Roberto Arroyo
Papers
7
Total Citations
341
H-Index
6
About
Roberto Arroyo is a leading researcher in robotics and computer vision, specializing in life-long visual localization, topological mapping, and multi-sensorial SLAM for autonomous systems. His major contributions address the extreme challenge of place recognition across changing seasons, dynamic elements, and varying illumination—a critical problem for long-term mobile robotics and intelligent vehicles. Arroyo pioneered the fusion and binarization of CNN features for robust topological localization, achieving 99 citations in his seminal 2016 work, and developed the ABLE-M method for efficient binary sequence matching (96 citations), enabling reliable life-long visual localization. He also advanced aerial robotics with a multi-sensorial SLAM system for low-cost micro aerial vehicles in GPS-denied environments (78 citations), and contributed to humanoid robot teleoperation with a low-cost control system. His work on non-rigid structure-from-motion for real-time deformable object tracking further showcases his versatility. With over 340 total citations, Arroyo’s research is foundational for autonomous navigation in unpredictable, real-world environments, making him a key figure in the field.
Research Focus
Key Achievements
Top Papers
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- 5Are you ABLE to perform a life-long visual topological localization?22 citations · 2017
- 6Real-time sequential model-based non-rigid SFM14 citations · 2014
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