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Intelligent Process Control Techniques Used for Robotics

Special Issue Information

Dear Colleagues,

Intelligent technologies include machine learning, fuzzy logic systems, neural networks, reinforcement learning, evolutionary algorithms, etc. In recent years, these intelligent technologies have been widely applied to various robots, such as industrial robots, medical robots, special robots, entertainment robots, etc. However, in order to adapt to the rapid development of robots, engineers have increasing requirements for intelligent technologies, including reliability, efficiency, autonomy, perception, controllability, etc. Although intelligent robots have developed rapidly in the past several decades, there are still some new technologies and application problems that need to be solved. Therefore, there is an urgent need for innovative intelligent algorithms, advanced modeling strategies, practical intelligent robot technologies, etc.

The main objective of this Special Issue is, through scientific researchers and technical engineers, to introduce the latest studies in the field of intelligent technologies for robotics, including intelligent algorithms, robotic systems, human–machine collaboration, etc. Furthermore, intelligent solutions for robotic engineering and future research prospects will also be provided. Authors are encouraged to submit their original contributions regarding the integration of intelligent technology with robotic systems. Potential topics include, but are not limited to, the following:

  • Intelligent control algorithms applied to robots (fuzzy control, neural network control, reinforcement learning control, etc.);
  • Artificial intelligence technologies applied to robots (cognitive mechanisms, machine vision, machine hearing, pattern recognition, machine reasoning, intelligent decision-making, etc.);
  • Examples of intelligent technologies applied to various robots (industrial robots, medical robots, special robots, entertainment robots, etc.);
  • Practical application examples of intelligent robots in automatic production processes (chemistry, biology, materials, energy, environment, food, pharmacy, manufacturing, etc.).

Dr. Tao Zhao
Prof. Dr. Xiangpeng Xie
Prof. Dr. Songyi Dian
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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes 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 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

  • fuzzy logic systems
  • neural networks
  • reinforcement learning
  • evolutionary algorithms

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Processes - ISSN 2227-9717