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Machines
Special Issues
Biorobotic Locomotion and Cybernetic Control
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Biorobotic Locomotion and Cybernetic Control

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Advanced Manufacturing".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 3631

Special Issue Editor

Dr. Edgar Martínez-García

E-Mail Website
Guest Editor
Institute of Engineering and Technology, Universidad Autónoma de Cd. Juarez, Juárez, Mexico
Interests: mobile robotics; robot control; biorobotics; motion planning; dynamics modeling; sensor fusion; synthetic intelligence

Special Issue Information

Dear Colleagues,

Biorobots are real-time intelligent machines and important scientific resources for investigating biological locomotion and efficient control models. The engineering design and research on bioinspired mechanisms, robot biomimetics, cybernetic sensorimotor behaviors and multibody systems dynamics for bioinspired locomotion significantly reduce the gaps between mobile robotic machines and biological entities. There is an overlap between biorobotics and cybernetic control, where theoretical control with engineering and biological sciences are combined to intelligently develop complex and agile locomotive tasks. Cybernetic control occurs in numerous aspects of nature, providing the principles of organization in complex systems, so that they behave like biological entities. Biorobots are governed by a looped system regulating itself through feedback communicating sensorimotor information to produce controlled efficient locomotion.

This Special Issue covers aspects of cybernetic control for coordinating biorobots. Feedback information is critical for exerting locomotive behaviors to adapt, change and perform dynamic motion-facing unpredictable scenarios and autonomously generate motion. This SI welcomes, but is not limited to, contributions from the following topics: Hybrid and multimodal locomotion of crawling, walking, swimming and flying robotics; the analysis and modeling of aerodynamics, hydrodynamics and terradynamics for biorobotic motion planning;  structures modeling and biomechanics of robot fish, amphibious robots, ornithopters, multilegged and crawling machines; and locomotive functions, such as neuro cybernetic behavioral skills, robotic artificial life, neural sensorimotor tasks, synthetic intelligence, evolutionary robotics and  control engineering.

Dr. Edgar Martínez-García
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. Machines 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 2400 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-robotics
  • cybernetics
  • locomotion
  • dynamics modeling
  • motion control
  • robot-fish modeling
  • walking-crawling robots
  • ornithopters modeling
  • musculoskeletal control
  • softrobotics
  • insect-like robots

Published Papers (3 papers)

