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Drones
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Autonomous Drone Navigation in GPS-Denied Environments
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Autonomous Drone Navigation in GPS-Denied Environments

A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drone Design and Development".

Deadline for manuscript submissions: 26 December 2025 | Viewed by 3468

Special Issue Editors

Prof. Dr. Hector Gutierrez

E-Mail Website
Guest Editor
Department of Mechanical Engineering, Florida Institute of Technology, Melbourne, FL 32901, USA
Interests: aerospace systems; mechatronics; motion control; electromechanical devices
Prof. Dr. Yang Liu

E-Mail Website
Guest Editor
Department of Engineering, University of Exeter, Exeter EX4 4PY, UK
Interests: automation and robotics; advanced control theory
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Drones have important applications in indoor environments, where there is no access to GPS for precise positioning. Indoor drone navigation faces specific challenges to achieve precise, robust position and attitude control, particularly given the small distances to walls and obstacles. While there is extensive work in the literature regarding localization and mapping, indoor navigation remains an important open topic with distinct challenges, given the reliance on visual–inertial information to achieve precise, robust positioning and 6-DOF motion control.

The Special Issue focuses on software, hardware, and analytical and computational techniques that support drone navigation in indoor environments, including, but not limited to, the following: image processing, sensor fusion, online–offline sensor calibration, localization, mapping, position and attitude estimation, path planning, and the 6-DOF motion control of drones in indoor environments.

Suggested article types:

  • Review Articles: detailed review of the state of the art in indoor drone navigation.
  • Articles: novel research contributions

Prof. Dr. Hector Gutierrez
Prof. Dr. Yang 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 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.

Keywords

  • autonomous drone navigation
  • GPS-denied environment
  • visual–inertial navigation
  • visual–inertial odometry
  • simultaneous localization and mapping
  • resource-constrained autonomous navigation
  • robust dynamic sensor calibration

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

Published Papers (4 papers)

