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      Unmanned Aerial Systems

      Theoretical Foundation and Applications

      AvAnis Koubaa,Ahmad Taher Azar

      Häftad, Engelska, 2021

      Del i serien Advances in Nonlinear Dynamical Systems and Roboticss (ANDC)

      1 540 kr

      Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

      Beskrivning

      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.



      • Covers some of the most innovative approaches to drones
      • Provides the latest state-of-the-art research and development surrounding unmanned aerial systems
      • Presents a comprehensive reference on unmanned aerial systems, with a focus on cutting-edge technologies and recent research trends in the area

      Produktinformation

      • Utgivningsdatum:2021-01-26
      • Mått:152 x 229 x 34 mm
      • Vikt:1 040 g
      • Format:Häftad
      • Språk:Engelska
      • Serie:Advances in Nonlinear Dynamical Systems and Roboticss (ANDC)
      • Antal sidor:650
      • Förlag:Elsevier Science
      • ISBN:9780128202760

      Utforska kategorier

      • Elektronik och kommunikationer inom Naturvetenskap och teknik
      • Flyg- och rymdteknik inom Naturvetenskap och teknik
      • Maskinteknik och material inom Naturvetenskap och teknik

      Mer om författaren

      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. Prof. Ahmad Azar is a full Professor at Prince Sultan University, Riyadh, Kingdom Saudi Arabia. He is the leader of Automated Systems and Computing Lab (ASCL), Prince Sultan University, Saudi Arabia.Prof. Azar is the Editor in Chief of the International Journal of Intelligent Engineering Informatics (IJIEI), Inderscience Publishers, Olney, UK. He is also the Editor in Chief of International Journal of Service Science, Management, Engineering, and Technology (IJSSMET) and International Journal of Sociotechnology and Knowledge Development (IJSKD) published by IGI Global, USA. From 2013 to 2017, Prof. Azar was an associate editor of ISA Transactions, Elsevier.He is currently an editor for IEEE Transactions on Fuzzy Systems, IEEE Systems Journal, IEEE Transactions on Neural Networks and Learning Systems, Springer's Human-centric Computing and Information Sciences.Prof. Azar specializes in artificial intelligence (AI), robotics, machine learning, control theory and applications, computational intelligence, reinforcement learning, and dynamic system modeling. He has published or co-published over 550 research papers, book chapters, and conference proceedings in prestigious peer-reviewed journals.Dr. Ahmad Azar has received several awards, including the Benha University Prize for Scientific Excellence (2015, 2016, 2017, and 2018) and the Benha University Highest Citation Award (2015, 2016, 2017, and 2018). In June 2018, he was awarded the Egyptian State Encouragement Award in Engineering Sciences by the Ministry of Higher Education and Scientific Research. In August 2018, he was elected as a senior member of the International Rough Set Society (IRSS).Prof. Azar was named one of the top computer scientists in Saudi Arabia by Research.com since December 2019. He was awarded the Egyptian President's Distinguished Egyptian Order of the First Class in February 2020. In October 2020, Prof. Azar received Abdul Hameed Shoman Arab Researchers Award in Machine Learning and Big Data Analytics. From October 2020 to September 2023, Prof. Azar was recognized as a Distinguished researcher at Prince Sultan University, Riyadh, Saudi Arabia.In November 2020, October 2021, October 2022, October 2023, September 2024, and September 2025 Prof. Azar was named one of the top 2% of scientists in the world in Artificial Intelligence by Stanford University, based on single-year impact and career-long impact. These rankings were published by Stanford University in the PLOS journal and were based on the SCOPUS database.Prof. Ahmad Azar has been recognized as one of the top ten researchers at Prince Sultan University, based on his Scopus H-index. He has also received a university award for being among his top publication of research.Prof. Azar has received Prince Sultan University’s Research Excellence Award. He is also the recipient of the university’s Highest Impact Researcher Award, based on his H-index. Additionally, he has earned a PSU research award for having publications ranked among the top five by impact factor.Prof. Ahmad Azar is the Vice Chair of the International Federation of Automatic Control (IFAC) Technical Committee of Control Design, Vice chair of IFAC Technical committee 4.3 Robotics, Vice chair of IFAC Technical committee 9.3 “Control for Smart Cities”. He is a technical Committee Member of Data Mining and Big Data Analytics of IEEE Computational Intelligence Society (CIS), IFAC Technical committee Member TC 2.2. Linear Control Systems, IFAC Technical committee Member TC 1.2. Adaptive and Learning Systems.

      Innehållsförteckning

      • 1. UAS System Design2. UAS Control systems3. Hybrid control of UAS4. Obstacle and collision avoidance of UAS5. UAV onboard data storage, transmission and retrieval6. Kalman and Particle filtering and other advanced techniques for motion sensor data fusion7. Simultaneous Localization and Mapping (SLAM)8. Single/multiple IMU–Vision-based navigation and orientation9. Autopilots and navigation: standard and advanced solutions for navigation integrity10. Integration of UAS into the Internet11. IoT applications using UAS12. Safety issues of UAS13. Ultra-Wide Band (UWB) localization14. Security threats of UAS15. UAS public deployment challenges16. UAS for cloud robotics17. 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 vehicles19. Deep-reinforcement learning for aerial robots (discrete-, or continuous-control) in dynamic environments20. Learning-based aerial manipulation in cluttered environments21. Decision making or task planning using machine learning for field aerial robots22. Long-term ecological monitoring based on UAVs23. Ecological Integrity parameters mapping24. Rapid risk and disturbance assessment using drones25. Ecosystem structure and processes assessment by using UAVs
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