Advanced Flight Control and Intelligent Trajectory Planning in UAVs

A special issue of Machines (ISSN 2075-1702).

Deadline for manuscript submissions: 31 May 2026 | Viewed by 623

Special Issue Editor


E-Mail Website
Guest Editor
School of Automation, Northwestern Polytechnical University, Xi’an 710072, China
Interests: flight control and simulation; trajectory optimization and guidance; formation flight control; intelligence control and modern control; fault-tolerance control and fault diagnosis

Special Issue Information

Dear Colleagues,

Trajectory planning refers to finding the optimal flight path for an aircraft from an initial point to a target point under specific constraints, meeting certain performance criteria. In recent years, as the complexity of Unmanned Aerial Vehicle missions has increased, advanced flight control and trajectory planning technologies have become key for efficient and reliable mission execution. Trajectory planning technology can be used to design safe flight paths for Unmanned Aerial Vehicles by comprehensively considering factors such as environmental threats, flight performance constraints, and spatiotemporal coordination. Meanwhile, advanced flight control methods effectively guide Unmanned Aerial Vehicles along the planned trajectory, ensuring the successful completion of flight missions.

This Special Issue invites original research contributions that address the challenges posed by flight control systems in aerospace applications. We are particularly interested in papers that offer theoretical insights and practical solutions, including, but not limited to, the following:

Advanced flight control for unmanned aerial vehicles;

Intelligent flight control for unmanned aerial vehicles;

Dynamic trajectory planning for unmanned aerial vehicles;

Intelligent trajectory planning for unmanned aerial vehicles.

Dr. Xiaoxiong Liu
Guest Editor

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. Machines 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 2400 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

  • flight control
  • trajectory planning
  • comprehensive guidance

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

18 pages, 3878 KB  
Article
Research on Vision-Based Autonomous Landing Fusion Positioning Algorithm for Unmanned Aerial Vehicle
by Hongyuan Zhu, Jing Ni, Nan Yang, Boyang Gao and Xiaoxiong Liu
Machines 2026, 14(5), 460; https://doi.org/10.3390/machines14050460 - 22 Apr 2026
Viewed by 304
Abstract
A multi-task network for runway lines and runway markings based on deep learning was designed to address the issue of prior information dependence on runway width in unmanned aerial vehicle visual autonomous landing application scenarios. By detecting runway images captured at different positions [...] Read more.
A multi-task network for runway lines and runway markings based on deep learning was designed to address the issue of prior information dependence on runway width in unmanned aerial vehicle visual autonomous landing application scenarios. By detecting runway images captured at different positions during flight, the parameters of the runway start line, left and right boundary lines, and runway markings were obtained. On this basis, a runway width estimation model and visual positioning algorithm based on line features were designed. In standard runway scenarios, the recognition of runway signs provides valuable prior information about the runway width. For simplified runways or cases where signs are missing, we have devised a width estimation model based on the left/right boundary lines. Furthermore, considering the variation in pitch angle during the UAV’s landing process, we have analyzed and refined the width estimation model to ensure its applicability throughout the entire landing process. Additionally, we have developed a visual positioning algorithm that utilizes the runway width and runway line parameters to calculate the relative position between the UAV and the runway. Considering the limitations of a single visual positioning algorithm, we adopt a visual and inertial navigation fusion positioning algorithm to enhance the reliability of landing positioning. To validate our algorithms, we have constructed a visual simulation platform and flight test. These tests confirm the effectiveness and accuracy of our detection algorithm and width estimation model. Furthermore, by utilizing the estimated runway width and the detected runway line parameters, we have successfully calculated the relative position, further validating the effectiveness of our positioning algorithm. Full article
(This article belongs to the Special Issue Advanced Flight Control and Intelligent Trajectory Planning in UAVs)
Show Figures

Figure 1

Back to TopTop