IRSCN workshop

International workshop on Intelligent Robot Swarm Communication Networks (IRSCN)

To be held at EAI ROSENET 2021
Shezhen, People’s Republic of China

Workshop Chairs

Bo Zhang, National Innovation Institute of Defense Technology, China
Chen Dong, Beijing University of Posts and Telecommunications, China
Changhao Du, Beijing Institute of Technology, China
Shida Zhong, Shenzhen University, China
Jiankang Zhang, Bournemouth University, United Kingdom


Artificial intelligence (AI)-enabled robot swarm system is one of the hottest topics both in robotics and in AI, and exciting progress is being achieved.  As the key enablers in intelligent robot swarms, communication and networking are acting as crucial roles.

However, there are many challenges and problems that are yet to be solved in developing real-world applications of wireless connected robots that functions reliably and robustly, such as co-working delivery robots in dense environments, collaborations of robots in post-disaster search and rescue missions, etc. Intelligent robot swarms are demanding joint efforts both from the robotic society and from communications society in order to enable robots to manage the wireless spectrum resources and highly-networked intelligent behaviours for achieving full potential intelligence.

In order to address these problems, research contributions concerning the analysis, modelling, simulations and field experiments are welcomed, as well as contributions that can fill the gap from theoretical contributions on intelligent swarms to practical demonstrations and applications.


Particular topics of interest include:

  • Channel modelling and simulation for wireless connected robot swarms
  • Cognitive PHY and MAC protocol design for wireless connected robot swarms
  • Ad hoc networking for wireless connected robot swarms
  • Decentralized control and distributed protocol design for wireless connected robot swarms
  • Data-driven optimization for robot swarm communication networks
  • Joint design of wireless communications and autonomous robot behaviours.
  • Machine learning, deep learning and reinforcement learning for intelligent robot swarms
  • Underwater robotic swarm communications and networking design
  • Distributed sensing and precise mapping in wireless-connected robot swarms
  • UAV Control, formation and navigation in wireless-connected robot swarms
  • Swarm intelligence in wireless-connected robot swarms
  • Cooperative robotic swarms for Internet-of-Things ecosystems
  • Testbeds and experimental evaluations for communications and networking in wireless-connected robot swarms
  • Field demonstrations and applications of aerial, ground and underwater robotic swarms

Submit paper to this workshop

Important dates

Paper submission: 9 September (extended!)

Notification deadline: 30 September 2021

Camera Ready: 18 October 2021

Accepted and presented technical papers will be submitted for publication by Springer and made available through SpringerLink Digital Library. Workshop Papers will be published as a part of the (EAI ROSENET 2021) Conference Proceedings. Proceedings will be submitted for inclusion in leading indexing services, including Ei Compendex, ISI Web of Science, Scopus, CrossRef, Google Scholar, DBLP, as well as EAI’s own EU Digital Library (EUDL).

We invite workshop participation through contributions that respond to one or more of the mentioned research questions in 6-11 pages for a short papers or 12-15 for a regular papers. Papers should be submitted through EAI ‘Confy+‘ system, and have to comply with the Springer format (see Author’s kit section).

Technical Program Committee of the Workshop

Shuangzhi Li, Zhengzhou University, China
Halil Yetgin, Bitlis Eren University, Turkey
Chao Xu, University of Southampton, UK
Guanglong Du, South China University of Technology, China
Xinying Guo, Henan University of Technology, China
Dandan Liang, Peng Cheng Laboratory, China
Hongming Zhang, Beijing University of Posts and Telecommunications, China 
Hongyan Wang, Zhejiang Sci-Tech University, China