Advanced Robotics Applications in Industry

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

Deadline for manuscript submissions: closed (18 February 2022) | Viewed by 24281

Special Issue Editors


E-Mail Website
Guest Editor
Laboratory for Advanced Manufacturing Simulation and Robotics (LAMS), School of Mechanical and Materials Engineering, University College Dublin, Dublin D04 V1W8, Ireland
Interests: digital manufacturing; manufacturing simulation; robotics; assembly processes; production planning and control
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Production Engineering, KTH Royal Institute of Technology, 10044 Stockholm, Sweden
Interests: process planning; machining; robotics; assembly; condition-based monitoring; maintenance; lifecycle engineering; cloud manufacturing
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Mechanical Engineering and Aeronautics, University of Patras, Rio Patras 26504, Greece
Interests: robotic systems; automation; augmented, mixed, and virtual reality in manufacturing; manufacturing process modeling; cloud technologies; Internet of Things (IoT); digital twin; 5G; artificial intelligence; product–service systems (PSS); Industry 4.0; Industry 5.0
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Laboratory for Manufacturing Systems and Automation (LMS), Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Rio Patras, Greece
Interests: smart intralogistics, robotics; virtual reality; augmented reality; virtual collaborative environments; AI
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Several recent technological advancements have led to the realization of novel industrial robot applications. New sensing, perception, machine intelligence, control, and computing paradigms have laid the foundation for facilitating the introduction of innovative robotics technologies in a series of diverse fields and manufacturing sectors.

As a result, new research initiatives will have to be undertaken to demonstrate how robots can be introduced in a broader range of processes and applications, including those where close cooperation with human operators is required, as well as how a higher level of flexibility can be achieved, while fostering the faster and more accurate modeling, simulation, and control of industrial robotics processes utilizing Industry 4.0 technologies. 

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

  • Novel industrial robot applications;
  • Sensing and control in robotics;
  • Modeling and simulation in robotics and automation;
  • Advanced software frameworks for modeling and controlling robotics applications;
  • Digital twins for robotics applications;
  • Novel applications based on the robot operating system (ROS) framework;
  • Robots and Industry 4.0 concepts;
  • Mobile robotic platforms in manufacturing and logistics;
  • Human–robot collaboration for manufacturing processes;
  • Robotics technologies for joining processes;
  • Advanced robot-based quality inspection and control applications;
  • Safety in industrial robot applications;
  • Advanced cyber-physical systems for industrial robot applications;
  • Design and development of robot end-effectors;
  • Learning and training for industrial robot applications.

Prof. Nikolaos Papakostas
Prof. Lihui Wang
Prof. Dimitris Mourtzis
Dr. Sotiris Makris
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.

Published Papers (8 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Editorial

Jump to: Research, Review

4 pages, 168 KiB  
Editorial
Editorial of the Special Issue “Advanced Robotics Applications in Industry”
by Nikolaos Papakostas, Lihui Wang, Sotiris Makris and Dimitris Mourtzis
Appl. Sci. 2023, 13(10), 5836; https://doi.org/10.3390/app13105836 - 09 May 2023
Viewed by 841
Abstract
Recently, the emergence of various technological advancements has enabled the development of new and unique applications for industrial robots [...] Full article
(This article belongs to the Special Issue Advanced Robotics Applications in Industry)

Research

Jump to: Editorial, Review

20 pages, 5435 KiB  
Article
Continuous-Time Nonlinear Model Predictive Tracking Control with Input Constraints Using Feedback Linearization
by Yong-Lin Kuo and Peeraya Pongpanyaporn
Appl. Sci. 2022, 12(10), 5016; https://doi.org/10.3390/app12105016 - 16 May 2022
Cited by 3 | Viewed by 1576
Abstract
This paper presents a tracking control scheme for nonlinear systems with input constraints by combining the continuous-time model predictive control and the feedback linearization. Although there are some similar combinations for nonlinear systems presented in literature, their formulations are complex and massive computations [...] Read more.
This paper presents a tracking control scheme for nonlinear systems with input constraints by combining the continuous-time model predictive control and the feedback linearization. Although there are some similar combinations for nonlinear systems presented in literature, their formulations are complex and massive computations are unavoidable. This study aims to simplify the formulations and reduce the computational loads by imposing the Laguerre functions to approximate the control signals. Since the Laguerre functions have the property of orthogonality, the tracking control problem, by applying the combination, leads to a constrained quadratic optimization problem in terms of the coefficients associated with the Laguerre functions, where the input constraints are converted so as to be state-dependent, based on feedback linearization. The Hildreth’s quadratic programming algorithm is used to solve the optimization problem, so as to determine the coefficients. Moreover, this study also summarizes some common linearization schemes and shows their pros and cons. Furthermore, the proposed approach is applied to two illustrative examples, and the control performances are compared with those by linear control strategies combined with those linearization schemes. Full article
(This article belongs to the Special Issue Advanced Robotics Applications in Industry)
Show Figures

