Papers
8
Total Citations
100
H-Index
5
About
Pepe Ojeda is a robotics researcher specializing in robotic olfaction, gas source localization (GSL), and autonomous mobile sensing systems. His work addresses one of the more challenging frontiers in robotics: enabling autonomous agents to detect, map, and trace airborne gases in complex, real-world indoor environments characterized by obstacles and turbulent airflows. Ojeda's most influential contribution, "Information-Driven Gas Source Localization Exploiting Gas and Wind Local Measurements" (2021, 43 citations), introduced a principled probabilistic approach to GSL that significantly advanced the field's applicability to realistic scenarios. He has consistently pushed the boundaries of simulation and benchmarking, developing tools such as GadenTools and contributing the VGR Dataset — a CFD-based gas dispersion resource designed to accelerate progress in robotic olfaction research. His 2021 simulation framework work demonstrated a notable commitment to community infrastructure, enabling multi-sensor integration previously unavailable to researchers. More recently, Ojeda has explored probabilistic mapping combined with online dispersion simulation (2024, 19 citations) and investigated multi-robot formation strategies for methane detection. Collectively accumulating nearly 100 citations, his body of work has meaningfully shaped the trajectory of robotic olfaction, offering both novel algorithms and essential open tools for researchers entering this emerging field.
Research Focus
Key Achievements
Top Papers
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- 4An Evaluation of Gas Source Localization Algorithms for Mobile Robots11 citations · 2020
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