Recent Progress in Multi-Robot Systems

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".

Deadline for manuscript submissions: 3 July 2024 | Viewed by 1594

Special Issue Editors


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Guest Editor
Department of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL, UK
Interests: distributed control; robotic path planning; multi-agent systems; distributed learning
Special Issues, Collections and Topics in MDPI journals
Department of Computer Science, University College London, London WC1E 6BT, UK
Interests: model predictive control; reinforcement learning; aerial robotics; autonomous systems
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Engineering, University of Leicester, University Road, Leicester LE1 7RH, UK
Interests: distributed optimization; game theory; autonomous driving; control of multi-agent systems

Special Issue Information

Dear Colleagues,

Multi-robot systems have become an increasingly important area of research due to the growing demand for intelligent robots that can operate in complex environments. These systems consist of multiple robots that coordinate with each other to achieve a common goal. Recent advances in multi-robot systems have been driven by developments in sensing, communication, and control technologies, which have enabled robots to work together more efficiently and effectively. In particular, learning and control methods have played a critical role in enabling robots to operate autonomously and adaptively in dynamic and uncertain environments. This Special Issue aims to present state-of-the-art research in multi-robot systems, and to highlight the key challenges and opportunities in this field. We welcome both review papers and original research papers. Topics include, but are not limited to, the following:

  • Multi-robot cooperative control;
  • Distributed control and optimization in multi-agent systems;
  • Reinforcement learning and deep reinforcement learning for multi-robot systems;
  • Communication and sensing in multi-robot systems;
  • Multi-robot perception and sensor fusion;
  • Swarms and swarm intelligence;
  • Human-robot interaction in multi-robot systems;
  • Applications of multi-agent systems, including search and rescue, environmental monitoring, transportation, manufacturing, smart cities and energy systems, etc.

Dr. Zhongguo Li
Dr. Yunda Yan
Dr. Xuefang Wang
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 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 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

  • multi-agent system
  • distributed control
  • learning-based control
  • autonomous systems
  • swarm robotics
  • cyber-physical systems

Published Papers (1 paper)

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Research

13 pages, 7600 KiB  
Communication
An Improved Super-Twisting Sliding Mode Composite Control for Quadcopter UAV Formation
by Yulong Ye, Song Hu, Xingyu Zhu and Zhenxing Sun
Machines 2024, 12(1), 32; https://doi.org/10.3390/machines12010032 - 3 Jan 2024
Viewed by 982
Abstract
Aiming at the nonlinear and multiple disturbances in the multi-quadcopter UAV system, this paper proposes a leader–follower composite formation control strategy based on an improved super-twisted sliding mode controller (ISTSMC) and a finite-time extended state observer (FTESO). For the designed sliding mode control [...] Read more.
Aiming at the nonlinear and multiple disturbances in the multi-quadcopter UAV system, this paper proposes a leader–follower composite formation control strategy based on an improved super-twisted sliding mode controller (ISTSMC) and a finite-time extended state observer (FTESO). For the designed sliding mode control algorithm, the integral term’s switching function is replaced with a non-smooth term to reduce the vibration in the control, further improving the overall performance of the system. For external disturbances, the finite-time extended state observer achieves rapid and accurate observation of external disturbances. Finally, through formation control experiments, the reliability and superiority of the proposed composite formation controller (CFC) is validated. Full article
(This article belongs to the Special Issue Recent Progress in Multi-Robot Systems)
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