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Drones
Special Issues
Advances in Perception, Communications, and Control for Drones: 2nd Edition
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Advances in Perception, Communications, and Control for Drones: 2nd Edition

A special issue of Drones (ISSN 2504-446X).

Deadline for manuscript submissions: 26 January 2026 | Viewed by 2587

Special Issue Editors

Dr. Shihao Yan

E-Mail Website
Guest Editor
School of Science, Edith Cowan University, Joondalup, WA 6027, Australia
Interests: UAV-aided communications; covert communications; covert sensing; location spoofing detection; physical layer security; IRS-aided wireless communications
Special Issues, Collections and Topics in MDPI journals
Dr. Zhihong Liu

E-Mail
Guest Editor
College of Intelligence and Technology, National University of Defense Technology, Changsha 410073, China
Interests: multi-UAV systems; UAV swarms; cooperative decision and control
Special Issues, Collections and Topics in MDPI journals
Dr. Yirui Cong

E-Mail Website
Guest Editor
College of Intelligence and Technology, National University of Defense Technology, Changsha 410073, China
Interests: UAV; control theory; communication theory; filtering theory
Special Issues, Collections and Topics in MDPI journals
Dr. Kehao Wang

E-Mail Website
Guest Editor
School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China
Interests: stochastic optimization; operation research; scheduling; wireless network communications; embedded operating system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce this Special Issue of Drones on “Advances in Perception, Communications, and Control for Drones: 2nd Edition”.

In recent years, the field of drones has witnessed significant advancements and has broad applications in various industries, including agriculture, delivery services, surveillance, and entertainment. Perception, communications, and control capabilities are the key aspects of autonomy for drones, which enable them to operate tasks in an efficient and intelligent manner without human intervention. Inevitably, drones will also be placed in more challenging conditions and show their great potential in the future, such as observing and understanding complex environments by their sensors on-board, operating path planning and navigation under their perception conditions, multiple or swarms of drones working in a cooperative mode under communication constraints, etc. Quite a few perception, communications, and control problems are still far from being completely solved. We believe recent advancements in this topic could bring a revolution to their capabilities and applications, opening up new possibilities for safer, more efficient, and intelligent operation.

The Special Issue solicits key theoretical and practical contributions to perception, communications, and control for drones, aiming to showcase the latest developments and cutting-edge research in this fast-evolving field.

This Special Issue will welcome manuscripts that link (but not limited to) the following themes:

  • Advanced perception techniques of object detection and tracking for drones;
  • Drones remote sensing for mapping and surveying;
  • Real-time collision detection and avoidance for drones;
  • Perception-aware target tracking of drones;
  • Path planning and navigation of drones;
  • Cooperative control of multiple drones;
  • Coupling mechanism between control and communication of drones;
  • Control theory under communication constraint of drones;
  • Efficient communications for drone swarms;
  • Robust formation control algorithms of drones;
  • Communication-oriented control optimization of drones;
  • Robust or adaptive control design for drones.

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

Dr. Shihao Yan
Dr. Zhihong Liu
Dr. Yirui Cong
Dr. Kehao Wang
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.

Keywords

  • perception
  • drone communications
  • autonomous control
  • communication-oriented control
  • perception-aware control
  • drone swarms

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Related Special Issue

Published Papers (2 papers)

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Research

29 pages, 9586 KB  
Article
L1 Adaptive Nonsingular Fast Terminal Super-Twisting Control for Quadrotor UAVs Under Unknown Disturbances
by Shunsuke Komiyama, Kenji Uchiyama and Kai Masuda
Drones 2025, 9(12), 878; https://doi.org/10.3390/drones9120878 - 18 Dec 2025
Abstract
Quadrotor UAVs benefit from control strategies that can deliver rapid convergence and strong robustness in order to fully exploit their high agility. Finite-time control based on terminal sliding modes has been recognized as an effective alternative to classical sliding mode control, which only [...] Read more.
Quadrotor UAVs benefit from control strategies that can deliver rapid convergence and strong robustness in order to fully exploit their high agility. Finite-time control based on terminal sliding modes has been recognized as an effective alternative to classical sliding mode control, which only guarantees asymptotic convergence. Its enhanced variant, nonsingular fast terminal sliding mode control, eliminates singularities and achieves accelerated convergence; however, chattering-induced high-frequency oscillations remain a major concern. To address this issue, this study introduces a hybrid control framework that combines the super-twisting algorithm with L1 adaptive control. The super-twisting component preserves the robustness of sliding mode control while mitigating chattering, whereas L1 adaptive control provides rapid online estimation and compensation of model uncertainties and unknown disturbances. The resulting scheme is implemented in a quadrotor flight-control architecture and evaluated through numerical simulations. The results show that the proposed controller offers faster convergence and enhanced robustness relative to existing approaches, particularly in the presence of wind perturbations, periodic obstacle-avoidance maneuvers, and abrupt partial loss of propeller thrust. Full article
(This article belongs to the Special Issue Advances in Perception, Communications, and Control for Drones: 2nd Edition)
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21 pages, 1876 KB  
Article
Adaptive Minimum Error Entropy Cubature Kalman Filter in UAV-Integrated Navigation Systems
by Xuhang Liu, Hongli Zhao, Yicheng Liu, Suxing Ling, Xinhanyang Chen, Chenyu Yang and Pei Cao
Drones 2025, 9(11), 740; https://doi.org/10.3390/drones9110740 - 24 Oct 2025
Viewed by 2184
Abstract
Small unmanned aerial vehicles are now commonly equipped with integrated navigation systems to obtain high-precision navigation parameters. However, affected by the dual impacts of multipath effects and dynamic environmental changes, their state estimation process is vulnerable to interference from measurement outliers, which in [...] Read more.
Small unmanned aerial vehicles are now commonly equipped with integrated navigation systems to obtain high-precision navigation parameters. However, affected by the dual impacts of multipath effects and dynamic environmental changes, their state estimation process is vulnerable to interference from measurement outliers, which in turn leads to the degradation of navigation accuracy and poses a threat to flight safety. To address this issue, this research presents an adaptive minimum error entropy cubature Kalman filter. Firstly, the cubature Kalman filter is introduced to solve the problem of model nonlinear errors; secondly, the cubature Kalman filter based on minimum error entropy is derived to effectively curb the interference that measurement outliers impose on filtering results; finally, a kernel bandwidth adjustment factor is designed, and the kernel bandwidth is estimated adaptively to further improve navigation accuracy. Through numerical simulation experiments, the robustness of the proposed method with respect to measurement outliers is validated; further flight experiment results show that compared with existing related filters, this proposed filter can achieve more accurate navigation and positioning. Full article
(This article belongs to the Special Issue Advances in Perception, Communications, and Control for Drones: 2nd Edition)
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