Advances in Collaborative Autonomy: Hybrid Multi-UAV/Robot Systems for Complex Environments

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: 15 September 2026 | Viewed by 168

Editor


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Guest Editor
Ocean College, Zhejiang University, Hangzhou, China
Interests: AUV; marine robotics; robotic control; artificial intelligence application, including autonomous computing of marine robots
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Special Issue Information

Dear Colleagues,

Multi-UAV (Unmanned Aerial Vehicle) systems and mobile robots represent a transformative frontier in autonomous systems, enabling complex tasks through coordination, collaboration, and distributed intelligence. These systems leverage advancements in robotics, artificial intelligence, and communication technologies to perform missions that are inefficient, dangerous, or impossible for single agents or humans. The convergence of multi-UAV systems with ground-based mobile robots further enhances operational scope, creating hybrid teams capable of addressing multi-domain challenges. However, key hurdles remain, including ensuring safety and regulatory compliance, managing energy autonomy, safeguarding against cybersecurity threats, and improving the systems' adaptability to unpredictable real-world conditions. Ongoing research aims to bridge these gaps, pushing toward fully autonomous, scalable, and trustworthy multi-robot systems that can seamlessly integrate into societal frameworks, ultimately augmenting human capabilities and operational efficiency across numerous sectors. Research in this domain focuses on several interconnected pillars: swarm intelligence and cooperative control, where decentralized algorithms enable emergent, resilient group behaviors; communication and networking, ensuring reliable, low-latency data exchange even in adversarial conditions; task planning and allocation, optimizing the distribution of objectives across a heterogeneous fleet; and human–swarm interaction, developing intuitive interfaces for supervisory control and collaborative tasking.

 The topics of interest include, but are not limited to the following:

  • Swarm intelligence and cooperative control.
  • Communication and networking.
  • Task planning, allocation, and optimization.
  • Human–swarm interaction.
  • AI-based cooperative control.
  • Heterogeneous robot swarms.
  • Efficient wireless swarm communication.
  • Cooperative navigation and position.
  • Fail-safe control circuit.
  • Fault-tolerant cooperative control.

Dr. Daxiong Ji
Guest Editor

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Keywords

  • modeling and identification
  • control based on trajectory planning/optimization
  • heterogeneous robot cluster system
  • multiple unmanned aerial systems
  • cross-domain robot cluster system collaborative control
  • control based on intelligent learning

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