Artificial Intelligence for Unmanned Aerial Vehicles: Sensing, Communication, and Computing

Artificial Intelligence for Unmanned Aerial Vehicles: Sensing, Communication, and Computing book cover

Artificial Intelligence for Unmanned Aerial Vehicles: Sensing, Communication, and Computing

Author(s): Shuyan Hu (Author), Xin Yuan (Author), Kai Li (Author), Wei Ni (Author), Xin Wang (Author)

  • Publisher: Wiley-IEEE Press
  • Publication Date: 13 Jan. 2026
  • Edition: 1st
  • Language: English
  • Print length: 416 pages
  • ISBN-10: 139436945X
  • ISBN-13: 9781394369454

Book Description

In-depth exploration of machine learning techniques applied to UAV operations and communications, highlighting areas of potential growth and research gaps

Artificial Intelligence for Unmanned Aerial Vehicles provides a comprehensive overview of machine learning (ML) techniques used in unmanned aerial vehicle (UAV) operations, communications, sensing, and computing. It emphasizes key components of UAV activity to which ML can significantly contribute including perception and feature extraction, feature interpretation and regeneration, trajectory and mission planning, and aerodynamic control and operation.

The book considers the notion of security in the UAV network primarily in terms of its underlying rationale. This book also includes a detailed analysis of UAV behavior with respect to time and explores online machine learning-based solutions for UAV-assisted IoT networks.

Additional topics include:

  • Joint cruise control and data collection
  • Resilience in an AI-aided UAV network against multiple attacks, introducing a flexible and adaptive threshold to alleviate malicious conduct
  • Quantification of influencing attributes, quantification of weights affiliated with these attributes, and movement tracking of malicious UAVs
  • Integration of contextual information, threshold definitions, and time-variant behavior analysis

Artificial Intelligence for Unmanned Aerial Vehicles is an essential up-to-date reference on the subject for researchers, professors, graduate and senior undergraduate students, and industry professionals in the field.

Editorial Reviews

From the Back Cover

In-depth exploration of machine learning techniques applied to UAV operations and communications, highlighting areas of potential growth and research gaps

Artificial Intelligence for Unmanned Aerial Vehicles provides a comprehensive overview of machine learning (ML) techniques used in unmanned aerial vehicle (UAV) operations, communications, sensing, and computing. It emphasizes key components of UAV activity to which ML can significantly contribute including perception and feature extraction, feature interpretation and regeneration, trajectory and mission planning, and aerodynamic control and operation.

The book considers the notion of security in the UAV network primarily in terms of its underlying rationale. This book also includes a detailed analysis of UAV behavior with respect to time and explores online machine learning-based solutions for UAV-assisted IoT networks.

Additional topics include:

  • Joint cruise control and data collection
  • Resilience in an AI-aided UAV network against multiple attacks, introducing a flexible and adaptive threshold to alleviate malicious conduct
  • Quantification of influencing attributes, quantification of weights affiliated with these attributes, and movement tracking of malicious UAVs
  • Integration of contextual information, threshold definitions, and time-variant behavior analysis

Artificial Intelligence for Unmanned Aerial Vehicles is an essential up-to-date reference on the subject for researchers, professors, graduate and senior undergraduate students, and industry professionals in the field.

About the Author

SHUYAN HU, PHD, is an Associate Professor with the College of Electronics and Information Engineering at Tongji University, Shanghai, China.

XIN YUAN, PHD, is a Senior Research Scientist at CSIRO and an Adjunct Senior Lecturer at the University of New South Wales, Sydney, NSW, Australia.

KAI LI, PHD, serves as a Visiting Research Scientist with the School of Electrical Engineering and Computer Science, TU Berlin, Germany, and is also a Senior Research Scientist with Real-Time and Embedded Computing Systems Research Centre (CISTER), Porto, Portugal.

WEI NI, PHD, is a Senior Principal Research Scientist at CSIRO and a Conjoint Professor at the University of New South Wales, Sydney, NSW, Australia.

XIN WANG, PHD, is a Professor with the College of Future Information Technology at Fudan University, Shanghai, China.

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