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Advances in Multi-Agent Systems: Cooperative and Intelligent Control Strategies for Complex Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 473

Special Issue Editor


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Guest Editor
School of Mathematics and Statistics, Xidian University, Xi’an 710126, China
Interests: intelligent control, cooperative control and their applications; stability of differential equations and their applications

Special Issue Information

Dear Colleagues,

Multi-agent systems (MASs) have become a key paradigm for solving complex problems in robotics, smart grids, transportation, and industrial automation. By combining the strengths of multiple autonomous agents, MASs provide scalable, adaptive, and robust solutions. This Special Issue focuses on advancements in cooperative and intelligent control strategies for MASs, covering topics such as distributed optimization, consensus algorithms, game-theoretic frameworks, and machine learning-based control. We invite original research, reviews, and case studies that explore theoretical foundations, practical implementations, and emerging trends in MASs. The goal is to showcase innovative approaches that improve coordination, communication, and decision-making in multi-agent systems, while addressing real-world challenges. Contributions to this Special Issue will highlight the potential of MASs to transform complex applications and inspire future research directions. 

Dr. Jiaxi Chen
Guest Editor

Manuscript Submission Information

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Keywords

  • multi-agent systems
  • cooperative control
  • intelligent control
  • distributed systems
  • autonomous agents

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Published Papers (1 paper)

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Research

18 pages, 1697 KiB  
Article
Multi-Robot System for Cooperative Tidying Up with Mobile Manipulators and Transport Agents
by Jae-Bong Yi, Shady Nasrat, Dongwoon Song, Joonyoung Kim and Seung-Joon Yi
Sensors 2025, 25(11), 3269; https://doi.org/10.3390/s25113269 - 22 May 2025
Viewed by 367
Abstract
This paper presents a system in which mobile manipulators and transport agents cooperate to solve a multi-agent pickup and delivery (MAPD) problem. The primary objective is to allocate appropriate tasks to heterogeneous robots by considering their capabilities and states. Unlike previous studies that [...] Read more.
This paper presents a system in which mobile manipulators and transport agents cooperate to solve a multi-agent pickup and delivery (MAPD) problem. The primary objective is to allocate appropriate tasks to heterogeneous robots by considering their capabilities and states. Unlike previous studies that focused on homogeneous teams or assigned distinct roles to heterogeneous robots, this work emphasizes synergy through cooperative task execution. A key feature of the proposed system is that mobile manipulators behave differently depending on whether they are paired with a transport agent. Additionally, rather than generating a full trajectory from start to end, the system plans partial trajectories, allowing dynamic re-pairing of transport agents through an auction algorithm. After re-pairing, new starting nodes are defined, and the following trajectory is updated accordingly. The proposed system is validated through simulations, and its effectiveness is demonstrated by comparing it against a baseline system without dynamic pairing. Full article
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