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About

Regina Ticona-Herrera is a leading researcher at the intersection of knowledge representation and autonomous robotics, with a primary focus on the Simultaneous Localization and Mapping (SLAM) problem. Her work addresses the critical challenge of making autonomous robots more intelligent and interoperable by formally modeling the complex knowledge involved in navigation and environmental mapping. Ticona-Herrera’s major contributions include the development of **OntoSLAM**, a dedicated ontology for representing location and mapping information, which provides a structured, flexible framework to enhance robot decision-making. Her foundational survey on ontologies for SLAM, with **15 citations**, has become a key reference for researchers seeking to integrate semantic knowledge into robotic systems. Beyond ontology creation, she has pioneered a **methodological approach for comparing ontologies**, applying the OQuaRE quality model to ensure robust evaluation and selection of knowledge models. With a growing body of work accumulating over **39 citations**, Ticona-Herrera’s research bridges the gap between abstract knowledge engineering and practical robotic autonomy, offering essential tools for developing more adaptive and context-aware mobile robots.