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Machines
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Intelligent Mechatronics Systems
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Intelligent Mechatronics Systems

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Robotics, Mechatronics and Intelligent Machines".

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 19436

Special Issue Editor

Prof. Dr. Antonios Gasteratos

E-Mail Website
Guest Editor
Department of Production and Management Engineering, Democritus University of Thrace, Vas. Sofias 12, GR-67100 Xanthi, Greece
Interests: robotics; computer vision; mechatronics; navigation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In contemporary mechatronics systems, the complexity of the mechanical and electronics parts imposes intelligence embedded to the system. The advancement in mechatronics design urges for sophisticated control laws as well as advanced feedback from smart sensors. Recent developments in artificial intelligence and machine vision allow the use of advanced algorithms into a variety of applications in order solve problems that arise when implementing sophisticated mechatronics systems. This Special Issue will accept contributions where the concepts of mechatronics, machine vision, and artificial intelligence intersect and coexist in a congruous manner. The overall objective of the Special Issue is to render the sine qua non role of artificial intelligence and machine vision in modern mechatronics systems.

The topics the Special Issue will cover include applications of artificial intelligence and machine vision to any of, but not limited to, the following areas:

  • Intelligent robotic systems (including surface, underwater and flying platforms);
  • Instrumentation and measurement;
  • Advanced manufacturing systems;
  • Industrial automation;
  • Automotive and transportation systems;
  • Sophisticated construction systems;
  • Surveillance and security systems;
  • Power systems;
  • Quality control;
  • ICT and robotics in agriculture;
  • Healthcare/medical automated systems;
  • Space exploration.

Prof. Antonios Gasteratos
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.

Published Papers (5 papers)

