Advances in AI Large Models for Unmanned Aerial Vehicles

Dear Colleagues,

Integrating artificial intelligence (AI) large models with unmanned aerial vehicles (UAVs) introduces a transformative model for intelligent low-altitude services, where autonomous drone networks play a pivotal role. This advancement is crucial for the emerging low-altitude economy, optimizing real-time decision-making, reducing latency, and enhancing operational efficiency in sectors such as logistics, surveillance, and disaster response. AI large models strengthen UAV operations by enabling sophisticated natural language processing, allowing UAVs to interpret commands, navigate complex environments, and interact dynamically with users. This combination creates a flexible platform capable of advanced data analysis, situational awareness, and autonomous functionalities, all essential for the future of low-altitude applications. Nonetheless, challenges such as energy efficiency, secure UAV coordination, and data protection still need to be addressed. As 6G networks progress, integrating AI large models with UAV swarms will significantly enhance low-altitude economic activities by fostering efficient, secure, and context-aware drone services, revolutionizing industries that rely on autonomous aerial operations.

This Special Issue will gather pioneering research on integrating AI large models and UAVs, aiming to explore their synergies and advance the development of intelligent, autonomous, and low-latency aerial services in next-generation networks. Topics of interest include, but are not limited to, the following:

• AI large models for UAV sensor networks;
• AI large models for real-time information processing for UAVs;
• AI large models for UAV localization and navigation;
• AI large models for UAV perception model;
• AI large models for UAV obstacles and collision avoidance;
• AI large models for UAV trajectory generation and motion planning;
• AI large models for UAV cooperative sensing;
• AI large models for UAV sensor fusion;
• AI large models for UAV threat analysis;
• Transparent decision-making UAV swarm driven by AI large models;
• Testbed, benchmark, and simulation studies in UAV network powered by AI large models;
• Security and privacy challenges and potential resolutions in UAV networks supported by AI large models;
• Security architecture for UAV systems with AI large models;
• Interpretability of AI large models over UAVs.

Dr. Jie Zeng
Prof. Dr. Tiejun Lv
Prof. Dr. Xin Su
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• AI large models
• UAV network
• navigation
• sensor fusion
• UAV swarm
• cooperative sensing