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Research

26 pages, 8635 KiB  
Article
Test Methodologies for Collision Tolerance, Navigation, and Trajectory-Following Capabilities of Small Unmanned Aerial Systems
by Edwin Meriaux and Kshitij Jerath
Drones 2025, 9(6), 447; https://doi.org/10.3390/drones9060447 - 18 Jun 2025
Viewed by 271
Abstract
SmallUnmanned Aerial Systems (sUAS) have seen rapid adoption thanks to advances in endurance, communications, autonomy, and manufacturing costs, yet most testing remains focused on GPS-supported, above-ground operations. This study introduces new test methodologies and presents comprehensive experimental evaluations of collision tolerance, navigation, and [...] Read more.
SmallUnmanned Aerial Systems (sUAS) have seen rapid adoption thanks to advances in endurance, communications, autonomy, and manufacturing costs, yet most testing remains focused on GPS-supported, above-ground operations. This study introduces new test methodologies and presents comprehensive experimental evaluations of collision tolerance, navigation, and trajectory following for commercial sUAS platforms in GPS-denied indoor environments. We also propose numerical and categorical metrics—based on established vehicle collision protocols such as the Modified Acceleration Severity Index (MASI) and Maximum Delta V (MDV)—to quantify collision resilience; for example, the tested platforms achieved an average MASI of 0.1 g, while demonstrating clear separation between the highest- and lowest-performing systems. The experimental results revealed that performance varied significantly with mission complexity, obstacle proximity, and trajectory requirements, identifying platforms best suited for subterranean or crowded indoor applications. By aggregating these metrics, users can select the optimal drone for their specific mission requirements in challenging enclosed spaces. Full article
(This article belongs to the Special Issue Autonomous Drone Navigation in GPS-Denied Environments)
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20 pages, 7513 KiB  
Article
UAV Autonomous Navigation System Based on Air–Ground Collaboration in GPS-Denied Environments
by Pengyu Yue, Jing Xin, Yan Huang, Jiahang Zhao, Christopher Zhang, Wei Chen and Mao Shan
Drones 2025, 9(6), 442; https://doi.org/10.3390/drones9060442 - 16 Jun 2025
Viewed by 520
Abstract
This paper explores breakthroughs from the perspective of UAV navigation architectures and proposes a UAV autonomous navigation method based on aerial–ground cooperative perception to address the challenge of UAV navigation in GPS-denied and unknown environments. The approach consists of two key components. Firstly, [...] Read more.
This paper explores breakthroughs from the perspective of UAV navigation architectures and proposes a UAV autonomous navigation method based on aerial–ground cooperative perception to address the challenge of UAV navigation in GPS-denied and unknown environments. The approach consists of two key components. Firstly, a mobile anchor trilateration and environmental modeling method is developed using a multi-UAV system by integrating the visual sensing capabilities of aerial surveillance UAVs with ultra-wideband technology. It constructs a real-time global 3D environmental model and provides precise positioning information, supporting autonomous planning and target guidance for near-ground UAV navigation. Secondly, based on real-time environmental perception, an improved D* Lite algorithm is employed to plan rapid and collision-free flight trajectories for near-ground navigation. This allows the UAV to autonomously execute collision-free movement from the initial position to the target position in complex environments. The results of real-world flight experiments demonstrate that the system can efficiently construct a global 3D environmental model in real time. It also provides accurate flight trajectories for the near-ground navigation of UAVs while delivering real-time positional updates during flight. The system enables UAVs to autonomously navigate in GPS-denied and unknown environments, and this work verifies the practicality and effectiveness of the proposed air–ground cooperative perception navigation system, as well as the mobile anchor trilateration and environmental modeling method. Full article
(This article belongs to the Special Issue Autonomous Drone Navigation in GPS-Denied Environments)
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16 pages, 4008 KiB  
Article
On the Flying Accuracy of Miniature Drones in Indoor Environments
by Nusin Akram, Ilker Kocabas and Orhan Dagdeviren
Drones 2025, 9(6), 399; https://doi.org/10.3390/drones9060399 - 28 May 2025
Viewed by 560
Abstract
Micro drones are becoming more popular in many areas, because they are small and fast enough to fly in tight and complex spaces. But they still have some significant problems. Their batteries drain fast, they cannot carry much weight, and their sensors and [...] Read more.
Micro drones are becoming more popular in many areas, because they are small and fast enough to fly in tight and complex spaces. But they still have some significant problems. Their batteries drain fast, they cannot carry much weight, and their sensors and computers are limited. These problems affect their flying performance and stability, which is very important for their missions. In this study, we evaluated the accuracy of mini drones in indoor environments. During hovering, the drones showed an average deviation of 77.9 cm, with a standard deviation of 26.4 cm, indicating moderate stability while stationary. In simple forward flights over 3 m, the average deviation increased to 92.6 cm, which showed slight drop in accuracy during movement. For more complex flight paths, such as L-shaped and square trajectories, the deviations increased to 141 cm and 245 cm, respectively. Full article
(This article belongs to the Special Issue Autonomous Drone Navigation in GPS-Denied Environments)
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24 pages, 9850 KiB  
Article
RTAPM: A Robust Top-View Absolute Positioning Method with Visual–Inertial Assisted Joint Optimization
by Pengfei Tong, Xuerong Yang, Xuanzhi Peng and Longfei Wang
Drones 2025, 9(1), 37; https://doi.org/10.3390/drones9010037 - 7 Jan 2025
Viewed by 1012
Abstract
In challenging environments such as disaster aid or forest rescue, unmanned aerial vehicles (UAVs) have been hampered by inconsistent or even denied global navigation satellite system (GNSS) signals, resulting in UAVs becoming incapable of operating normally. Currently, there is no unmanned aerial vehicle [...] Read more.
In challenging environments such as disaster aid or forest rescue, unmanned aerial vehicles (UAVs) have been hampered by inconsistent or even denied global navigation satellite system (GNSS) signals, resulting in UAVs becoming incapable of operating normally. Currently, there is no unmanned aerial vehicle (UAV) positioning method that is capable of substituting or temporarily replacing GNSS positioning. This study proposes a reliable UAV top-down absolute positioning method (RTAPM) based on a monocular RGB camera that employs joint optimization and visual–inertial assistance. The proposed method employs a bird’s-eye view monocular RGB camera to estimate the UAV’s moving position. By comparing real-time aerial images with pre-existing satellite images of the flight area, utilizing components such as template geo-registration, UAV motion constraints, point–line image matching, and joint state estimation, a method is provided to substitute satellites and obtain short-term absolute positioning information of UAVs in challenging and dynamic environments. Based on two open-source datasets and real-time flight experimental tests, the method proposed in this study has significant advantages in positioning accuracy and system robustness over existing typical UAV absolute positioning methods, and it can temporarily replace GNSS for application in challenging environments such as disaster aid or forest rescue. Full article
(This article belongs to the Special Issue Autonomous Drone Navigation in GPS-Denied Environments)
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