Figure 1

17 pages, 2589 KiB  
Article
Closed-Loop Robotic Arm Manipulation Based on Mixed Reality
by Dimitris Mourtzis, John Angelopoulos and Nikos Panopoulos
Appl. Sci. 2022, 12(6), 2972; https://doi.org/10.3390/app12062972 - 14 Mar 2022
Cited by 15 | Viewed by 4619
Abstract
Robotic manipulators have become part of manufacturing systems in recent decades. However, in the realm of Industry 4.0, a new type of manufacturing cell has been introduced—the so-called collaborative manufacturing cell. In such collaborative environments, communication between a human operator and robotic manipulators [...] Read more.
Robotic manipulators have become part of manufacturing systems in recent decades. However, in the realm of Industry 4.0, a new type of manufacturing cell has been introduced—the so-called collaborative manufacturing cell. In such collaborative environments, communication between a human operator and robotic manipulators must be flawless, so that smooth collaboration, i.e., human safety, is ensured constantly. Therefore, engineers have focused on the development of suitable human–robot interfaces (HRI) in order to tackle this issue. This research work proposes a closed-loop framework for the human–robot interface based on the utilization of digital technologies, such as Mixed Reality (MR). Concretely, the framework can be realized as a methodology for the remote and safe manipulation of the robotic arm in near real-time, while, simultaneously, safety zones are displayed in the field of view of the shop-floor technician. The method is based on the creation of a Digital Twin of the robotic arm and the setup of a suitable communication framework for continuous and seamless communication between the user interface, the physical robot, and the Digital Twin. The development of the method is based on the utilization of a ROS (Robot Operating System) for the modelling of the Digital Twin, a Cloud database for data handling, and Mixed Reality (MR) for the Human–Machine Interface (HMI). The developed MR application is tested in a laboratory-based machine shop, incorporating collaborative cells. Full article
(This article belongs to the Special Issue Advanced Robotics Applications in Industry)
Show Figures

Figure 1

21 pages, 3626 KiB  
Article
Joint Motion Planning of Industrial Robot Based on Modified Cubic Hermite Interpolation with Velocity Constraint
by Yasong Pu, Yaoyao Shi, Xiaojun Lin, Wenbin Zhang and Pan Zhao
Appl. Sci. 2021, 11(19), 8879; https://doi.org/10.3390/app11198879 - 24 Sep 2021
Cited by 6 | Viewed by 1925
Abstract
As for industrial robots’ point-to-point joint motion planning with constrained velocity, cubic polynomial planning has the problem of discontinuous acceleration; quintic polynomial planning requires acceleration to be specified in advance, which will likely cause velocity to fluctuate largely because appropriate acceleration assigned in [...] Read more.
As for industrial robots’ point-to-point joint motion planning with constrained velocity, cubic polynomial planning has the problem of discontinuous acceleration; quintic polynomial planning requires acceleration to be specified in advance, which will likely cause velocity to fluctuate largely because appropriate acceleration assigned in advance is hardly acquired. Aiming at these problems, a modified cubic Hermite interpolation for joint motion planning was proposed. In the proposed methodology, knots of cubic Hermite interpolation need to be reconfigured according to the initial knots. The formulas for how to build new knots were put forward after derivation. Using the newly-built knots instead of initial knots for cubic Hermite interpolation, joint motion planning was carried out. The purpose was that the joint planning not only satisfied the displacement and velocity constraints at the initial knots but also guaranteed C2 continuity and less velocity fluctuation. A study case was given to verify the rationality and effectiveness of the methodology. Compared with the other two planning methods, it proved that the raised problems can be solved effectively via the proposed methodology, which is beneficial to the working performance and service life of industrial robots. Full article
(This article belongs to the Special Issue Advanced Robotics Applications in Industry)
Show Figures

Figure 1

14 pages, 5239 KiB  
Article
Cognitive Mechatronic Devices for Reconfigurable Production of Complex Parts
by Panagiotis Karagiannis, George Michalos, Dionisis Andronas, Aleksandros-Stereos Matthaiakis, Christos Giannoulis and Sotiris Makris
Appl. Sci. 2021, 11(11), 5034; https://doi.org/10.3390/app11115034 - 29 May 2021
Cited by 3 | Viewed by 2197
Abstract
This paper discusses a robotic cell that handles geometrically complex products, exploiting cognitive control and actuation systems for the manipulation, assembly and packaging. The individual mechatronic components, namely a 6-DoF gripper and a flexible assembly mechanism, have been designed via functional decomposition of [...] Read more.
This paper discusses a robotic cell that handles geometrically complex products, exploiting cognitive control and actuation systems for the manipulation, assembly and packaging. The individual mechatronic components, namely a 6-DoF gripper and a flexible assembly mechanism, have been designed via functional decomposition of the actual assembly and handling tasks. The flexibility of these mechanisms is exploited through control modules, performing different cognition functions at cell, resource and device level. The design approach can be generalized for tasks requiring dexterity and adaptation to products. A case study from the consumer goods sector, showcases the system’s reconfigurability and efficiency. Full article
(This article belongs to the Special Issue Advanced Robotics Applications in Industry)
Show Figures

