Romana Pernisch

Vrije Universiteit Amsterdam, RELX Group (Netherlands)

Papers

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About

Romana Pernisch is a leading researcher at the intersection of the Semantic Web and autonomous robotics, specializing in knowledge-driven perception systems. Her work addresses a critical challenge: enabling robots to move beyond raw sensor data toward meaningful, context-aware understanding of their environments. Pernisch’s major contributions center on linking perceived entities in real-time to structured knowledge, effectively bridging the gap between physical sensing and machine-readable background knowledge. She introduced the ORKA ontology (Ontology for Robotic Knowledge Acquisition), a formal framework that allows robots to systematically acquire and integrate semantic knowledge during operation. Her most-cited papers—including "Large-Scale Knowledge Graphs as a Tool for Enhanced Robotic Perception," "Advancing Robotic Perception with Perceived-Entity Linking," and "ORKA: An Ontology for Robotic Knowledge Acquisition"—each published in 2024 and garnering 2 citations, represent foundational steps in this emerging field. By treating large-scale knowledge graphs as a cognitive resource for robots, Pernisch is pioneering methods that could transform how autonomous systems interpret complex, dynamic environments, making her work essential reading for researchers in robotics, knowledge representation, and AI.