
Bio-Inspired Neural Network for Real-Time Evasion of Multi-Robot Systems in Dynamic Environments
by Junfei Li and Simon X. Yang
Biomimetics 2024, 9(3), 176; https://0-doi-org.brum.beds.ac.uk/10.3390/biomimetics9030176 - 15 Mar 2024
Viewed by 868
Abstract
In complex and dynamic environments, traditional pursuit–evasion studies may face challenges in offering effective solutions to sudden environmental changes. In this paper, a bio-inspired neural network (BINN) is proposed that approximates a pursuit–evasion game from a neurodynamic perspective instead of formulating the problem [...] Read more.
In complex and dynamic environments, traditional pursuit–evasion studies may face challenges in offering effective solutions to sudden environmental changes. In this paper, a bio-inspired neural network (BINN) is proposed that approximates a pursuit–evasion game from a neurodynamic perspective instead of formulating the problem as a differential game. The BINN is topologically organized to represent the environment with only local connections. The dynamics of neural activity, characterized by the neurodynamic shunting model, enable the generation of real-time evasive trajectories with moving or sudden-change obstacles. Several simulation and experimental results indicate that the proposed approach is effective and efficient in complex and dynamic environments. Full article
(This article belongs to the Special Issue Bio-Inspired and Biomimetic Intelligence in Robotics)
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35 pages, 5234 KiB  
Article
Simulated Dopamine Modulation of a Neurorobotic Model of the Basal Ganglia
by Tony J. Prescott, Fernando M. Montes González, Kevin Gurney, Mark D. Humphries and Peter Redgrave
Biomimetics 2024, 9(3), 139; https://0-doi-org.brum.beds.ac.uk/10.3390/biomimetics9030139 - 25 Feb 2024
Viewed by 942
Abstract
The vertebrate basal ganglia play an important role in action selection—the resolution of conflicts between alternative motor programs. The effective operation of basal ganglia circuitry is also known to rely on appropriate levels of the neurotransmitter dopamine. We investigated reducing or increasing the [...] Read more.
The vertebrate basal ganglia play an important role in action selection—the resolution of conflicts between alternative motor programs. The effective operation of basal ganglia circuitry is also known to rely on appropriate levels of the neurotransmitter dopamine. We investigated reducing or increasing the tonic level of simulated dopamine in a prior model of the basal ganglia integrated into a robot control architecture engaged in a foraging task inspired by animal behaviour. The main findings were that progressive reductions in the levels of simulated dopamine caused slowed behaviour and, at low levels, an inability to initiate movement. These states were partially relieved by increased salience levels (stronger sensory/motivational input). Conversely, increased simulated dopamine caused distortion of the robot’s motor acts through partially expressed motor activity relating to losing actions. This could also lead to an increased frequency of behaviour switching. Levels of simulated dopamine that were either significantly lower or higher than baseline could cause a loss of behavioural integration, sometimes leaving the robot in a ‘behavioral trap’. That some analogous traits are observed in animals and humans affected by dopamine dysregulation suggests that robotic models could prove useful in understanding the role of dopamine neurotransmission in basal ganglia function and dysfunction. Full article
(This article belongs to the Special Issue Bio-Inspired and Biomimetic Intelligence in Robotics)
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26 pages, 8866 KiB  
Article
Research on Teleoperated Virtual Reality Human–Robot Five-Dimensional Collaboration System
by Qinglei Zhang, Qinghao Liu, Jianguo Duan and Jiyun Qin
Biomimetics 2023, 8(8), 605; https://0-doi-org.brum.beds.ac.uk/10.3390/biomimetics8080605 - 13 Dec 2023
Cited by 1 | Viewed by 1168
Abstract
In the realm of industrial robotics, there is a growing challenge in simplifying human–robot collaboration (HRC), particularly in complex settings. The demand for more intuitive teleoperation systems is on the rise. However, optimizing robot control interfaces and streamlining teleoperation remains a formidable task [...] Read more.
