Bio-inspired Computation in Unmanned Aerial Vehicles

Giving readers a rounded understanding of control-related problems in UAVs and presenting the latest advances in bio-inspired computation, this volume links theory, algorithms, and implementation procedures. It tracks results with academically sound graphics.

Bio-inspired Computation in Unmanned Aerial Vehicles focuses on the aspects of path planning, formation control, heterogeneous cooperative control and vision-based surveillance and navigation in Unmanned Aerial Vehicles (UAVs) from the perspective of bio-inspired computation. It helps readers to gain a comprehensive understanding of control-related problems in UAVs, presenting the latest advances in bio-inspired computation.

By combining bio-inspired computation and UAV control problems, key questions are explored in depth, and each piece is content-rich while remaining accessible. With abundant illustrations of simulation work, this book links theory, algorithms and implementation procedures, demonstrating the simulation results with graphics that are intuitive without sacrificing academic rigor. Further, it pays due attention to both the conceptual framework and the implementation procedures.

The book offers a valuable resource for scientists, researchers and graduate students in the field of Control, Aerospace Technology and Astronautics, especially those interested in artificial intelligence and Unmanned Aerial Vehicles.

Professor Haibin Duan and Dr. Pei Li, both work at Beihang University (formerly Beijing University of Aeronautics & Astronautics, BUAA). Prof Duan's academic website is: http://hbduan.buaa.edu.cn

The only book focused on the bio-inspired computation in UAVs Proposes the conceptual framework and the implementation procedures Investigates the challenging issues in multiple UAVs cooperation

Inhalt

Introduction.- Bio-inspired Computation Algorithms.- UAV Modeling and Controller Design.- UAV Path Planning.- Multiple UAVs Formation Control.- Multiple UAV/UGVs Heterogeneous Cooperative Control.- Biological Vision-based Surveillance and Navigation.- Conclusions and Outlook.