Air–Ground Integrated Perception and Cooperative Control for UAVs and UGVs

Dear Colleagues,

We are pleased to invite you to submit contributions to the Special Issue entitled “Air–Ground Integrated Perception and Cooperative Control for UAVs and UGVs” in Drones.

With the rapid development of intelligent transportation and autonomous systems, unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) have become key platforms for perception, monitoring, and cooperative control. UAVs provide flexible, wide-area, and long-range sensing and delivery capabilities, whereas UGVs enable accurate ground-level interaction and autonomous task execution. Emerging applications increasingly involve multi-UGV cooperative control and UAV-based long-range perception and delivery, which introduce new challenges in coordination, scalability, and system robustness.

The increasing complexity of real-world applications, such as urban traffic management and emergency response, highlights the need for integrated air–ground perception, cooperative control, and effective coordination among multiple UGVs, as well as robust UAV-based sensing and delivery control. Despite recent advances in artificial intelligence and communication technologies, significant challenges remain in scalable multi-agent coordination, communication-aware control, cross-modal perception consistency, and especially in air–ground collaboration.

The aim of this Special Issue is to bring together high-quality research that advances theories, algorithms, and applications related to Air–Ground Integrated Perception and Cooperative Control for UAVs and UGVs. It also encompasses multi-UGV cooperative control and UAV-enabled perception and delivery within unified autonomous system frameworks.

This Special Issue seeks contributions addressing the following themes, including but not limited to:

• UAV aerial perception and delivery control;
• UGV motion planning and multi-vehicle cooperative control;
• Air–ground integrated perception and information fusion;
• Cooperative control of heterogeneous UAV–UGV systems;
• Communication-aware perception and control in unmanned autonomous Systems;
• Edge–cloud intelligence for UAV–UGV collaborative systems;
• Foundation models and large-scale simulation for air–ground intelligence.

We look forward to receiving your original research articles and reviews.

Dr. Shunchao Wang
Dr. Meng Li
Dr. Shuo Cheng
Dr. Qi Cao
Dr. Rui Shang
Dr. Qi Liu
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 250 words) can be sent to the Editorial Office for assessment.

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.

• unmanned aerial vehicles
• unmanned ground vehicles
• air–ground integrated perception 
• UAV–UGV cooperative systems
• multi-agent collaborative control
• AI-driven unmanned systems
• autonomous transportation systems
• multimodal perception and fusion