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Automation Control and Robotics in Human-Machine Cooperation

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

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 29275

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Special Issue Editors

Dr. Wojciech Kaczmarek

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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

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Guest Editor

Dr. Albert Smalcerz

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Guest Editor

Department of Industrial Informatics, Faculty of Materials Science, Silesian University of Technology, Krasinskiego 8, 40-019 Katowice, Poland
Interests: industrial informatics; induction heating; electromagnetic field; numerical simulation; optimization; electromagnetic fields; alloys; electromagnetics; computational electromagnetics; electromagnetic engineering; refining
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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 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

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 (11 papers)

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Research

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12 pages, 6266 KiB

Open AccessArticle

Experimental Study of the Vibration of the Spot Welding Gun at a Robotic Station

by Szymon Borys, Wojciech Kaczmarek, Dariusz Laskowski and Rafał Polak

Appl. Sci. 2022, 12(23), 12209; https://0-doi-org.brum.beds.ac.uk/10.3390/app122312209 - 29 Nov 2022

Cited by 3 | Viewed by 1559

Abstract

The paper presents issues associated with the experimental study of the vibration of a spot welding gun mounted on a robotic arm. The main aim of the study was to assess the vibration of the robot flange and the vibration of the mounted tool. Because of the tools’ large size and weight (up to 150 kg), manipulating it in a limited space is a challenge for programmers when defining trajectories. The article presents the results of inertial measurements of the KUKA KR120 R2500 industrial robot equipped with a pneumatic welding tool, paying particular attention to the vibrations occurring at the process points. Inertial tests on the robotic station were made using triaxial accelerometers and a high-speed camera. The methodology developed by the authors confirmed the existence of structural vibrations and allowed for defining the relationship between the robot’s motion parameters (notably velocity and acceleration) and the size of the vibrations present. The paper presents selected test results for various parameters of robot motion (speeds from 2000 mm/s to 500 mm/s and acceleration ramps ranging from 100% to 25%). In the course of the study, a disturbance was noticed in the form of a reduction in the value of maximum acceleration. This could be attributed to the appearance of the structure’s natural vibrations. Their character is not constant, and they are damped. Full article

(This article belongs to the Special Issue Automation Control and Robotics in Human-Machine Cooperation)

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19 pages, 9333 KiB

Open AccessArticle

Experimental Study of the Vibrations of a Roller Shutter Gripper

by Wojciech Kaczmarek, Szymon Borys, Jarosław Panasiuk, Michał Siwek and Piotr Prusaczyk

Appl. Sci. 2022, 12(19), 9996; https://0-doi-org.brum.beds.ac.uk/10.3390/app12199996 - 05 Oct 2022

Cited by 5 | Viewed by 1688

Abstract

The article presents issues related to an experimental study of the vibrations of a roller shutter gripper on a robotic palletizing station. The authors presented the developed and built construction of the gripper for handling whole layers of products, separators, and pallets. The concept of the device was developed in cooperation with an integrator company. The authors verified the functionality of the gripper in a virtual environment for modeling and programming industrial robots. After the gripper was manufactured and the control software was developed for it, functional tests and inertia tests were carried out. The main purpose of the tests was to determine the vibration of the robot’s flange and the vibration of the attached gripper. Tests of the gripper’s properties on the robotic test bench were performed using MTi XSENS sensors and a PHANTOM V210 high-speed camera. The testing methodology proposed by the authors made it possible to confirm the occurrence of vibrations in the structure and to determine the relationship between the parameters of the robot’s motion (velocity and acceleration) and the magnitude of the vibrations occurring. During the tests, a disturbance in the decrease in the maximum value of acceleration was noted. This may be due to the appearance of natural vibrations in the structure. They have a damped character; however, they are not steady. In future work, the authors will focus on the possibility of using the proposed methodology to reduce robot vibrations in selected robotic production processes (such as spot welding). Full article

(This article belongs to the Special Issue Automation Control and Robotics in Human-Machine Cooperation)

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14 pages, 14265 KiB

Open AccessArticle

An Easy to Use Deep Reinforcement Learning Library for AI Mobile Robots in Isaac Sim

by Maximiliano Rojas, Gabriel Hermosilla, Daniel Yunge and Gonzalo Farias

Appl. Sci. 2022, 12(17), 8429; https://0-doi-org.brum.beds.ac.uk/10.3390/app12178429 - 24 Aug 2022

