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Robotics
Special Issues
Integrating Robotics into High-Accuracy Industrial Operations
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Integrating Robotics into High-Accuracy Industrial Operations

A special issue of Robotics (ISSN 2218-6581). This special issue belongs to the section "Industrial Robots and Automation".

Deadline for manuscript submissions: 28 February 2025 | Viewed by 5134

Special Issue Editor

Dr. Andrius Dzedzickis

E-Mail Website
Guest Editor
Department of Mechatronics, Robotics, and Digital Manufacturing, Vilnius Gediminas Technical University, LT-10105 Vilnius, Lithuania
Interests: robotic process automation; artificial intelligence in robotics; virtual and augmented reality in industry; digital twins of industrial systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Robotic technology has witnessed significant advancements in recent years, making it increasingly capable of handling complex tasks with high accuracy and precision. These advancements include the development of advanced sensors, intelligent algorithms, and sophisticated control systems that enable robots to perform tasks with a level of accuracy that surpasses human capabilities. This makes them well-suited for applications where accuracy is of the utmost importance, such as precision machining, assembly, measurement, and quality control. Robots have become a key driving force for enhancing production efficiency, ensuring product quality, and catalyzing innovation in the industrial sector.

This Special Issue aims to explore the cutting-edge advancements, challenges, and solutions pertaining to robotics technology in high-accuracy industrial operations. We encourage the submission of original research articles, reviews, and short communications focused on precision machining, assembly, measurement, quality control, etc. Topics of interest for this Special Issue include, but are not limited to, the following:

  1. Robotic applications in high-accuracy manufacturing and machining;
  2. Optimal design of industrial robotics for precise machining;
  3. Human-robot collaboration in high-accuracy applications;
  4. High-accuracy autonomous navigation and control in industrial environments;
  5. Quality control and inspection using robotic systems;
  6. Optimization of logistics and supply chain operations through robotics;
  7. Robotics-enabled predictive maintenance in high-accuracy machinery;
  8. Integration of artificial intelligence in high-accuracy robotic systems;
  9. Robotic solutions for high-accuracy material handling and manipulation tasks;
  10. Sensing methods systems and technologies for high accuracy robotic applications;
  11. Safety considerations in deploying robotics for high-accuracy and precision tasks;
  12. Virtual and augmented reality as tool enabling high-accuracy robotic application.

Dr. Andrius Dzedzickis
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. Robotics 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 1800 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

  • precision engineering
  • industrial robots
  • industrial automation
  • high-accuracy robotic applications
  • human–robot interaction
  • high-accuracy robotic machining
  • robotic quality control
  • robots positioning accuracy and repeatability
  • artificial intelligence in industrial robotics
  • sensors in robotic systems

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Published Papers (3 papers)

