Papers
56
Total Citations
2,272
H-Index
22
About
Pascual Campoy is a leading researcher in autonomous aerial robotics, computer vision, and artificial intelligence, whose work has fundamentally shaped how unmanned aerial vehicles (UAVs) perceive, navigate, and interact with their environments. Based at the Technical University of Madrid, Campoy has pioneered the application of deep learning and reinforcement learning to drone autonomy, most notably through his highly influential 2017 review of deep learning methods for UAVs, which has accumulated over 360 citations and remains a foundational reference in the field. His groundbreaking contributions include developing autonomous UAV landing systems on moving platforms, indoor search-and-rescue aerial robots using learning-based techniques, and deep reinforcement learning controllers for visual servoing — work that collectively underscores his commitment to translating theoretical AI advances into real-world robotic applications. Campoy has also advanced human-drone interaction through natural user interfaces and contributed AEROSTACK, an open-source software framework that has democratized aerial robotics research globally. With thousands of cumulative citations and contributions spanning semantic SLAM, vision-based control, and event-driven model predictive control, Campoy's research continues to define the frontier of intelligent, autonomous aerial systems.
Research Focus
Key Achievements
Top Papers
- 1A Review of Deep Learning Methods and Applications for Unmanned Aerial Vehicles363 citations · 2017
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- 4Natural user interfaces for human-drone multi-modal interaction176 citations · 2016
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- 6VPS-SLAM: Visual Planar Semantic SLAM for Aerial Robotic Systems94 citations · 2020
- 7A vision-based strategy for autonomous aerial refueling tasks82 citations · 2013
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