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Applied Sciences
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Advances in Industrial Robotics and Control Systems
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Advances in Industrial Robotics and Control Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: 30 August 2026 | Viewed by 6619

Editors

Prof. Dr. Ricardo Balcazar

E-Mail Website
Guest Editor
Departamento de Mecatronica, Tecnologico de Estudios Superiores de Coacalco, Estado de Mexico 55700, Mexico
Interests: control; robotics; mechatronics
Special Issues, Collections and Topics in MDPI journals
Dr. Genaro Ochoa

E-Mail Website
Guest Editor
Sección de Estudios de Posgrado e Investigación, ESIME Azcapotzalco, Instituto Politécnico Nacional, México City 02250, Mexico
Interests: control systems; dynamic modeling; robotics; intelligent systems
Special Issues, Collections and Topics in MDPI journals
Dr. Jaime Pacheco Martínez

E-Mail Website
Guest Editor
Section of Postgraduate Studies and Research, ESIME Azcapotzalco, Instituto Politécnico Nacional, Mexico City 02250, Mexico
Interests: linear systems; nonlinear control systems; Jacobian matrices; Lyapunov methods; adaptive control; control system synthesis; fuzzy control; fuzzy set theory
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Advances in robotics are increasingly broad. Where the objective is to replace humans with machines that can perform many repetitive tasks for long periods of time, they include artificial vision, robot programming, telemetry, collaborative robotics, and Industry 4.0 and 5.0, among others. In addition, these robots have to interact with automated processes, and all the information generated has to be sent to a server (cloud). There, the data is used to analyze the growth of the industry. Clear examples are parcel companies such as Amazon, AliExpress, and MercadoLibre, among others.

What directs the behavior of industrial robots, automated systems, and even data traffic are the different control systems applied to these systems. This is why important automatic control theories, including path tracking, stabilization, synchronization, compensators, optimization, obstacle avoidance, and disturbance rejection, are applied to robotic systems. Papers in this Special Issue of “Advances in Industrial Robotics and Control Systems” may cover the following topics:

  1. Kinematics, dynamics of manipulator robots;
  2. Robot construction;
  3. Humanoid robots;
  4. Biped robots;
  5. Intelligent mobile robots;
  6. Mobile robotics;
  7. Artificial vision;
  8. Drone navigation systems;
  9. Manufacturing systems;
  10. Neural networks;
  11. Data storage and data processing;
  12. Use of synthetic data;
  13. Smart warehouses;
  14. Industry 4.0 and 5.0;
  15. Model-based or evolutionary adaptive control of robotic systems;
  16. Neural network or fuzzy control of robotic systems;
  17. Intelligent or feedback control of robotic systems;
  18. Feedback or geometric control of robotic systems;
  19. Sliding mode or robust control of robotic systems;
  20. Structure at infinity or structure control of robotic systems;
  21. Observer-based or active rejection-based control of robotic systems;
  22. Optimal control or optimization of robotic systems.

Prof. Dr. Ricardo Balcazar
Dr. Genaro Ochoa
Dr. Jaime Pacheco Martínez
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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

  • robotics
  • automatic control
  • automation
  • mechatronics

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Published Papers (2 papers)