Cited by 6 | Viewed by 3730

Abstract

The use of mobile robots for personal and industrial uses is becoming popular. Currently, many robot simulators with high-graphical capabilities can be used by engineering to develop and test these robots such as Isaac Sim. However, using that simulator to train mobile robots with the deep reinforcement learning paradigm can be very difficult and time-consuming if one wants to develop a custom experiment, requiring an understanding of several libraries and APIs to use them together correctly. The proposed work aims to create a library that conceals configuration problems in creating robots, environments, and training scenarios, reducing the time dedicated to code. Every developed method is equivalent to sixty-five lines of code at maximum and five at minimum. That brings time saving in simulated experiments and data collection, thus reducing the time to produce and test viable algorithms for robots in the industry or academy. Full article

(This article belongs to the Special Issue Automation Control and Robotics in Human-Machine Cooperation)

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16 pages, 1630 KiB

Open AccessArticle

The Use of Social Robots in the Diagnosis of Autism in Preschool Children

by Krzysztof Arent, David J. Brown, Joanna Kruk-Lasocka, Tomasz Lukasz Niemiec, Aleksandra Helena Pasieczna, Penny J. Standen and Remigiusz Szczepanowski

Appl. Sci. 2022, 12(17), 8399; https://0-doi-org.brum.beds.ac.uk/10.3390/app12178399 - 23 Aug 2022

Cited by 6 | Viewed by 1863

Abstract

The present study contributes to the research problem of applying social robots in autism diagnosis. There is a common belief that existing diagnostic methods for autistic spectrum disorder are not effective. Advances in Human–Robot Interactions (HRI) provide potential new diagnostic methods based on interactive robots. We investigated deficits in turn-taking in preschool children by observing their interactions with the NAO robot during two games: (Dance with me vs. Touch me). We compared children’s interaction profiles with the robot (five autistic vs. five typically developing young children). Then, to investigate turn-taking deficits, we adopted a rating procedure to indicate differences between both groups of children based on an observational scale. A statistical analysis based on ratings of the children’s interactions with the NAO robot indicated that autistic children presented a deficient level of turn-taking behaviors. Our study provides evidence for the potential of designing and implementing an interactive dyadic game between a child and a social robot that can be used to detect turn-taking deficits based on objective measures. We also discuss our results in the context of existing studies and propose guidelines for a robotic-enabled autism diagnosis system. Full article

(This article belongs to the Special Issue Automation Control and Robotics in Human-Machine Cooperation)

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17 pages, 5542 KiB

Open AccessArticle

Position Control of a Mobile Robot through Deep Reinforcement Learning

by Francisco Quiroga, Gabriel Hermosilla, Gonzalo Farias, Ernesto Fabregas and Guelis Montenegro

Appl. Sci. 2022, 12(14), 7194; https://0-doi-org.brum.beds.ac.uk/10.3390/app12147194 - 17 Jul 2022

Cited by 7 | Viewed by 2238

Abstract

This article proposes the use of reinforcement learning (RL) algorithms to control the position of a simulated Kephera IV mobile robot in a virtual environment. The simulated environment uses the OpenAI Gym library in conjunction with CoppeliaSim, a 3D simulation platform, to perform the experiments and control the position of the robot. The RL agents used correspond to the deep deterministic policy gradient (DDPG) and deep Q network (DQN), and their results are compared with two control algorithms called Villela and IPC. The results obtained from the experiments in environments with and without obstacles show that DDPG and DQN manage to learn and infer the best actions in the environment, allowing us to effectively perform the position control of different target points and obtain the best results based on different metrics and indices. Full article

(This article belongs to the Special Issue Automation Control and Robotics in Human-Machine Cooperation)

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20 pages, 4642 KiB

Open AccessArticle

Non-Uniform Input-Based Adaptive Growing Neural Gas for Unstructured Environment Map Construction

by Suyu Wang, Ze Ren and Miao Wu

Appl. Sci. 2022, 12(12), 6110; https://0-doi-org.brum.beds.ac.uk/10.3390/app12126110 - 16 Jun 2022

