Investigation into Vision-Based Navigation Systems for Unmanned Aerial Vehicles

DOI

10.2991/978-94-6463-821-9_21How to use a DOI?

Keywords

Vision-Based Navigation; Unmanned Aerial Vehicles; Autonomous Navigation; Deep Learning

Abstract

With the rapid advancement of unmanned aerial vehicle (UAV) technology, the limitations of traditional Global Positioning System (GPS) in complex low-altitude environments have become increasingly apparent, driving research demands for vision-based navigation technologies. This paper systematically investigates the fundamental principles, sensor types, and mainstream algorithms of UAV visual navigation systems. Through analysis of practical cases, solutions are proposed to enhance UAVs’ autonomous navigation and intelligent decision-making capabilities in complex environments. The study concludes that vision-based navigation systems enable efficient data acquisition and processing in challenging low-altitude scenarios, effectively compensating for GPS deficiencies. To address these issues, the paper proposes solutions such as multimodal sensor fusion, algorithm structure optimization, and parallel computing resource utilization. Future research on vision-based navigation should focus on algorithm optimization and innovation to reduce computational complexity and improve system adaptability. This work aims to address critical challenges in UAV visual navigation systems and provides perspectives on improving real-time performance and positioning accuracy for future developments.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Tianhao Huang
PY  - 2025
DA  - 2025/08/31
TI  - Investigation into Vision-Based Navigation Systems for Unmanned Aerial Vehicles
BT  - Proceedings of the 2025 2nd International Conference on Mechanics, Electronics Engineering and Automation (ICMEEA 2025)
PB  - Atlantis Press
SP  - 181
EP  - 190
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-821-9_21
DO  - 10.2991/978-94-6463-821-9_21
ID  - Huang2025
ER  -