Autonomous Landing Algorithms is a computational framework designed to enable unmanned aerial vehicles to navigate, detect suitable landing sites, and execute precise landings without human intervention, distinguished by its integration of perception, decision-making, and control functionalities within dynamic and unstructured environments.
420
Publications
17.5K
Citations
1.3K
Authors
360
Institutions
Publications per year
2017–2026
193
Parents
Publications
420
A vision system for landing an unmanned aerial vehicle
C. Sharp, Omid Shakernia, S. Shankar Sastry · 2002 · 322 citations
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1.3K
- LM
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Institutions
360
Jet Propulsion Laboratory
Pasadena, United States
18 h-index
62 publications
3.2K citations
Beihang University
Beijing, China
14 h-index
47 publications
1.8K citations
Korea Advanced Institute of Science and Technology
Daejeon, South Korea
13 h-index
41 publications
1.6K citations
National University of Defense Technology
Changsha, China
13 h-index
58 publications
2.7K citations
Beijing Institute of Technology
Beijing, China
10 h-index
32 publications
1K citations
Nanjing University of Aeronautics and Astronautics
Nanjing, China
9 h-index
27 publications
801 citations
Carnegie Mellon University
Pittsburgh, United States
9 h-index
19 publications
824 citations
Northwestern Polytechnical University
Xi'an, China
7 h-index
23 publications
1.2K citations
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Venues
- Journal of Intelligent & Robotic Systems
22 publications · 1.5K citations
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- Sensors
14 publications · 1K citations
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- Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
8 publications · 133 citations
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- Drones
10 publications · 352 citations
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- Aerospace Science and Technology
AST · 7 publications · 407 citations
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