Robotic Swarming Control via Voronoi Tessellations

Foundations and Applications
1. Auflage 2026
ISBN: 978-1-041-19913-7
Verlag: Taylor & Francis Ltd

Buch, Englisch, 297 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 735 g

With the help of a Voronoi diagram, this book systematically discusses how to solve the core cooperative control problem in a multi-robot system. From basic theory to cutting-edge applications, Robotic Swarming Control via Voronoi Tessellations: Foundations and Applications provides a comprehensive overview of the subject matter, offering readers a rigorous and practical knowledge system.

Central to this book's contribution is its transformation of centroidal Voronoi tessellations (CVT) theory into innovative multi-robot control algorithms. The effectiveness and superiority of these algorithms are verified through numerous simulations and real-environment experiments. The book demonstrates the deep integration of mathematical geometry and robotics, offering universal solutions for swarm intelligence in complex environments. It serves as an authoritative guide, bridging the gap between theoretical geometry and robotics engineering practice.

This book will be invaluable to scholars and students of robotics, automation, control engineering, and computer science.

Zielgruppe

Academic, Postgraduate, Professional Practice & Development, Undergraduate Advanced, and Undergraduate Core

Autoren/Hrsg.

Cao, Kai

Chen, ChaoBo

Gao, Song

Chen, YangQuan

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik

Inhaltsverzeichnis

1. Introduction 2. Geometric Properties and Computational Methods 3. Multi-Robot Cooperation and Formation 4. Multi-Robot Formation Switching 5. Multi-Robot Safety and Collision Avoidance 6. Multi-Robot Source Search and Coverage Control 7. Multi-Robot System Optimization and Health Management 8. Multi-Robot Capture 9. Reinforcement Learning and Multi-Robot Capture 10. Multi-Robot Physical Implementation 11. Conclusions and Future Prospects

Über Autor(innen)

Kai Cao is an associate professor at Xi’an Technological University and deputy director of the International Joint Research Center for Autonomous Systems and Intelligent Control in Shaanxi Province, China. His main research directions include multi-agent systems, multi-robot formation control and source localization, and collaborative multispectral remote sensing based on small drones.

ChaoBo Chen is a professor at Xi’an Technological University. He is currently the dean of the School of Electronic Information Engineering of Xi’an Technological University and the council member and deputy secretary-general of Shaanxi Provincial Automation Society. His current research focuses on intelligent control, fault diagnosis, and fault tolerance control.

Song Gao is a professor at Xi’an Technological University. Director of the International Joint Research Center for Autonomous Systems and Intelligent Control in Shaanxi Province, his research interests include autonomous intelligent unmanned systems, robot multi-mode intelligent inspection, automation control, and grid-connected inverter technology.

YangQuan Chen, a Clarivate Highly Cited Researcher, is a professor in the Department of Mechanical and Aerospace Engineering, School of Engineering, University of California, Merced. His research interests include mechatronics, smart control engineering via digital twins, and applied fractional calculus in STEM.