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State-of-the-Art Autonomous Landing Solutions for UAVs on Moving Platforms
Nguyen, T.; Van Rijswijck, V.; De Cubber, G.; Janssens, B.; Bruyninckx, H. (2025). State-of-the-Art Autonomous Landing Solutions for UAVs on Moving Platforms. Proc. SPIE Int. Soc. Opt. Eng. 13680: 136800C. https://dx.doi.org/10.1117/12.3069539
In: Proceedings of SPIE, the International Society for Optical Engineering. SPIE: Bellingham, WA. ISSN 0277-786X; e-ISSN 1996-756X, meer
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| Author keywords |
uav;autonomous;landing;literature review;unmanned aerial vehicles;control strategies;quadrotor;tracking;guidance |
| Auteurs | | Top |
- Nguyen, T.
- Van Rijswijck, V.
- De Cubber, G., meer
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- Janssens, B.
- Bruyninckx, H.
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| Abstract |
The autonomous landing of Unmanned Aerial Vehicles (UAVs) onto dynamic, moving platforms poses significant technical challenges but offers transformative capabilities for persistent surveillance, remote logistics, and force projection in security and defense operations. This paper presents a systematic and comprehensive state-of-the-art review of autonomous landing systems specifically targeting these demanding scenarios. Our research methodology involved analyzing a broad range of recent literature, focusing on holistic system-level solutions rather than isolated component advancements. We categorize and evaluate approaches based on key integrated subsystems: perception, motion planning, flight control strategies, and landing supported hardware. The review explicitly considers how aerodynamic constraints and actuation capabilities influence landing strategy and system design when interacting with platforms like ground vehicles or maritime vessels under varying environmental conditions. Key findings indicate a trend towards vision-based primary sensing often augmented with complementary sensors for robustness, particularly in GPS-denied environments. Significant challenges persist in achieving high reliability under adverse weather, high sea states, or non-cooperative target motion. We analyze the trade-offs between different system architectures regarding computational load, communication requirements, and resilience. This synthesized overview identifies critical technology gaps and promising research avenues, such as AI-driven perception and control, cooperative multi-agent landing, and enhanced testing and validation methodologies, providing valuable insights for advancing autonomous capabilities in security and defense contexts. |
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