Cao / Chen / Gao | Robotic Swarming Control via Voronoi Tessellations | Buch | 978-1-041-19913-7 | www.sack.de

Buch, Englisch, 288 Seiten, Format (B × H): 178 mm x 254 mm

Cao / Chen / Gao

Robotic Swarming Control via Voronoi Tessellations

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

Foundations and Applications

Buch, Englisch, 288 Seiten, Format (B × H): 178 mm x 254 mm

ISBN: 978-1-041-19913-7
Verlag: Taylor & Francis Ltd


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, the book 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.

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Zielgruppe


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

Weitere Infos & Material


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


Kai Cao, an Associate Professor at Xi’an Technological University. Deputy Director of the "International Joint Research Center for Autonomous Systems and Intelligent Control" in Shaanxi Province, China. 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 Director of Shaanxi Provincial Automation Society. The current research focuses on intelligent control, fault diagnosis and fault tolerance control.

Song Gao is currently a professor at Xi'an Technological University. His research interests are autonomous intelligent unmanned systems, robot multi-mode intelligent inspection, automation control and grid-connected inverter technology.

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



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