In the realm of industrial robotics, there is a growing challenge in simplifying human–robot collaboration (HRC), particularly in complex settings. The demand for more intuitive teleoperation systems is on the rise. However, optimizing robot control interfaces and streamlining teleoperation remains a formidable task due to the need for operators to possess specialized knowledge and the limitations of traditional methods regarding operational space and time constraints. This study addresses these issues by introducing a virtual reality (VR) HRC system with five-dimensional capabilities. Key advantages of our approach include: (1) real-time observation of robot work, whereby operators can seamlessly monitor the robot’s real-time work environment and motion during teleoperation; (2) leveraging VR device capabilities, whereby the strengths of VR devices are harnessed to simplify robot motion control, significantly reducing the learning time for operators; and (3) adaptability across platforms and environments: our system effortlessly adapts to various platforms and working conditions, ensuring versatility across different terminals and scenarios. This system represents a significant advancement in addressing the challenges of HRC, offering improved teleoperation, simplified control, and enhanced accessibility, particularly for operators with limited prior exposure to robot operation. It elevates the overall HRC experience in complex scenarios. Full article
(This article belongs to the Special Issue Bio-Inspired and Biomimetic Intelligence in Robotics)
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33 pages, 25173 KiB  
Article
Contributions to the Dynamic Regime Behavior of a Bionic Leg Prosthesis
by Marius-Valentin Drăgoi, Anton Hadăr, Nicolae Goga, Florin Baciu, Amado Ștefan, Lucian Ștefăniță Grigore, Damian Gorgoteanu, Cristian Molder and Ionica Oncioiu
Biomimetics 2023, 8(5), 414; https://0-doi-org.brum.beds.ac.uk/10.3390/biomimetics8050414 - 06 Sep 2023
Viewed by 1178
Abstract
The purpose of prosthetic devices is to reproduce the angular-torque profile of a healthy human during locomotion. A lightweight and energy-efficient joint is capable of decreasing the peak actuator power and/or power consumption per gait cycle, while adequately meeting profile-matching constraints. The aim [...] Read more.
The purpose of prosthetic devices is to reproduce the angular-torque profile of a healthy human during locomotion. A lightweight and energy-efficient joint is capable of decreasing the peak actuator power and/or power consumption per gait cycle, while adequately meeting profile-matching constraints. The aim of this study was to highlight the dynamic characteristics of a bionic leg with electric actuators with rotational movement. Three-dimensional (3D)-printing technology was used to create the leg, and servomotors were used for the joints. A stepper motor was used for horizontal movement. For better numerical simulation of the printed model, three mechanical tests were carried out (tension, compression, and bending), based on which the main mechanical characteristics necessary for the numerical simulation were obtained. For the experimental model made, the dynamic stresses could be determined, which highlights the fact that, under the conditions given for the experimental model, the prosthesis resists. Full article
(This article belongs to the Special Issue Bio-Inspired and Biomimetic Intelligence in Robotics)
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Review

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17 pages, 2830 KiB  
Review
Exploring Embodied Intelligence in Soft Robotics: A Review
by Zikai Zhao, Qiuxuan Wu, Jian Wang, Botao Zhang, Chaoliang Zhong and Anton A. Zhilenkov
Biomimetics 2024, 9(4), 248; https://0-doi-org.brum.beds.ac.uk/10.3390/biomimetics9040248 - 19 Apr 2024
Viewed by 257
Abstract
Soft robotics is closely related to embodied intelligence in the joint exploration of the means to achieve more natural and effective robotic behaviors via physical forms and intelligent interactions. Embodied intelligence emphasizes that intelligence is affected by the synergy of the brain, body, [...] Read more.
Soft robotics is closely related to embodied intelligence in the joint exploration of the means to achieve more natural and effective robotic behaviors via physical forms and intelligent interactions. Embodied intelligence emphasizes that intelligence is affected by the synergy of the brain, body, and environment, focusing on the interaction between agents and the environment. Under this framework, the design and control strategies of soft robotics depend on their physical forms and material properties, as well as algorithms and data processing, which enable them to interact with the environment in a natural and adaptable manner. At present, embodied intelligence has comprehensively integrated related research results on the evolution, learning, perception, decision making in the field of intelligent algorithms, as well as on the behaviors and controls in the field of robotics. From this perspective, the relevant branches of the embodied intelligence in the context of soft robotics were studied, covering the computation of embodied morphology; the evolution of embodied AI; and the perception, control, and decision making of soft robotics. Moreover, on this basis, important research progress was summarized, and related scientific problems were discussed. This study can provide a reference for the research of embodied intelligence in the context of soft robotics. Full article
(This article belongs to the Special Issue Bio-Inspired and Biomimetic Intelligence in Robotics)
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