This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space.

This book presents the basic tools required to obtain the dynamical models for aerial vehicles (in the Newtonian or Lagrangian approach). Several control laws are presented for mini-helicopters, quadrotors, mini-blimps, flapping-wing aerial vehicles, planes, etc. Finally, this book has two chapters devoted to embedded control systems and Kalman filters applied for aerial vehicles control and navigation. This book presents the state of the art in the area of UAVs. The aerodynamical models of different configurations are presented in detail as well as the control strategies which are validated in experimental platforms.

Unmanned aerial vehicles (UAVs) and artificial intelligence (AI) are gaining the attention of academic and industrial researchers due to the freedoms that UAVs afford when operating and monitoring activities remotely. Applying machine learning and deep learning techniques can result in fast and reliable outputs and have helped in real-time monitoring, data collection and processing, and prediction. UAVs utilizing these techniques can become instrumental tools for computer/wireless networks, smart cities, military applications, agricultural sectors, and mining. Unmanned Aerial Vehicles and Multidisciplinary Applications Using AI Techniques is an essential reference source that covers pattern recognition, machine and deep learning-based methods, and other AI techniques and the impact they have when applied to different real-time applications of UAVs. It synthesizes the scope and importance of machine learning and deep learning models in enhancing UAV capabilities, solutions to problems, and numerous application areas. Covering topics such as vehicular surveillance systems, yield prediction, and human activity recognition, this premier reference source is a comprehensive resource for computer scientists; AI engineers; data scientists; agriculturalists; government officials; military leaders; business managers and leaders; students and faculty of higher education; academic libraries; academicians; and researchers in computer science, computer vision, pattern recognition, imaging, and engineering.

This book addresses the major challenges in realizing unmanned aerial vehicles (UAVs) in IoT-based Smart Cities. The challenges tackled vary from cost and energy efficiency to availability and service quality. The aim of this book is to focus on both the design and implementation aspects of the UAV-based approaches in IoT-enabled smart cities’ applications that are enabled and supported by wireless sensor networks, 5G, and beyond. The contributors mainly focus on data delivery approaches and their performability aspects. This book is meant for readers of varying disciplines who are interested in implementing the smart planet/environments vision via wireless/wired enabling technologies. Involves the most up to date unmanned aerial vehicles (UAV) assessment and evaluation approaches Includes innovative operational ideas in agriculture, surveillance, rescue, etc. Pertains researchers, scientists, engineers and practitioners in the field of smart cities, IoT, and communications Fadi Al-Turjman received his Ph.D. from Queen’s University, Canada. He is a full professor and a research center director at Near East University, Nicosia. He is a leading authority in the area of IoT and intelligent systems. His publication history spans over 250 publications in addition to his editorialship in top journals such as the IEEE Communication Surveys and Tutorials, and the Elsevier Sustaibable Cities and Society.

Written by an expert with more than 30 years of experience, Guidance of Unmanned Aerial Vehicles contains new analytical results, taken from the author's research, which can be used for analysis and design of unmanned aerial vehicles guidance and control systems. This book progresses from a clear elucidation of guidance laws and unmanned aerial veh

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

Many industries have begun to recognize the potential support that unmanned aerial vehicles (UAVs) offer, and this is no less true for the commercial sector. Current research on this field is narrowly focused on technological development to improve the functionality of delivery and endurance of the drone delivery in logistics, as well as on regulatory challenges posed by such operations. There is a need for further attention to be applied to operational and integration challenges associated with UAVs. Unmanned Aerial Vehicles in Civilian Logistics and Supply Chain Management is a collection of innovative research that investigates the opportunities and challenges for the use of UAVs in logistics and supply chain management with a specific aim to focus on the multifaceted impact of drone delivery. While highlighting topics including non-military operations, public management, and safety culture, this book is ideally designed for government administrators, managers, industry professionals, researchers, and students.

This book provides a complete overview of the theory, design, and applications of unmanned aerial vehicles. It covers the basics, including definitions, attributes, manned vs. unmanned, design considerations, life cycle costs, architecture, components, air vehicle, payload, communications, data link, and ground control stations. Chapters cover types and civilian roles, sensors and characteristics, alternative power, communications and data links, conceptual design, human machine interface, sense and avoid systems, civil airspace issues and integration efforts, navigation, autonomous control, swarming, and future capabilities.

"As a companion piece to Volume 133 of this series, this volume extends our discussion of the use of unmanned aerial vehicles, commonly referred to as drones, by the U.S. government. While the previous volume focused on the use of drone attacks to protect American interests and the American people from threats emanating from abroad, this volume addresses domestic uses of drones"--