Matteo Reggente
Papers
10
Total Citations
464
H-Index
9
About
Matteo Reggente is a pioneering researcher at the intersection of mobile robotics and environmental monitoring, with a particular focus on gas distribution modeling and pollution mapping. His most significant contribution is the development of the Kernel DM+V algorithm (2009), a statistical framework that enables mobile robots to construct accurate two-dimensional gas distribution models — a landmark work that has garnered over 150 citations and fundamentally advanced the field of robotic olfaction. Building on this foundation, Reggente extended his methods to incorporate wind dynamics through the Kernel DM+V/W algorithm and subsequently scaled these approaches into full three-dimensional gas distribution mapping, demonstrating remarkable depth and progression in his research agenda. A recurring theme in Reggente's work is the translation of theoretical algorithms into real-world applications. His involvement in the EU-funded DustBot project exemplifies this commitment, deploying autonomous robots for urban pollution monitoring and waste collection in pedestrian environments. With over 460 cumulative citations across his published work, Reggente has made enduring contributions to how robots perceive and characterize chemical environments. His doctoral dissertation synthesized these developments into a comprehensive treatment of statistical gas distribution modeling, serving as an essential reference for researchers exploring robotic sensing in uncontrolled, real-world settings.
Research Focus
Key Achievements
Top Papers
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- 2Towards environmental monitoring with mobile robots84 citations · 2008
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- 10Statistical Gas Distribution Modelling for Mobile Robot Applications6 citations · 2014