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22 pages, 18310 KiB

Open AccessArticle

Advancing the Robotic Vision Revolution: Development and Evaluation of a Bionic Binocular System for Enhanced Robotic Vision

by Hongxin Zhang and Suan Lee

Biomimetics 2024, 9(6), 371; https://doi.org/10.3390/biomimetics9060371 - 19 Jun 2024

Cited by 3 | Viewed by 1254

Abstract

This paper describes a novel bionic eye binocular vision system designed to mimic the natural movements of the human eye. The system provides a broader field of view and enhances visual perception in complex environments. Compared with similar bionic binocular cameras, the JEWXON [...] Read more.

This paper describes a novel bionic eye binocular vision system designed to mimic the natural movements of the human eye. The system provides a broader field of view and enhances visual perception in complex environments. Compared with similar bionic binocular cameras, the JEWXON BC200 bionic binocular camera developed in this study is more miniature. It consumes only 2.8 W of power, which makes it ideal for mobile robots. Combining axis and camera rotation enables more seamless panoramic image synthesis and is therefore suitable for self-rotating bionic binocular cameras. In addition, combined with the YOLO-V8 model, the camera can accurately recognize objects such as clocks and keyboards. This research provides new ideas for the development of robotic vision systems. Full article

(This article belongs to the Special Issue Bio-Inspired and Biomimetic Intelligence in Robotics)

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26 pages, 6668 KiB

Open AccessArticle

Innate Orientating Behavior of a Multi-Legged Robot Driven by the Neural Circuits of C. elegans

by Kangxin Hu, Yu Zhang, Fei Ding, Dun Yang, Yang Yu, Ying Yu, Qingyun Wang and Hexi Baoyin

Biomimetics 2024, 9(6), 314; https://doi.org/10.3390/biomimetics9060314 - 23 May 2024

Viewed by 1411

Abstract

The objective of this research is to achieve biologically autonomous control by utilizing a whole-brain network model, drawing inspiration from biological neural networks to enhance the development of bionic intelligence. Here, we constructed a whole-brain neural network model of Caenorhabditis elegans (C. [...] Read more.

The objective of this research is to achieve biologically autonomous control by utilizing a whole-brain network model, drawing inspiration from biological neural networks to enhance the development of bionic intelligence. Here, we constructed a whole-brain neural network model of Caenorhabditis elegans (C. elegans), which characterizes the electrochemical processes at the level of the cellular synapses. The neural network simulation integrates computational programming and the visualization of the neurons and synapse connections of C. elegans, containing the specific controllable circuits and their dynamic characteristics. To illustrate the biological neural network (BNN)’s particular intelligent control capability, we introduced an innovative methodology for applying the BNN model to a 12-legged robot’s movement control. Two methods were designed, one involving orientation control and the other involving locomotion generation, to demonstrate the intelligent control performance of the BNN. Both the simulation and experimental results indicate that the robot exhibits more autonomy and a more intelligent movement performance under BNN control. The systematic approach of employing the whole-brain BNN for robot control provides biomimetic research with a framework that has been substantiated by innovative methodologies and validated through the observed positive outcomes. This method is established as follows: (1) two integrated dynamic models of the C. elegans’ whole-brain network and the robot moving dynamics are built, and all of the controllable circuits are discovered and verified; (2) real-time communication is achieved between the BNN model and the robot’s dynamical model, both in the simulation and the experiments, including applicable encoding and decoding algorithms, facilitating their collaborative operation; (3) the designed mechanisms using the BNN model to control the robot are shown to be effective through numerical and experimental tests, focusing on ‘foraging’ behavior control and locomotion control. Full article

(This article belongs to the Special Issue Bio-Inspired and Biomimetic Intelligence in Robotics)

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16 pages, 5249 KiB

Open AccessArticle

How to Easily Make Self-Sensing Pneumatic Inverse Artificial Muscles

by Valentina Potnik, Gabriele Frediani and Federico Carpi

Biomimetics 2024, 9(3), 177; https://doi.org/10.3390/biomimetics9030177 - 15 Mar 2024

Cited by 2 | Viewed by 1799

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

Open AccessArticle

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://doi.org/10.3390/biomimetics9030176 - 15 Mar 2024

Cited by 1 | Viewed by 1524

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

Open AccessArticle

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://doi.org/10.3390/biomimetics9030139 - 25 Feb 2024

Cited by 1 | Viewed by 1634

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

Open AccessArticle

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://doi.org/10.3390/biomimetics8080605 - 13 Dec 2023

Cited by 4 | Viewed by 1910

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

Open AccessArticle

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://doi.org/10.3390/biomimetics8050414 - 6 Sep 2023

Cited by 1 | Viewed by 1661

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

Jump to: Research

17 pages, 2830 KiB

Open AccessReview

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://doi.org/10.3390/biomimetics9040248 - 19 Apr 2024

Cited by 1 | Viewed by 3330

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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