Ivan Markovi

Papers

Total Citations

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About

Ivan Markovi is a researcher whose work lies at the intersection of robotics, sensor modeling, and acoustic signal processing. His primary research focuses on enhancing how mobile robots perceive and interact with their environment through sound, particularly in the challenging domain of speaker localization and tracking. Markovi’s most notable contribution is his pioneering application of the von Mises distribution to microphone array probabilistic sensor modeling, a novel approach detailed in his 2010 paper. This work addresses the critical problem of localizing and tracking a moving speaker across the full 360-degree range around a mobile robot. By estimating the time difference of arrival through a weighted cross-correlation function and employing geometric calculations, his algorithm significantly improves the accuracy and robustness of auditory perception in dynamic, real-world settings. While his most-cited paper has garnered 5 citations, the conceptual foundation he laid is instrumental for researchers in human-robot interaction and autonomous navigation. Markovi’s work represents a meaningful step forward in equipping robots with more reliable, biologically inspired auditory capabilities, bridging the gap between probabilistic modeling and practical robotic applications.