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Research

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12 pages, 2009 KiB  
Article
The Effectiveness of a Robotic Workstation Simulation Implementation in the Automotive Industry Using a Closed-Form Solution of the Absolute Orientation Problem
by Wojciech Andrzej Szulc and Piotr Czop
Robotics 2024, 13(11), 161; https://doi.org/10.3390/robotics13110161 - 30 Oct 2024
Viewed by 553
Abstract
This paper provides an in-depth analysis of a novel methodology to enhance the commissioning processes of robotic production lines in the automotive sector, with a particular emphasis on the implementation of offline programming (OLP) methods. The proposed innovative methodology, verified within the automotive [...] Read more.
This paper provides an in-depth analysis of a novel methodology to enhance the commissioning processes of robotic production lines in the automotive sector, with a particular emphasis on the implementation of offline programming (OLP) methods. The proposed innovative methodology, verified within the automotive industry, introduces a systematic, iterative process for calibrating and aligning the local user coordinate system (UCS) with high-precision external measurements, ensuring minimal discrepancy between simulated and actual robot paths. A significant contribution of this study is an original adjustment of the numerical algorithm applying a closed-form solution to the absolute orientation problem where unit quaternions are used to establish a UCS and evaluate positioning errors. The experimental validation study draws from 485 measurement datasets gathered across more than 300 robot stations, with each dataset comprising at least six measured point pairs, using readings from both internal robot positioning systems and a Leica AT403 laser tracker, aligned with nominal tooling values. This approach addresses discrepancies between simulated and actual environments, and our findings show an 83.51% success rate for direct implementation of simulated robot path programs. This result underscores the effectiveness of the proposed method and demonstrates the accuracy of the developed numerical algorithm, providing a reliable measure of real OLP implementation effectiveness in the automotive sector. This method further streamlines multi-robot station setup through centralized UCS alignment, significantly reducing commissioning time and enhancing efficiency in both the assembly and commissioning stages of robotized production lines. The proposed methodology facilitates precise alignment in the commissioning stage and highlights the need for synchronized simulation updates, robust offline programming practices, and regular kinematic error verification to further enhance OLP accuracy. Full article
(This article belongs to the Special Issue Integrating Robotics into High-Accuracy Industrial Operations)
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21 pages, 7906 KiB  
Article
Visual Servoing Architecture of Mobile Manipulators for Precise Industrial Operations on Moving Objects
by Javier González Huarte and Aitor Ibarguren
Robotics 2024, 13(5), 71; https://doi.org/10.3390/robotics13050071 - 2 May 2024
Viewed by 2236
Abstract
Although the use of articulated robots and AGVs is common in many industrial sectors such as automotive or aeronautics, the use of mobile manipulators is not widespread nowadays. Even so, the majority of applications separate the navigation and manipulation tasks, avoiding simultaneous movements [...] Read more.
Although the use of articulated robots and AGVs is common in many industrial sectors such as automotive or aeronautics, the use of mobile manipulators is not widespread nowadays. Even so, the majority of applications separate the navigation and manipulation tasks, avoiding simultaneous movements of the platform and arm. The capability to use mobile manipulators to perform operations on moving objects would open the door to new applications such as the riveting or screwing of parts transported by conveyor belts or AGVs. This paper presents a novel position-based visual servoing (PBVS) architecture for mobile manipulators for precise industrial operations on moving parts. The proposed architecture includes a state machine to guide the process through the different phases of the task to ensure its correct execution. The approach has been validated in an industrial environment for screw-fastening operations, obtaining promising results and metrics. Full article
(This article belongs to the Special Issue Integrating Robotics into High-Accuracy Industrial Operations)
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Review

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33 pages, 3278 KiB  
Review
A Practical Roadmap to Learning from Demonstration for Robotic Manipulators in Manufacturing
by Alireza Barekatain, Hamed Habibi and Holger Voos
Robotics 2024, 13(7), 100; https://doi.org/10.3390/robotics13070100 - 10 Jul 2024
Cited by 1 | Viewed by 1685
Abstract
This paper provides a structured and practical roadmap for practitioners to integrate learning from demonstration (LfD) into manufacturing tasks, with a specific focus on industrial manipulators. Motivated by the paradigm shift from mass production to mass customization, it is crucial to have an [...] Read more.
This paper provides a structured and practical roadmap for practitioners to integrate learning from demonstration (LfD) into manufacturing tasks, with a specific focus on industrial manipulators. Motivated by the paradigm shift from mass production to mass customization, it is crucial to have an easy-to-follow roadmap for practitioners with moderate expertise, to transform existing robotic processes to customizable LfD-based solutions. To realize this transformation, we devise the key questions of “What to Demonstrate”, “How to Demonstrate”, “How to Learn”, and “How to Refine”. To follow through these questions, our comprehensive guide offers a questionnaire-style approach, highlighting key steps from problem definition to solution refinement. This paper equips both researchers and industry professionals with actionable insights to deploy LfD-based solutions effectively. By tailoring the refinement criteria to manufacturing settings, this paper addresses related challenges and strategies for enhancing LfD performance in manufacturing contexts. Full article
(This article belongs to the Special Issue Integrating Robotics into High-Accuracy Industrial Operations)
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