Cited by 1 | Viewed by 1064

Abstract

The research and development of special robots such as excavation robots is an important way to achieve safe and efficient production in coal mines. Affected by the unstructured environment such as complex working conditions and unsteady factor disturbances, the real-time construction of section environment maps that can accurately describe the environment and facilitate trajectory planning and decision making has become a key scientific problem to be solved as soon as possible. Therefore, non-uniform input based adaptive growing neural gas for unstructured environment map construction has been proposed. Considering complex load identification, real-time location identification, and the types of unsteady disturbance factors and working conditions, a set of environment identification models has been established based on a large amount of underground measured data training. These models can express whether the section environment has changed, as well as the type and magnitude of the change, to realize the overall knowledge extraction and parametric representation of the unstructured environment. Then, in order to solve the problems of inaccurate topology, excessive aging of connecting edges, and excessive deletion of nodes in non-uniform input environment, an adaptive growing neural gas algorithm based on non-uniform input environment (AGNG-NU) is proposed. Featured by a dynamic response deletion mechanism and adaptive adjustment mechanism of neuron parameters, the generated nodes and their topology can be dynamically adjusted according to the density of regional sample points. Several sets of non-uniform input environments are set to test the algorithm. The experimental results show that the topological maps established by AGNG-NU express clearer environmental information and, at the same time, the accuracy and distribution are improved by 8% and 15%, respectively, compared with the basic GNG algorithm. The accuracy and the distribution have also been significantly improved compared with other common SOM and GCS algorithms. Full article

(This article belongs to the Special Issue Automation Control and Robotics in Human-Machine Cooperation)

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17 pages, 3868 KiB

Open AccessArticle

Path Tracking of Underground Mining Boom Roadheader Combining BP Neural Network and State Estimation

by Yuanyuan Qu, Teng Yang, Tao Li, Yu Zhan and Shichen Fu

Appl. Sci. 2022, 12(10), 5165; https://0-doi-org.brum.beds.ac.uk/10.3390/app12105165 - 20 May 2022

Cited by 4 | Viewed by 1643

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 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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17 pages, 11157 KiB

Open AccessArticle

Self-Balancing Power Amplifier with a Minimal DC Offset for Launcher Automation Control Circuits of a Surface-to-Air Missile System

by Piotr Żółtowski and Witold Bużantowicz

Appl. Sci. 2022, 12(7), 3532; https://0-doi-org.brum.beds.ac.uk/10.3390/app12073532 - 30 Mar 2022

Cited by 2 | Viewed by 3346

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 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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17 pages, 551 KiB

Open AccessArticle

Parameter Optimization of dsRNA Splicing Evolutionary Algorithm Based Fixed-Time Obstacle-Avoidance Trajectory Planning for Space Robot

by Junyu Yao, Wen Yan, Qijie Lan, Yicheng Liu and Yun Zhao

Appl. Sci. 2021, 11(19), 8839; https://0-doi-org.brum.beds.ac.uk/10.3390/app11198839 - 23 Sep 2021

Cited by 4 | Viewed by 1261

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.

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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26 pages, 14676 KiB

Open AccessArticle

Equal Baseline Camera Array—Calibration, Testbed and Applications

by Adam L. Kaczmarek and Bernhard Blaschitz

Appl. Sci. 2021, 11(18), 8464; https://0-doi-org.brum.beds.ac.uk/10.3390/app11188464 - 12 Sep 2021

Cited by 2 | Viewed by 1854

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 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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Review

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19 pages, 1050 KiB

Open AccessReview

Meat 4.0: Principles and Applications of Industry 4.0 Technologies in the Meat Industry

by Noemí Echegaray, Abdo Hassoun, Sandeep Jagtap, Michelle Tetteh-Caesar, Manoj Kumar, Igor Tomasevic, Gulden Goksen and Jose Manuel Lorenzo

Appl. Sci. 2022, 12(14), 6986; https://0-doi-org.brum.beds.ac.uk/10.3390/app12146986 - 10 Jul 2022

Cited by 32 | Viewed by 7049

Abstract

Meat 4.0 refers to the application the fourth industrial revolution (Industry 4.0) technologies in the meat sector. Industry 4.0 components, such as robotics, Internet of Things, Big Data, augmented reality, cybersecurity, and blockchain, have recently transformed many industrial and manufacturing sectors, including agri-food sectors, such as the meat industry. The need for digitalised and automated solutions throughout the whole food supply chain has increased remarkably during the COVID-19 pandemic. This review will introduce the concept of Meat 4.0, highlight its main enablers, and provide an updated overview of recent developments and applications of Industry 4.0 innovations and advanced techniques in digital transformation and process automation of the meat industry. A particular focus will be put on the role of Meat 4.0 enablers in meat processing, preservation and analyses of quality, safety and authenticity. Our literature review shows that Industry 4.0 has significant potential to improve the way meat is processed, preserved, and analysed, reduce food waste and loss, develop safe meat products of high quality, and prevent meat fraud. Despite the current challenges, growing literature shows that the meat sector can be highly automated using smart technologies, such as robots and smart sensors based on spectroscopy and imaging technology. Full article

(This article belongs to the Special Issue Automation Control and Robotics in Human-Machine Cooperation)

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