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About

Angelos Mallios is a robotics researcher specializing in autonomous underwater vehicles (AUVs), simultaneous localization and mapping (SLAM), and sonar-based navigation in complex underwater environments. His work sits at the compelling intersection of marine robotics and real-world applications, pushing the boundaries of how robots perceive and navigate unstructured aquatic settings. Mallios is perhaps best known for his foundational contributions to probabilistic sonar scan-matching techniques, most notably the MSISpIC algorithm, which enables AUVs to reliably localize and map unknown environments using mechanical scanning imaging sonar. These methods have been extended into full EKF-SLAM frameworks and bathymetry-based mapping using multibeam profilers, demonstrating both theoretical rigor and practical versatility. His most-cited work (244 citations) showcases an exceptional interdisciplinary reach — leading robotic surveys of an ancient Greek shipwreck off Chios, bridging marine archaeology and autonomous systems. His underwater cave dataset (60 citations) has become a valuable community benchmark, further amplifying his broader impact. With over 590 cumulative citations across his key publications, Mallios has established himself as a significant contributor to underwater robotics, providing the research community with both innovative algorithms and rare, high-quality real-world datasets that continue to drive advances in marine autonomy.