• Produktbild: Unmanned Aerial Systems
  • Produktbild: Unmanned Aerial Systems

Unmanned Aerial Systems Theoretical Foundation and Applications

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

16.02.2021

Herausgeber

Anis Koubaa + weitere

Verlag

Elsevier Science & Technology

Seitenzahl

652

Maße (L/B/H)

22,9/15,2/3,3 cm

Gewicht

860 g

Sprache

Englisch

ISBN

978-0-12-820276-0

Beschreibung

Portrait

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.

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.

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

16.02.2021

Herausgeber

Verlag

Elsevier Science & Technology

Seitenzahl

652

Maße (L/B/H)

22,9/15,2/3,3 cm

Gewicht

860 g

Sprache

Englisch

ISBN

978-0-12-820276-0

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Zeitfracht Medien GmbH
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99095 Erfurt
DE
produktsicherheit@zeitfracht.de

Herstelleradresse

Elsevier Science & Technology
125 London Wall
EC2Y 5AS London
GB
tradeorders@elsevier.com

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  • Produktbild: Unmanned Aerial Systems
  • Produktbild: Unmanned Aerial Systems
  • 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