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Special Issue "New Trends in Robotics and Automation"
A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".
Deadline for manuscript submissions: 30 November 2023 | Viewed by 4074
Special Issue Editors
Interests: human-vehicle cooperative steering control; intelligent vehicle motion control; advanced control theory
Special Issues, Collections and Topics in MDPI journals
Special Issue in Machines: Modeling, Estimation, Control, and Decision for Human-Vehicle Systems
Interests: reinforcement learning; multi-objective optimization; robust decision and control; autonomous driving and robotics
Special Issue Information
Robotics and automation technologies have been widely leveraged in diverse domains such as agriculture, healthcare, and transportation, and they have had significant societal impacts and benefits. As robotics and automation technologies play a central role in leading the fourth industrial revolution, new trends in robotics and automation should be thoroughly investigated to enable their development in the long run. With the rapid development of emerging technologies such as artificial intelligence (AI), digital twins (DT), Internet of Things (IoT) and human-computer interaction (HCI), there must be a booming room for robotics and automation to be discussed. Therefore, this Special Issue is proposed here to provide a forum for researchers and practitioners to exchange their latest theoretical and engineering achievements. This special issue aims to compile the latest research and development advances in robotics and automation. The topics of interest within the scope of this special issue include (although not limited to) the following:
Intelligent control in robotics;
Intelligent connected vehicles;
Trustworthy artificial intelligence;
Artificial intelligence technology applied in intelligence system;
Modeling and control of human-machine system;
System state information acquisition and parameter identification;
Application of linear and nonlinear analysis and control;
Decision-making and control with multi-source information;
Decision-making and control for multi-agent system.
Prof. Dr. Jian Wu
Dr. Xiangkun He
Dr. Guangfei Xu
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. Machines 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 2000 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.
- new theories and studies in robotics
- advanced control strategies
- control decision-making with multi-source information
- artificial intelligence (AI) technology applied in vehicles
- system state information acquisition and parameter identification
- intelligent connected vehicles
- strategy and control of multi-agent cooperative operation
- application of linear nonlinear analysis and control
- modeling and control of human–machine cooperation