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About

Thomas Reineking is a leading researcher in the field of evidential robotics, whose work has fundamentally advanced how autonomous systems perceive and navigate uncertain environments. His primary contributions lie at the intersection of simultaneous localization and mapping (SLAM) and Dempster-Shafer theory, where he has pioneered the use of belief functions to model and manage uncertainty in robotic perception. His seminal 2016 paper, "An evidential approach to SLAM, path planning, and active exploration," with 38 citations, provides a comprehensive framework for integrating evidential reasoning into core robotic tasks. Reineking’s earlier work, "Evidential FastSLAM for grid mapping" (2013), was groundbreaking as the first to address the full SLAM problem using belief functions, while his "β-SLAM" (2018) introduced beta distributions for more robust grid mapping. He also extended his expertise to multi-modal perception with "Information-Driven Active Audio-Visual Source Localization" (2015), demonstrating a particle filter approach for combining audio and visual data on mobile robots. Across his publications, Reineking has accumulated over 85 citations, establishing himself as a key innovator in uncertainty-aware robotics.