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Research

7 pages, 1285 KiB  
Communication
A Product Pose Tracking Paradigm Based on Deep Points Detection
by Loukas Bampis, Spyridon G. Mouroutsos and Antonios Gasteratos
Machines 2021, 9(6), 112; https://0-doi-org.brum.beds.ac.uk/10.3390/machines9060112 - 28 May 2021
Cited by 2 | Viewed by 2322
Abstract
The paper at hand presents a novel and versatile method for tracking the pose of varying products during their manufacturing procedure. By using modern Deep Neural Network techniques based on Attention models, the most representative points to track an object can be automatically [...] Read more.
The paper at hand presents a novel and versatile method for tracking the pose of varying products during their manufacturing procedure. By using modern Deep Neural Network techniques based on Attention models, the most representative points to track an object can be automatically identified using its drawing. Then, during manufacturing, the body of the product is processed with Aluminum Oxide on those points, which is unobtrusive in the visible spectrum, but easily distinguishable from infrared cameras. Our proposal allows for the inclusion of Artificial Intelligence in Computer-Aided Manufacturing to assist the autonomous control of robotic handlers. Full article
(This article belongs to the Special Issue Intelligent Mechatronics Systems)
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23 pages, 5649 KiB  
Article
A Synergy of Innovative Technologies towards Implementing an Autonomous DIY Electric Vehicle for Harvester-Assisting Purposes
by Dimitrios Loukatos, Evangelos Petrongonas, Kostas Manes, Ioannis-Vasileios Kyrtopoulos, Vasileios Dimou and Konstantinos G. Arvanitis
Machines 2021, 9(4), 82; https://0-doi-org.brum.beds.ac.uk/10.3390/machines9040082 - 19 Apr 2021
Cited by 16 | Viewed by 3555
Abstract
The boom in the electronics industry has made a variety of credit card-sized computer systems and plenty of accompanying sensing and acting elements widely available, at continuously diminishing cost and size levels. The benefits of this situation for agriculture are not left unexploited [...] Read more.
The boom in the electronics industry has made a variety of credit card-sized computer systems and plenty of accompanying sensing and acting elements widely available, at continuously diminishing cost and size levels. The benefits of this situation for agriculture are not left unexploited and thus, more accurate, efficient and environmentally-friendly systems are making the scene. In this context, there is an increasing interest in affordable, small-scale agricultural robots. A key factor for success is the balanced selection of innovative hardware and software components, among the plethora being available. This work describes exactly the steps for designing, implementing and testing a small autonomous electric vehicle, able to follow the farmer during the harvesting activities and to carry the fruits/vegetables from the plant area to the truck location. Quite inexpensive GPS and IMU units, assisted by hardware-accelerated machine vision, speech recognition and networking techniques can assure the fluent operation of a prototype vehicle exhibiting elementary automatic control functionality. The whole approach also highlights the challenges for achieving a truly working solution and provides directions for future exploitation and improvements. Full article
(This article belongs to the Special Issue Intelligent Mechatronics Systems)
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22 pages, 15912 KiB  
Article
Model-Based Manipulation of Linear Flexible Objects: Task Automation in Simulation and Real World
by Peng Chang and Taşkın Padır
Machines 2020, 8(3), 46; https://0-doi-org.brum.beds.ac.uk/10.3390/machines8030046 - 08 Aug 2020
Cited by 16 | Viewed by 5126
Abstract
Manipulation of deformable objects is a desired skill in making robots ubiquitous in manufacturing, service, healthcare, and security. Common deformable objects (e.g., wires, clothes, bed sheets, etc.) are significantly more difficult to model than rigid objects. In this research, we contribute to the [...] Read more.
Manipulation of deformable objects is a desired skill in making robots ubiquitous in manufacturing, service, healthcare, and security. Common deformable objects (e.g., wires, clothes, bed sheets, etc.) are significantly more difficult to model than rigid objects. In this research, we contribute to the model-based manipulation of linear flexible objects such as cables. We propose a 3D geometric model of the linear flexible object that is subject to gravity and a physical model with multiple links connected by revolute joints and identified model parameters. These models enable task automation in manipulating linear flexible objects both in simulation and real world. To bridge the gap between simulation and real world and build a close-to-reality simulation of flexible objects, we propose a new strategy called Simulation-to-Real-to-Simulation (Sim2Real2Sim). We demonstrate the feasibility of our approach by completing the Plug Task used in the 2015 DARPA Robotics Challenge Finals both in simulation and real world, which involves unplugging a power cable from one socket and plugging it into another. Numerical experiments are implemented to validate our approach. Full article
(This article belongs to the Special Issue Intelligent Mechatronics Systems)
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25 pages, 8102 KiB  
Article
A Novel Adaptive and Nonlinear Electrohydraulic Active Suspension Control System with Zero Dynamic Tire Liftoff
by Amhmed Mohamed Al Aela, Jean-Pierre Kenne and Honorine Angue Mintsa
Machines 2020, 8(3), 38; https://0-doi-org.brum.beds.ac.uk/10.3390/machines8030038 - 11 Jul 2020
Cited by 10 | Viewed by 3319
Abstract
In this paper, a novel adaptive control system (NAC) is proposed for a restricted quarter-car electrohydraulic active suspension system. The main contribution of this NAC is its explicit tackling of the trade-off between passenger comfort/road holding and passenger comfort/suspension travel. Reducing suspension travel [...] Read more.
In this paper, a novel adaptive control system (NAC) is proposed for a restricted quarter-car electrohydraulic active suspension system. The main contribution of this NAC is its explicit tackling of the trade-off between passenger comfort/road holding and passenger comfort/suspension travel. Reducing suspension travel oscillations is another control target that was considered. Many researchers have developed control laws for constrained active suspension systems. However, most of the studies in the works of the latter have not directly examined the compromise between road holding, suspension travel, and passenger comfort. In this study, we proposed a novel adaptive control system to explicitly address the trade-off between passenger comfort and road holding, as well as the compromise between passenger comfort and suspension travel limits. The novelty of our control technique lies in its introduction of a modeling system for a dynamic landing tire system aimed at avoiding a dynamic tire liftoff. The proposed control consists of an adaptive neural networks’ backstepping control, coupled with a nonlinear control filter system aimed at tracking the output position of the nonlinear filter. The tracking control position is the difference between the sprung mass position and the output nonlinear filter signal. The results indicate that the novel adaptive control (NAC) can achieve the handling of car–road stability, ride comfort, and safe suspension travel compared to that of the other studies, demonstrating the controller’s effectiveness. Full article
(This article belongs to the Special Issue Intelligent Mechatronics Systems)
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25 pages, 5282 KiB  
Article
A Self-triggered Position Based Visual Servoing Model Predictive Control Scheme for Underwater Robotic Vehicles
by Shahab Heshmati-alamdari, Alina Eqtami, George C. Karras, Dimos V. Dimarogonas and Kostas J. Kyriakopoulos
Machines 2020, 8(2), 33; https://0-doi-org.brum.beds.ac.uk/10.3390/machines8020033 - 11 Jun 2020
Cited by 26 | Viewed by 3310
Abstract
An efficient position based visual sevroing control approach for Autonomous Underwater Vehicles (AUVs) by employing Non-linear Model Predictive Control (N-MPC) is designed and presented in this work. In the proposed scheme, a mechanism is incorporated within the vision-based controller that determines when the [...] Read more.
An efficient position based visual sevroing control approach for Autonomous Underwater Vehicles (AUVs) by employing Non-linear Model Predictive Control (N-MPC) is designed and presented in this work. In the proposed scheme, a mechanism is incorporated within the vision-based controller that determines when the Visual Tracking Algorithm (VTA) should be activated and new control inputs should be calculated. More specifically, the control loop does not close periodically, i.e., between two consecutive activations (triggering instants), the control inputs calculated by the N-MPC at the previous triggering time instant are applied to the underwater robot in an open-loop mode. This results in a significantly smaller number of requested measurements from the vision tracking algorithm, as well as less frequent computations of the non-linear predictive control law. This results in a reduction in processing time as well as energy consumption and, therefore, increases the accuracy and autonomy of the Autonomous Underwater Vehicle. The latter is of paramount importance for persistent underwater inspection tasks. Moreover, the Field of View constraints (FoV), control input saturation, the kinematic limitations due to the underactuated degree of freedom in sway direction, and the effect of the model uncertainties as well as external disturbances have been considered during the control design. In addition, the stability and convergence of the closed-loop system has been guaranteed analytically. Finally, the efficiency and performance of the proposed vision-based control framework is demonstrated through a comparative real-time experimental study while using a small underwater vehicle. Full article
(This article belongs to the Special Issue Intelligent Mechatronics Systems)
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