Figure 1

23 pages, 6553 KiB  
Article
Enabling Flexibility in Manufacturing by Integrating Shopfloor and Process Perception for Mobile Robot Workers
by Angelos Christos Bavelos, Niki Kousi, Christos Gkournelos, Konstantinos Lotsaris, Sotiris Aivaliotis, George Michalos and Sotiris Makris
Appl. Sci. 2021, 11(9), 3985; https://doi.org/10.3390/app11093985 - 28 Apr 2021
Cited by 19 | Viewed by 3596
Abstract
Robotic flexibility in industry is becoming more and more relevant nowadays, especially with the rise of the Industry 4.0 concept. This paper presents a smart execution control framework for enabling the autonomous operation of flexible mobile robot workers. These robot resources are able [...] Read more.
Robotic flexibility in industry is becoming more and more relevant nowadays, especially with the rise of the Industry 4.0 concept. This paper presents a smart execution control framework for enabling the autonomous operation of flexible mobile robot workers. These robot resources are able to autonomously navigate the shopfloor, undertaking multiple operations while acting as assistants to human operators. To enable this autonomous behavior, the proposed framework integrates robot perception functions for the real-time shopfloor and process understanding while orchestrating the process execution. A Digital World Model is deployed synthesizing the sensor data coming from multiple 2D and 3D sensors from the shopfloor. This model is consumed for the perception functions enabling the real-time shopfloor and process perception by the robot workers. This smart control system has been applied and validated in a case study from the automotive sector. Full article
(This article belongs to the Special Issue Advanced Robotics Applications in Industry)
Show Figures

Figure 1

18 pages, 4932 KiB  
Article
Sensor-Guided Assembly of Segmented Structures with Industrial Robots
by Yuan-Chih Peng, Shuyang Chen, Devavrat Jivani, John Wason, William Lawler, Glenn Saunders, Richard J. Radke, Jeff Trinkle, Shridhar Nath and John T. Wen
Appl. Sci. 2021, 11(6), 2669; https://doi.org/10.3390/app11062669 - 17 Mar 2021
Cited by 5 | Viewed by 2305
Abstract
This paper presents a robotic assembly methodology for the manufacturing of large segmented composite structures. The approach addresses three key steps in the assembly process: panel localization and pick-up, panel transport, and panel placement. Multiple stationary and robot-mounted cameras provide information for localization [...] Read more.
This paper presents a robotic assembly methodology for the manufacturing of large segmented composite structures. The approach addresses three key steps in the assembly process: panel localization and pick-up, panel transport, and panel placement. Multiple stationary and robot-mounted cameras provide information for localization and alignment. A robot wrist-mounted force/torque sensor enables gentle but secure panel pick-up and placement. Human-assisted path planning ensures reliable collision-free motion of the robot with a large load in a tight space. A finite state machine governs the process flow and user interface. It allows process interruption and return to the previous known state in case of error condition or when secondary operations are needed. For performance verification, a high resolution motion capture system provides the ground truth reference. An experimental testbed integrating an industrial robot, vision and force sensors, and representative laminated composite panels demonstrates the feasibility of the proposed assembly process. Experimental results show sub-millimeter placement accuracy with shorter cycle times, lower contact force, and reduced panel oscillation than manual operations. This work demonstrates the versatility of sensor guided robotic assembly operation in a complex end-to-end tasks using the open source Robot Operating System (ROS) software framework. Full article
(This article belongs to the Special Issue Advanced Robotics Applications in Industry)
Show Figures

Figure 1

Review

Jump to: Editorial, Research

35 pages, 6517 KiB  
Review
Digital Twin for Human–Robot Collaboration in Manufacturing: Review and Outlook
by Aswin K. Ramasubramanian, Robins Mathew, Matthew Kelly, Vincent Hargaden and Nikolaos Papakostas
Appl. Sci. 2022, 12(10), 4811; https://doi.org/10.3390/app12104811 - 10 May 2022
Cited by 23 | Viewed by 5514
Abstract
Industry 4.0, as an enabler of smart factories, focuses on flexible automation and customization of products by utilizing technologies such as the Internet of Things and cyber–physical systems. These technologies can also support the creation of virtual replicas which exhibit real-time characteristics of [...] Read more.
Industry 4.0, as an enabler of smart factories, focuses on flexible automation and customization of products by utilizing technologies such as the Internet of Things and cyber–physical systems. These technologies can also support the creation of virtual replicas which exhibit real-time characteristics of a physical system. These virtual replicas are commonly referred to as digital twins. With the increased adoption of digitized products, processes and services across manufacturing sectors, digital twins will play an important role throughout the entire product lifecycle. At the same time, collaborative robots have begun to make their way onto the shop floor to aid operators in completing tasks through human–robot collaboration. Therefore, the focus of this paper is to provide insights into approaches used to create digital twins of human–robot collaboration and the challenges in developing these digital twins. A review of different approaches for the creation of digital twins is presented, and the function and importance of digital twins in human–robot collaboration scenarios are described. Finally, the paper discusses the challenges of creating a digital twin, in particular the complexities of modelling the digital twin of human–robot collaboration and the exactness of the digital twin with respect to the physical system. Full article
(This article belongs to the Special Issue Advanced Robotics Applications in Industry)
Show Figures

Figure 1

Back to TopTop