David Valiente
Papers
14
Total Citations
169
H-Index
8
About
David Valiente is a leading researcher in mobile robotics, specializing in omnidirectional vision, visual localization, and Simultaneous Localization and Mapping (SLAM). His work focuses on overcoming the challenges of robust perception and navigation using catadioptric cameras, which provide a full 360-degree field of view. Valiente’s key contributions include developing dynamic uncertainty management for visual SLAM, which addresses the non-linearities inherent in omnidirectional projection systems, and pioneering Bayesian inference methods for adaptive, probability-oriented feature matching. His research has produced highly cited works, such as his 2017 paper on robust visual localization (29 citations) and his 2018 study on visual information fusion (26 citations), which have significantly advanced the reliability of robot navigation in complex environments. Beyond SLAM, Valiente has explored hierarchical environmental modeling and altitude estimation using holistic descriptors, further expanding the capabilities of vision-based robotics. His work is widely recognized for its practical impact, with over 150 total citations, and he has also contributed to educational tools for simulating robot localization and control, demonstrating a commitment to both research and pedagogy.
Research Focus
Key Achievements
Top Papers
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- 4Improved Omnidirectional Odometry for a View-Based Mapping Approach21 citations · 2017
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