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Integrating Generative AI with UAVs for Autonomous Navigation and Decision Making

Submission Deadline: 31 July 2026 View: 1666 Submit to Special Issue

Guest Editor(s)

Assist. Prof. Inam Ullah

Email: inam@gachon.ac.kr

Affiliation: Department of Computer Engineering, Gachon University, Seongnam 13120, Republic of Korea

Homepage:

Research Interests: Artificial Intelligence (AI), Internet of Things (IoT), Robotics, Intelligent Robots, Internet of Vehicles (IoV), Autonomous Vehicles, UAVs, Drones, Intelligent Transportation Systems (ITS), Smart City, Wireless Sensor Networks (WSNs), Underwater Wireless Sensor Networks, Network Security, IoT Security, Data Privacy, Sensing & Monitoring, Computer Vision, Image Processing, Signal & Systems

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Dr. Hazrat Bilal

Email: hbilal@mail.ustc.edu.cn

Affiliation: School of Information Science and Technology, University of Science and Technology of China, Hefei 230026, China

Homepage:

Research Interests: Robotics, Artificial Intelligence, Autonomous Vehicles, IoRT, UAVs, etc


Summary

Unmanned Aerial Vehicles (UAVs) are at the forefront of modern technological innovations, with applications ranging from surveillance and agriculture to environmental monitoring and logistics. As UAVs become increasingly autonomous, the integration of advanced AI techniques is crucial for enhancing their capabilities. Generative AI, with its ability to create adaptive models and solve complex problems, is emerging as a game-changer in autonomous navigation and decision-making for UAV systems. The importance of this research lies in the potential of Generative AI to significantly improve the autonomy, adaptability, and efficiency of UAVs in dynamic environments, where traditional algorithms often struggle.

This special issue aims to explore the convergence of Generative AI and UAV technology, focusing on how generative models can be applied to improve UAV performance in real-time decision-making and autonomous navigation. The issue will highlight both the theoretical advancements in Generative AI and the practical implications of its integration into UAV systems. It will also address the challenges of real-time computation, data processing, and safety in autonomous UAV operations, particularly in environments with high uncertainty and dynamic changes.

Suggested Themes:
· Generative AI for UAV Path Planning and Navigation Optimization
· Autonomous Mission Planning and Decision Making in UAV Systems
· AI-Based Obstacle Detection and Collision Avoidance Algorithms
· Generative Models for UAV Behavior Prediction and Adaptation
· Real-time Data Processing and AI Techniques for UAVs
· Generative AI for UAV Swarm Systems and Cooperative Autonomy
· Ethical Considerations and Safety in AI-Driven UAV Operations
· AI-Powered UAVs in Dynamic Environments: Challenges and Opportunities


Keywords

Unmanned Aerial Vehicles (UAVs), Generative AI, Autonomous Navigation, Path Planning, Decision Making, Machine Learning, Reinforcement Learning, AI-Driven UAV Systems, Obstacle Avoidance, Mission Planning, UAV Autonomy, Generative Adversarial Networks (GANs), Environmental Adaptation, UAV Swarm Systems, Real-time Data Processing

Published Papers


  • Open Access

    ARTICLE

    Generative AI for Efficient and Secure Authentication in UAV-Enabled Smart City Transportation Systems

    Akmalbek Abdusalomov, Kudratjon Zohirov, Sojida Ochilova, Jakhongir Oramov, Zafar Ruziyev, Malika Rustamova, Gulrukh Sherboboyeva, Komil Tashev, Young Im Cho
    CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2026.081292
    (This article belongs to the Special Issue: Integrating Generative AI with UAVs for Autonomous Navigation and Decision Making)
    Abstract Unmanned aerial vehicles (UAVs) are also increasingly becoming more often in the transportation infrastructure of smart cities, so that they can successfully achieve real-time observation of traffic, emergency coordination, and two-way communication relaying. However, the security and privacy risks arising in open, highly mobile intelligent transportation systems (ITS) enabled by UAVs are critical, as they pose threats of impersonation, replay, Sybil, and tracking attacks. Secondly, standard static authentication mechanisms are unable to support dynamic risk environments and excessive resource consumption on UAV platforms with limited capacity. To address these challenges, this study introduces a Generative-AI-assisted… More >

  • Open Access

    ARTICLE

    Artificial Intelligence (AI)-Enabled Unmanned Aerial Vehicle (UAV) Systems for Optimizing User Connectivity in Sixth-Generation (6G) Ubiquitous Networks

    Zeeshan Ali Haider, Inam Ullah, Ahmad Abu Shareha, Rashid Nasimov, Sufyan Ali Memon
    CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-16, 2026, DOI:10.32604/cmc.2025.071042
    (This article belongs to the Special Issue: Integrating Generative AI with UAVs for Autonomous Navigation and Decision Making)
    Abstract The advent of sixth-generation (6G) networks introduces unprecedented challenges in achieving seamless connectivity, ultra-low latency, and efficient resource management in highly dynamic environments. Although fifth-generation (5G) networks transformed mobile broadband and machine-type communications at massive scales, their properties of scaling, interference management, and latency remain a limitation in dense high mobility settings. To overcome these limitations, artificial intelligence (AI) and unmanned aerial vehicles (UAVs) have emerged as potential solutions to develop versatile, dynamic, and energy-efficient communication systems. The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning (CoRL) to manage an autonomous network.… More >

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