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Research

19 pages, 30994 KiB  
Article
Combined Soft Grasping and Crawling Locomotor Robot for Exterior Navigation of Tubular Structures
by Nicolás Mendoza and Mahdi Haghshenas-Jaryani
Machines 2024, 12(3), 157; https://0-doi-org.brum.beds.ac.uk/10.3390/machines12030157 - 24 Feb 2024
Viewed by 898
Abstract
This paper presents the design, development, and testing of a robot that combines soft-body grasping and crawling locomotion to navigate tubular objects. Inspired by the natural snakes’ climbing locomotion of tubular objects, the soft robot includes proximal and distal modules with radial expansion/contraction [...] Read more.
This paper presents the design, development, and testing of a robot that combines soft-body grasping and crawling locomotion to navigate tubular objects. Inspired by the natural snakes’ climbing locomotion of tubular objects, the soft robot includes proximal and distal modules with radial expansion/contraction for grasping around the objects and a longitudinal contractile–expandable driving module in-between for providing a bi-directional crawling movement along the length of the object. The robot’s grasping modules are made of fabrics, and the crawling module is made of an extensible pneumatic soft actuator (ePSA). Conceptual designs and CAD models of the robot parts, textile-based inflatable structures, and pneumatic driving mechanisms were developed. The mechanical parts were fabricated using advanced and conventional manufacturing techniques. An Arduino-based electro-pneumatic control board was developed for generating cyclic patterns of grasping and locomotion. Different reinforcing patterns and materials characterize the locomotor actuators’ dynamical responses to the varying input pressures. The robot was tested in a laboratory setting to navigate a cable, and the collected data were used to modify the designs and control software and hardware. The capability of the soft robot for navigating cables in vertical, horizontal, and curved path scenarios was successfully demonstrated. Compared to the initial design, the forward speed is improved three-fold. Full article
(This article belongs to the Special Issue Biorobotic Locomotion and Cybernetic Control)
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41 pages, 3430 KiB  
Article
Electromyography-Based Biomechanical Cybernetic Control of a Robotic Fish Avatar
by Manuel A. Montoya Martínez, Rafael Torres-Córdoba, Evgeni Magid and Edgar A. Martínez-García
Machines 2024, 12(2), 124; https://0-doi-org.brum.beds.ac.uk/10.3390/machines12020124 - 09 Feb 2024
Viewed by 1018
Abstract
This study introduces a cybernetic control and architectural framework for a robotic fish avatar operated by a human. The behavior of the robot fish is influenced by the electromyographic (EMG) signals of the human operator, triggered by stimuli from the surrounding objects and [...] Read more.
This study introduces a cybernetic control and architectural framework for a robotic fish avatar operated by a human. The behavior of the robot fish is influenced by the electromyographic (EMG) signals of the human operator, triggered by stimuli from the surrounding objects and scenery. A deep artificial neural network (ANN) with perceptrons classifies the EMG signals, discerning the type of muscular stimuli generated. The research unveils a fuzzy-based oscillation pattern generator (OPG) designed to emulate functions akin to a neural central pattern generator, producing coordinated fish undulations. The OPG generates swimming behavior as an oscillation function, decoupled into coordinated step signals, right and left, for a dual electromagnetic oscillator in the fish propulsion system. Furthermore, the research presents an underactuated biorobotic mechanism of the subcarangiform type comprising a two-solenoid electromagnetic oscillator, an antagonistic musculoskeletal elastic system of tendons, and a multi-link caudal spine composed of helical springs. The biomechanics dynamic model and control for swimming, as well as the ballasting system for submersion and buoyancy, are deduced. This study highlights the utilization of EMG measurements encompassing sampling time and μ-volt signals for both hands and all fingers. The subsequent feature extraction resulted in three types of statistical patterns, namely, Ω,γ,λ, serving as inputs for a multilayer feedforward neural network of perceptrons. The experimental findings quantified controlled movements, specifically caudal fin undulations during forward, right, and left turns, with a particular emphasis on the dynamics of caudal fin undulations of a robot prototype. Full article
(This article belongs to the Special Issue Biorobotic Locomotion and Cybernetic Control)
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30 pages, 26046 KiB  
Article
Neuro-Cognitive Locomotion with Dynamic Attention on Topological Structure
by Azhar Aulia Saputra, János Botzheim and Naoyuki Kubota
Machines 2023, 11(6), 619; https://0-doi-org.brum.beds.ac.uk/10.3390/machines11060619 - 03 Jun 2023
Viewed by 971
Abstract
This paper discusses a mechanism for integrating locomotion with cognition in robots. We demonstrate an attentional ability model that can dynamically change the focus of its perceptual area by integrating attention and perception to generate behavior. The proposed model considers both internal sensory [...] Read more.
This paper discusses a mechanism for integrating locomotion with cognition in robots. We demonstrate an attentional ability model that can dynamically change the focus of its perceptual area by integrating attention and perception to generate behavior. The proposed model considers both internal sensory information and also external sensory information. We also propose affordance detection that identifies different actions depending on the robot’s immediate possibilities. Attention is represented in a topological structure generated by a growing neural gas that uses 3D point-cloud data. When the robot faces an obstacle, the topological map density increases in the suspected obstacle area. From here, affordance information is processed directly into the behavior pattern generator, which comprises interconnections between motor and internal sensory neurons. The attention model increases the density associated with the suspected obstacle to produce a detailed representation of the obstacle. Then, the robot processes the cognitive information to enact a short-term adaptation to its locomotion by changing its swing pattern or movement plan. To test the effectiveness of the proposed model, it is implemented in a computer simulation and also in a medium-sized, four-legged robot. The experiments validate the advantages in three categories: (1) Development of attention model using topological structure, (2) Integration between attention and affordance in moving behavior, (3) Integration of exteroceptive sensory information to lower-level control of locomotion generator. Full article
(This article belongs to the Special Issue Biorobotic Locomotion and Cybernetic Control)
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