Yerai Berenguer
Papers
10
Total Citations
84
H-Index
4
About
Yerai Berenguer is a robotics researcher whose work centers on autonomous mobile robot navigation, omnidirectional vision, and robot kinematics. His primary contributions lie in developing methods for robots to build environmental models and estimate their position using the global appearance of omnidirectional images—a holistic approach that avoids complex feature extraction. His most cited paper, "Using Omnidirectional Vision to Create a Model of the Environment" (24 citations), compares global-appearance descriptors for robust mapping, while his second most cited work (22 citations) presents techniques for position estimation and local mapping from single omnidirectional snapshots. Berenguer has also explored altitude estimation for aerial or climbing robots (10 citations) and designed novel hybrid serial-parallel biped robots for inspection tasks, including kinematic analysis and workspace calculation. With over 80 total citations across his publications, his research has advanced practical, appearance-based localization methods that enable robots to navigate unknown environments efficiently. His work on simulation platforms for robot localization and education further demonstrates his commitment to accessible, reproducible research.
Research Focus
Key Achievements
Top Papers
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- 4Monte-Carlo Workspace Calculation of a Serial-Parallel Biped Robot9 citations · 2015
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- 8Kinematic Analysis and Simulation of a Hybrid Biped Climbing Robot3 citations · 2015
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