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Advances in Vision-Based UAV Navigation: Innovations and Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: 15 September 2025 | Viewed by 5

Special Issue Editors

School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710129, China
Interests: vision navigation

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Guest Editor
School of Aerospace, Northwestern Polytechnical University, Xi’an 710129, China
Interests: aviation/space vehicle photoelectric detection technology; intelligent perception and anti-interference technology
School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710129, China
Interests: intelligent image processing; machine learning and artificial intelligence
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Special Issue Information

Dear Colleagues,

Unmanned Aerial Vehicles (UAVs) have seen remarkable growth in recent years, driven by advances in sensor technology, computing power, and artificial intelligence. Vision-based navigation, which leverages cameras and computer vision, is a key enabling technology for autonomous UAVs. This Special Issue aims to capture the latest innovations and applications in vision-based UAV navigation. It will cover a broad range of topics, from fundamental research to practical implementations, providing a comprehensive overview of the current state of the art and future directions in this dynamic field. By bringing together leading researchers and practitioners, this Special Issue will serve as a valuable resource for advancing the capabilities and applications of UAVs.

This Special Issue focuses on the recent advancements and emerging trends in vision-based navigation for unmanned aerial vehicles (UAVs). We seek original research articles, review papers, and case studies that highlight theoretical developments, novel algorithms, sensor fusion techniques, and practical implementations that enhance the performance, robustness, and autonomy of UAVs. Topics of interest include, but are not limited to, visual simultaneous localization and mapping (VSLAM), real-time obstacle detection and avoidance, machine learning for environmental perception, sensor integration, and energy-efficient navigation. We also encourage submissions that explore the application of vision-based navigation in diverse fields such as urban environments, agriculture, surveillance, and disaster response.

Dr. Bo Li
Dr. Shaoyi Li
Dr. Shun Zhang
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. Sensors is an international peer-reviewed open access semimonthly 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

  • vision-based navigation
  • unmanned aerial vehicles (UAVs)
  • visual SLAM
  • obstacle detection and avoidance
  • machine learning
  • sensor fusion
  • real-time processing
  • energy-efficient navigation
  • urban environments
  • agricultural applications

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Published Papers

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