Hailong Huang, Andrey V. Savkin, Chao Huang

eBook, ePUB

Wireless Communication Networks Supported by Autonomous UAVs and Mobile Ground Robots (eBook, ePUB)

Beschreibung

Wireless Communication Networks Supported by Autonomous UAVs and Mobile Ground Robots covers wireless sensor networks and cellular networks. For wireless sensor networks, the book presents approaches using mobile robots or UAVs to collect sensory data from sensor nodes. For cellular networks, it discusses the approaches to using UAVs to work as aerial base stations to serve cellular users. In addition, the book covers the challenges involved in these two networks, existing approaches (e.g., how to use the public transportation vehicles to play the role of mobile sinks to collect sensory data from sensor nodes), and potential methods to address open questions.

• Gives a comprehensive understanding of the development of mobile robot-supported wireless communication approaches
• Provides the latest approaches of mobile robot-supported wireless communication, including scheduling approaches with multiple robots and the online and reactive navigation algorithm
• Covers interesting research scenarios that include the system model, problem statement, solution and results so that readers will be able to design their own system
• Presents unresolved research issues and future research directions

Technische Details

• Geräte: eReader
• ohne Kopierschutz

Autor

Dr. Hailong Huang received a B.Sc. degree in automation, from China University of Petroleum, Beijing, China, in June 2012, and received Ph.D degree in Systems and Control from the University of New South Wales, Sydney, Australia, in March 2018. From Feb. 2018 to July 2021, he worked as a postdoctoral research fellow at the School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, Australia. He is now an assistant professor at the Department of Aeronautical and Aviation Engineering, the Hong Kong Polytechnic University. His current research interests include the coordination, navigation and control of ground robots and unmanned aerial vehicles.Prof. Andrey V. Savkin received M.S. and Ph.D. degrees in mathematics from the Leningrad State University, Saint Petersburg, Russia, in 1987 and 1991, respectively. From 1987 to 1992, he was with the Television Research Institute, Leningrad, Russia. From 1992 to 1994, he held a Postdoctoral position in the Department of Electrical Engineering, Australian Defence Force Academy, Canberra. From 1994 to 1996, he was a Research Fellow in the Department of Electrical and Electronic Engineering and the Cooperative Research Centre for Sensor Signal and Information Processing, University of Melbourne, Australia. From 1996 to 2000, he was a Senior Lecturer, and then an Associate Professor in the Department of Electrical and Electronic Engineering, University of Western Australia, Perth. Since 2000, he has been a Professor in the School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia. His current research interests include robust control and state estimation, hybrid dynamical systems, guidance, navigation and control of mobile robots, applications of control and signal processing in biomedical engineering and medicine.Dr. Chao Huang received the B.Sc. degree in automation, from China University of Petroleum, Beijing, China, in June 2012, and received Ph.D degree from the University of Wollongong, Australia, in Dec. 2018. From Sep. 2018 to Sep. 2019, she worked as a project leader at National Institute of Informatics, Tokyo, Japan. From Oct. 2019 to July 2021, she worked as a postdoctoral research fellow at the School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore. She is now a research assistant professor at the Department of Industrial and Systems Engineering, the Hong Kong Polytechnic University, Hong Kong. Her interests include motion planning, human machine collaboration, fault tolerant, and automotive control and application.

Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 216
• Erscheinungstermin: 3. Januar 2022
• Englisch
• ISBN-13: 9780323901833
• Artikelnr.: 63249400