Special Issue "Automation Control and Robotics in Human-Machine Cooperation"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".

Deadline for manuscript submissions: 10 June 2022 | Viewed by 2550

Special Issue Editors

Dr. Wojciech Kaczmarek
E-Mail Website
Guest Editor
Faculty of Mechatronics, Armament and Aerospace, Military University of Technology, Kaliskiego 2 Street, 00-908 Warsaw, Poland
Interests: human–robot collaboration; digital tweens; manufacturing simulation; robotics; pick and place processes; production planning and control
Dr. Jarosław Panasiuk
E-Mail Website
Guest Editor
Faculty of Mechatronics, Armament and Aerospace, Military University of Technology, Kaliskiego 2 Street, 00-908 Warsaw, Poland
Interests: human–robot collaboration; digital tweens; manufacturing simulation; robotics; pick and place processes; production planning and control; vision systems; machine learning
Dr. Albert Smalcerz
E-Mail Website
Guest Editor
Department of Industrial Informatics, Silesian University of Technology, Akademicka 2A, 44-100 Gliwice, Poland
Interests: industrial informatics; induction heating; electromagnetic field; numerical simulation; optimization; electromagnetic fields; alloys; electromagnetics; computational electromagnetics; electromagnetic compatibility; electromagnetic engineering
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Special Issue Information

Dear Colleagues,

I would like to interest you in this Special Issue, entitled “Automation Control and Robotics in Human-Machine Cooperation,” in Applied Sciences and cordially invite you to submit your articles. The purpose of this Special Issue is to compile studies on knowledge, research practice, and forecast development trends in the field of automation control, robotics, and human-machine cooperation.

Every day, people use devices and machines that are more or less automated. Thanks to advanced interfaces, we often do not think about the degree of automation. However, we should be aware of the fact that cooperation between humans and machines is developing very fast both in everyday life and on the production floor. Close cooperation between humans and machines is possible thanks to the rapid development of sensor technologies, data processing, and data acquisition systems. On the one hand, we are trying to increase the functionality of everyday devices by automating them; on the other hand, we are trying to find a place for operators working on production lines by reducing their distance to the machines. In both cases, the main goal is to combine human skill and innovation with machine efficiency and precision. This is particularly evident in modern production lines, where the cooperation of operators with robots in a common workspace is becoming an everyday reality. Nowadays, virtual environments for designing and programming robots and machines enable fast and reliable preparation of technological processes. They also allow simulation studies to determine the performance of processes, which corresponds to the idea of digital tweens (full representation of a real process station by a virtual model).  

We welcome the submission of papers on the topics including but not limited to the following:

  • Human–robot collaboration for manufacturing processes
  • Sensing and control in robotics
  • Modelling and simulation in robotics and automation—digital tweens
  • Advanced environment for modelling and controlling robotics applications
  • Robots and Industry 4.0 concepts
  • Industrial robots in research applications
  • Mobile robotic platforms
  • Safety in industrial robot applications
  • Design and development of robots and robot end-effectors
  • Study and analysis of robotic processes
  • Virtual reality and augmented reality
  • Techniques for online, offline robots programming
  • Sensors in control and steering of the system
  • Smart/intelligent sensors

Dr. Wojciech Kaczmarek
Dr. Jarosław Panasiuk
Dr. Albert Smalcerz
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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2300 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

  • automation and control
  • Human-Machine cooperation
  • modelling and simulation of robotic systems
  • digital tweens
  • mobile robots
  • industrial robots
  • collaborative robots (cobots)
  • research robot application
  • Industry 4.0

Published Papers (4 papers)

