Papers
11
Total Citations
108
H-Index
5
About
Ilaria Tiddi is a leading researcher at the intersection of robotics, artificial intelligence, and the Semantic Web, with a core focus on making robots more intelligent, accessible, and integrated into human environments. Her work is pivotal in defining the emerging field of **Robot–City Interaction (RCI)** , as detailed in her highly-cited 2019 survey (58 citations), which maps how robots can effectively operate within the complex, dynamic ecosystems of modern cities. Tiddi’s major contributions lie in developing **ontology-based frameworks** and **knowledge-driven perception** to bridge the gap between robotic systems and non-expert users. She has created tools like the ORKA ontology for robotic knowledge acquisition and interfaces that allow users to design complex robot behaviours without programming expertise. Her research also advances **few-shot object recognition** for mobile robots and explores novel human-robot teaching methods inspired by dog training. With a growing h-index and recent publications on large-scale knowledge graphs for enhanced robotic perception (2024), Tiddi is shaping a future where robots are not just tools, but intuitive, knowledgeable partners in our daily lives.
Research Focus
Key Achievements
Top Papers
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- 4A user-friendly interface to control ROS robotic platforms6 citations · 2018
- 5Meet HanS, the Health&Safety autonomous inspector5 citations · 2018
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- 7Update of time-invalid information in Knowledge Bases through Mobile Agents2 citations · 2016
- 8Large-Scale Knowledge Graphs as a Tool for Enhanced Robotic Perception2 citations · 2024
- 9Advancing Robotic Perception with Perceived-Entity Linking2 citations · 2024
- 10ORKA: An Ontology for Robotic Knowledge Acquisition2 citations · 2024