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…mehr
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.
Produktdetails
Produktdetails
Advances in Nonlinear Dynamical Systems and Robotics (ANDC)
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Autorenporträt
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 committee
s 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.
Inhaltsangabe
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
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
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