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Research

Article
Path Tracking of Underground Mining Boom Roadheader Combining BP Neural Network and State Estimation
Appl. Sci. 2022, 12(10), 5165; https://doi.org/10.3390/app12105165 - 20 May 2022
Viewed by 246
Abstract
This paper proposes a path correction scheduling strategy for the underground mining boom roadheader by ably combining a back propagation (BP) neural network and state estimation. First, a pose deviation-based tracking model is designed for the roadheader, and it is then further studied [...] Read more.
This paper proposes a path correction scheduling strategy for the underground mining boom roadheader by ably combining a back propagation (BP) neural network and state estimation. First, a pose deviation-based tracking model is designed for the roadheader, and it is then further studied and optimized by incorporating the benefits of BP neural networks into the model adaptation. Considering the fact that there is skidding between tracks on the ground and errors during the instant pose detection of the roadheader underground, singular value decomposition (SVD)–Unscented Kalman filtering is applied to estimate the real pose deviation, based on the summarized distribution regularities of the track skidding ratios and the pose detection errors, instead of complicated analysis mechanisms. The BP neural network and states estimation are well combined in structure, enabling this scheduling strategy to update the control law and revise the control instruction simultaneously in the procedure. The proposed path tracking model for the roadheader is simple and clear, without adding extra devices or massive algorithms, which is attractive in terms of industrial use. The path tracking simulations show that this proposed strategy achieves path tracking well in different scenarios and is of high adaptability when facing complex trajectory while still giving stable control instructions for the roadheader. Full article
(This article belongs to the Special Issue Automation Control and Robotics in Human-Machine Cooperation)
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Article
Self-Balancing Power Amplifier with a Minimal DC Offset for Launcher Automation Control Circuits of a Surface-to-Air Missile System
Appl. Sci. 2022, 12(7), 3532; https://doi.org/10.3390/app12073532 - 30 Mar 2022
Viewed by 301
Abstract
This paper discusses the design of a new self-balancing amplifier of an AC component power characterized by a minimal output DC offset. The design of the amplifier is based on semiconductor technology and intended for application in low-frequency analog signal processing paths, particularly [...] Read more.
This paper discusses the design of a new self-balancing amplifier of an AC component power characterized by a minimal output DC offset. The design of the amplifier is based on semiconductor technology and intended for application in low-frequency analog signal processing paths, particularly in surface-to-air missile system launcher automation circuits. The proposed solution has several design and technical-implementation advantages, whereas the primary novelty compared to the commonly used ones is the ability for self-generating a near-zero DC component value of output signal. The design features and technical parameters of the developed amplifier make it suitable for use in a wide range of devices that must ensure the stable, prolonged operation of a low-frequency power amplifier under variable weather conditions and a minimal DC offset of output signal. Full article
(This article belongs to the Special Issue Automation Control and Robotics in Human-Machine Cooperation)
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Article
Parameter Optimization of dsRNA Splicing Evolutionary Algorithm Based Fixed-Time Obstacle-Avoidance Trajectory Planning for Space Robot
Appl. Sci. 2021, 11(19), 8839; https://doi.org/10.3390/app11198839 - 23 Sep 2021
Viewed by 442
Abstract
This paper addresses a smoother fixed-time obstacle-avoidance trajectory planning based on double-stranded ribonucleic acid (dsRNA) splicing evolutionary algorithm for a dual-arm free-floating space robot, the smoothness of large joint angular velocity is improved by 15.61% on average compared with the current trajectory [...] Read more.
This paper addresses a smoother fixed-time obstacle-avoidance trajectory planning based on double-stranded ribonucleic acid (dsRNA) splicing evolutionary algorithm for a dual-arm free-floating space robot, the smoothness of large joint angular velocity is improved by 15.61% on average compared with the current trajectory planning strategy based on pose feedback, and the convergence performance is improved by 76.44% compared with the existing optimal trajectory planning strategy without pose feedback. Firstly, according to the idea of pose feedback, a novel trajectory planning strategy with low joint angular velocity input is proposed to make the pose errors of the end-effector and base converge asymptotically within fixed time. Secondly, a novel evolutionary algorithm based on the gene splicing idea of dsRNA virus is proposed to optimize the parameter of the fixed-time error response function and obstacle-avoidance algorithm, which can make joint angular velocity trajectory is planned smooth. In the end, the optimized trajectory planning strategy is applied into the dual-arm space robot system so that the robotic arm can smoothly, fast and accurately complete the tracking task. The proposed novel algorithm achieved 7.56–30.40% comprehensive performance improvement over the benchmark methods, experiment and simulation verify the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Automation Control and Robotics in Human-Machine Cooperation)
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Article
Equal Baseline Camera Array—Calibration, Testbed and Applications
Appl. Sci. 2021, 11(18), 8464; https://doi.org/10.3390/app11188464 - 12 Sep 2021
Viewed by 573
Abstract
This paper presents research on 3D scanning by taking advantage of a camera array consisting of up to five adjacent cameras. Such an array makes it possible to make a disparity map with a higher precision than a stereo camera, however it preserves [...] Read more.
This paper presents research on 3D scanning by taking advantage of a camera array consisting of up to five adjacent cameras. Such an array makes it possible to make a disparity map with a higher precision than a stereo camera, however it preserves the advantages of a stereo camera such as a possibility to operate in wide range of distances and in highly illuminated areas. In an outdoor environment, the array is a competitive alternative to other 3D imaging equipment such as Structured-light 3D scanners or Light Detection and Ranging (LIDAR). The considered kinds of arrays are called Equal Baseline Camera Array (EBCA). This paper presents a novel approach to calibrating the array based on the use of self-calibration methods. This paper also introduces a testbed which makes it possible to develop new algorithms for obtaining 3D data from images taken by the array. The testbed was released under open-source. Moreover, this paper shows new results of using these arrays with different stereo matching algorithms including an algorithm based on a convolutional neural network and deep learning technology. Full article
(This article belongs to the Special Issue Automation Control and Robotics in Human-Machine Cooperation)
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