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Research

39 pages, 7637 KB  
Article
Design and Implementation of an Industry 4.0 Oriented Robotic Cell Through the Integration of the ABB IRB 14000 Robot and Optimized PID Control of a Conveyor Belt
by Ricardo Balcazar, José de Jesús Rubio, Mario Alberto Hernandez, Jaime Pacheco, Alejandro Zacarías, Eduardo Orozco, Enrique Garcia, Genaro Ochoa, Ricardo Rodriguez-Figueroa and Roberto Morales-Montaño
Appl. Sci. 2026, 16(13), 6318; https://doi.org/10.3390/app16136318 - 23 Jun 2026
Viewed by 603
Abstract
This work addresses the design and implementation of an automated system for the handling and transportation of parts, integrating speed sensors, an optimized PID controller, an HMI interface, and an industrial robotic system. The speed sensors, powered by 5 V DC, enable continuous [...] Read more.
This work addresses the design and implementation of an automated system for the handling and transportation of parts, integrating speed sensors, an optimized PID controller, an HMI interface, and an industrial robotic system. The speed sensors, powered by 5 V DC, enable continuous measurement of the conveyor belt’s speed and direction of rotation, providing the feedback signal required for the control loop. The core element of the system is the implementation of a PID controller applied to a direct current motor responsible for driving the conveyor belt. This controller regulates the motor speed by analyzing the error between the reference speed and the measured speed, using proportional, integral, and derivative actions to improve system stability, reduce steady-state error, and minimize oscillations. The application of PID control makes it possible to achieve an appropriate dynamic response, ensuring accuracy and reliability in the transportation process. System monitoring and operation are carried out through a human–machine interface (HMI) developed in LOGO Web Editor, which communicates with the PLC (LOGO V8) to visualize and control the status of the conveyor belt, sensors, and control elements in real time. This interface facilitates interaction between the operator and the system, allowing both virtual and physical operation. In addition, RAPID programming is used to control the IRB 14000 industrial robot, enabling the reading of PLC signals and the execution of coordinated trajectories between both arms. The operating sequence includes picking up a part with the left arm, placing it on the conveyor belt, and, after detection by sensors and PLC control, subsequent manipulation by the right arm to a specific point. Finally, both arms return to their original position, ensuring synchronized and collision-free operation. Lastly, this work integrates scientific knowledge related to the modeling, analysis, and control of dynamic systems, particularly in the implementation of closed-loop PID control optimized using genetic algorithms. This control is applied directly to an embedded system through the use of an Arduino board as the processing and control platform. Likewise, technological knowledge associated with industrial automation, PLC programming, HMI development, and industrial robotics is incorporated. The convergence of these scientific and technological approaches results in a comprehensive and compelling project that demonstrates the practical application of theoretical concepts in a functional automated system representative of real industrial environments. Full article
(This article belongs to the Special Issue Advances in Industrial Robotics and Control Systems)
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29 pages, 1578 KB  
Article
Algorithmic Modified Denavit–Hartenberg Modeling for Robotic Manipulators Using Line Geometry
by Minchang Sung and Youngjin Choi
Appl. Sci. 2025, 15(9), 4999; https://doi.org/10.3390/app15094999 - 30 Apr 2025
Cited by 16 | Viewed by 5219
Abstract
This paper proposes a kinematic modeling method for robotic manipulators by extracting the modified Denavit–Hartenberg (MDH) parameters using line geometry. For single-branched manipulators, various joint axes can be represented as lines using Plücker coordinates. The forward kinematics is derived by performing the product [...] Read more.
This paper proposes a kinematic modeling method for robotic manipulators by extracting the modified Denavit–Hartenberg (MDH) parameters using line geometry. For single-branched manipulators, various joint axes can be represented as lines using Plücker coordinates. The forward kinematics is derived by performing the product of matrices which are the exponential maps lifted from two kinds of exponential coordinates using the MDH parameters. For extracting MDH parameters, line geometry systematically analyzes the following: (1) the closest point between a point and line, (2) the closest distance and twist angle between two lines, (3) the common perpendicular line and its intersection points, and (4) classifies line relationships into collinear, distant parallel, intersected, and skewed cases. For each case, five parameters including twist angle, closest distance, common perpendicular direction vector, and both feet on a common perpendicular line are sequentially computed as results of the line geometry block. Finally, the aforementioned line geometry blocks are utilized to extract the four MDH parameters according to their definitions. The effectiveness of the proposed algorithm is verified by four examples including a typical Selective Compliance Assembly Robot Arm (SCARA) robot and three different commercial manipulators. Full article
(This article belongs to the Special Issue Advances in Industrial Robotics and Control Systems)
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