Unmanned Aerial Systems
Theoretical Foundation and Applications
Published on 26. January 2021
Book
Paperback/Softback
650 pages
978-0-12-820276-0 (ISBN)
Description
Unmanned Aerial Systems: Theoretical Foundation and Applications presents some of the latest innovative approaches to drones from the point-of-view of dynamic modeling, system analysis, optimization, control, communications, 3D-mapping, search and rescue, surveillance, farmland and construction monitoring, and more. With the emergence of low-cost UAS, a vast array of research works in academia and products in the industrial sectors have evolved. The book covers the safe operation of UAS, including, but not limited to, fundamental design, mission and path planning, control theory, computer vision, artificial intelligence, applications requirements, and more.
This book provides a unique reference of the state-of-the-art research and development of unmanned aerial systems, making it an essential resource for researchers, instructors and practitioners.
This book provides a unique reference of the state-of-the-art research and development of unmanned aerial systems, making it an essential resource for researchers, instructors and practitioners.
More details
Series
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
Professional and scholarly
Researches and Industries working in the fields of Electrical and Electronics Engineering; Control Engineering, Power Engineering, Computer science, Mathematics and Applied Mathematics, Physics, Computer Engineering.
Mathematicians, Engineering Mathematics, Biomedical Engineering, Computational Physics
Product notice
Paperback (trade)
Illustrations
Approx. 200 illustrations
Dimensions
Height: 229 mm
Width: 152 mm
Thickness: 33 mm
Weight
860 gr
ISBN-13
978-0-12-820276-0 (9780128202760)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
E-Book
01/2021
Academic Press
€140.00
Available for download
Persons
Anis Koubaa is a Professor in Computer Science, Advisor to the Rector, and Leader of the Robotics and Internet of Things Research Lab, in Prince Sultan University. He is also R&D Consultant at Gaitech Robotics in China and Senior Researcher in CISTER/INESC TEC and ISEP-IPP, Porto, Portugal. He has been the Chair of the ACM Chapter in Saudi Arabia since 2014. He is also a Senior Fellow of the Higher Education Academy (HEA) in UK. He received several distinctions and awards including the Rector Research Award in 2010 at Al-Imam Mohamed bin Saud University, and the Rector Teaching Award in 2016 at Prince Sultan University. He is the Editor in Chief of the Robotics Software Engineering topic of the International Journal of Advanced Robotics Systems, Associate Editor in the Cyber-Physical Journal (Taylor & Francis). He is also the authors of six books with Springer on robots, sensor networks and Robot Operating Systems (ROS). He has been also actively participating in program committees of several international conferences including, ACM/IEEE International Conference on Cyber-Physical Systems, International Conference on Robotics Computing, European Conference on Wireless Sensor Networks, IEEE International Conference on Autonomous Robot Systems and Competitions, IEEE International Workshop on Factory Communication Systems. He is the author of more than 200 journal and conference publications, and one patent. He received several research grants as principal investigator, and he established research collaboration between Prince Sultan University and Gaitech Robotics for the development of robots and drones, and ROS. Ahmad Azar is a Research Associate Professor at the Prince Sultan University, Riyadh, Kingdom Saudi Arabia. He is also an associate professor at the Faculty of Computers and Artificial intelligence, in Benha University, Egypt. He is the Editor in Chief of the International Journal of System Dynamics Applications (IJSDA), International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), and International Journal of Intelligent Engineering Informatics (IJIEI), among others. He is currently Associate Editor of ISA Transactions, Elsevier, and the IEEE systems journal. Dr. Azar works in the areas of control theory & applications, process control, chaos control and synchronization, nonlinear control, renewable energy, computational intelligence.
Editor
Professor in Computer Science, Advisor to the Rector, and Leader of the Robotics and Internet of Things Research Lab, Prince Sultan University, Saudi Arabia
Research Associate Professor, Prince Sultan University, Riyadh, Kingdom Saudi Arabia; Associate Professor, Faculty of Computers and Artificial intelligence, Benha University, Egypt
Content
1. UAS System Design
2. UAS Control systems
3. Hybrid control of UAS
4. Obstacle and collision avoidance of UAS
5. UAV onboard data storage, transmission and retrieval
6. Kalman and Particle filtering and other advanced techniques for motion sensor data fusion
7. Simultaneous Localization and Mapping (SLAM)
8. Single/multiple IMU-Vision-based navigation and orientation
9. Autopilots and navigation: standard and advanced solutions for navigation integrity
10. Integration of UAS into the Internet
11. IoT applications using UAS
12. Safety issues of UAS
13. Ultra-Wide Band (UWB) localization
14. Security threats of UAS
15. UAS public deployment challenges
16. UAS for cloud robotics
17. Deep neural networks (DNN) for field aerial robot perception (e.g., object detection, or semantic classification for navigation)
18. Recurrent networks for state estimation and dynamic identification of aerial vehicles
19. Deep-reinforcement learning for aerial robots (discrete-, or continuous-control) in dynamic environments
20. Learning-based aerial manipulation in cluttered environments
21. Decision making or task planning using machine learning for field aerial robots
22. Long-term ecological monitoring based on UAVs
23. Ecological Integrity parameters mapping
24. Rapid risk and disturbance assessment using drones
25. Ecosystem structure and processes assessment by using UAVs
2. UAS Control systems
3. Hybrid control of UAS
4. Obstacle and collision avoidance of UAS
5. UAV onboard data storage, transmission and retrieval
6. Kalman and Particle filtering and other advanced techniques for motion sensor data fusion
7. Simultaneous Localization and Mapping (SLAM)
8. Single/multiple IMU-Vision-based navigation and orientation
9. Autopilots and navigation: standard and advanced solutions for navigation integrity
10. Integration of UAS into the Internet
11. IoT applications using UAS
12. Safety issues of UAS
13. Ultra-Wide Band (UWB) localization
14. Security threats of UAS
15. UAS public deployment challenges
16. UAS for cloud robotics
17. Deep neural networks (DNN) for field aerial robot perception (e.g., object detection, or semantic classification for navigation)
18. Recurrent networks for state estimation and dynamic identification of aerial vehicles
19. Deep-reinforcement learning for aerial robots (discrete-, or continuous-control) in dynamic environments
20. Learning-based aerial manipulation in cluttered environments
21. Decision making or task planning using machine learning for field aerial robots
22. Long-term ecological monitoring based on UAVs
23. Ecological Integrity parameters mapping
24. Rapid risk and disturbance assessment using drones
25. Ecosystem structure and processes assessment by using UAVs