Guest Editors
Prof. Jin Yi, Chongqing University, Chongqing, China
Prof. Wenying Xu, Southeast University, Nanjing, China
Prof. Dengyu Xiao, Chongqing University, Chongqing, China
Summary
Swarms of unmanned systems, such as drones, mobile robots and unmanned surface vessels, have the potential to revolutionize various industries, including search and rescue, agriculture, surveillance, and transportation. The collective behavior of these systems can help accomplish complex tasks that are otherwise impossible for a single unit. However, managing and controlling swarms of unmanned systems is a challenging task due to their decentralized nature.
Intelligent algorithms have shown great promise in improving the performance of swarms of unmanned systems by enabling them to operate autonomously with high efficiency, scalability, and adaptability. These algorithms use decision-making techniques based on machine learning, optimization, and game theory to coordinate the actions of individual units within a swarm.
This special issue aims to bring together researchers and practitioners from academia and industry to share their latest research findings and practical applications related to intelligent algorithms in swarms of unmanned systems. Original research, review, and application papers are both welcome.
Keywords
Swarm formation and control;
Multi-agent coordination and communication;
Task assignment and scheduling;
Resource management and allocation;
Path planning and navigation;
Distributed sensing and perception;
Autonomous decision-making and learning;
Adaptive control and fault diagnosis of unmanned systems.
Published Papers
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