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New Trends in the Control of Robots and Mechatronic Systems II

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

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 2631

Special Issue Editor


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Guest Editor
DIME - Department of Mechanical, Energy, Management and Transportation Engineering, University of Genova, Genova, Italy
Interests: mechanics and control of robots and automation devices, and in particular: parallel robotics, mobile robotics, cooperation of robots in complex tasks with force control, robot control algorithms, design of miniaturized devices and microgrippers with flexible joints, design of mechatronic systems actuated by electrical linear motors, fractional-order control of mechatronic devices, design of wave energy converters

Special Issue Information

Dear Colleagues,

In recent years, research on the control of robotic and mechatronic systems has led to a wide variety of advanced paradigms and techniques. Fuzzy, neural, sliding mode, backstepping, adaptive, predictive, fault-tolerant, fractional-order controls, reinforcement learning, genetic algorithms, evolutionary computation, and their combinations are examples of possible approaches. On the other hand, a big gap still exists between the scientific state-of-the-art and the industrial scenario, in which only a very limited subset of the research findings is applied, and the attention is more focused on human–machine interfaces, connectivity, safety, reliability, cost, and other more practical aspects.

This Special Issue is focused on new trends in the control of robotic and mechatronic systems, considering in particular applications in which innovations in the control approach bring significant improvements in the system performance, for example, in terms of accuracy, readiness, adaptability to different operative conditions, and energetic efficiency, without increasing too much the control complexity from the end-user point of view and without decreasing stability and robustness. In other words, the main intent is to promote the practical feasibility and usefulness of some cutting-edge techniques with a good technology readiness level.

It is, therefore, my immense pleasure to invite you to submit a manuscript for this Special Issue, covering any aspect of design, simulation, prototyping, and testing of robotic and mechatronic control systems.

Assoc. Prof. Luca Bruzzone
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. 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

  • robot control
  • mechatronics
  • motion control
  • model-based control of mechanical systems
  • fractional-order control
  • neuro-fuzzy control
  • sliding-mode control
  • adaptive control
  • reinforcement learning

Published Papers (1 paper)

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Research

13 pages, 3327 KiB  
Article
Motion Control Method of Bionic Robot Dog Based on Vision and Navigation Information
by Zhaolu Li, Ning Xu, Xiaoli Zhang, Xiafu Peng and Yumin Song
Appl. Sci. 2023, 13(6), 3664; https://doi.org/10.3390/app13063664 - 13 Mar 2023
Cited by 2 | Viewed by 2301
Abstract
With the progress and development of AI technology and industrial automation technology, AI robot dogs are widely used in engineering practice to replace human beings in high-precision and tedious industrial operations. Bionic robots easily produce control errors due to the influence of spatial [...] Read more.
With the progress and development of AI technology and industrial automation technology, AI robot dogs are widely used in engineering practice to replace human beings in high-precision and tedious industrial operations. Bionic robots easily produce control errors due to the influence of spatial disturbance factors in the process of pose determination. It is necessary to calibrate robots accurately to improve the positioning control accuracy of bionic robots. Therefore, a robust control algorithm for bionic robots based on binocular vision navigation is proposed. An optical CCD binocular vision dynamic tracking system is used to measure the end position and pose parameters of a bionic robot, and the kinematics model of the controlled object is established. Taking the degree of freedom parameter of the robot’s rotating joint as the control constraint parameter, a hierarchical subdimensional space motion planning model of the robot is established. The binocular vision tracking method is used to realize the adaptive correction of the position and posture of the bionic robot and achieve robust control. The simulation results show that the fitting error of the robot’s end position and pose parameters is low, and the dynamic tracking performance is good when the method is used for the position positioning of control of the bionic robot. Full article
(This article belongs to the Special Issue New Trends in the Control of Robots and Mechatronic Systems II)
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