Daniel Rodriguez-Criado
Papers
2
Total Citations
35
H-Index
2
About
Daniel Rodriguez-Criado is a leading researcher in human-aware robot navigation, specializing in the integration of graph neural networks (GNNs) to model and predict human-robot interactions. His work addresses the critical challenge of enabling robots to navigate safely and socially in environments shared with people. His most-cited paper, "A graph neural network to model disruption in human-aware robot navigation" (2021, 28 citations), introduces a novel GNN-based framework that predicts the disruption caused by robot motion, allowing for more intuitive and less intrusive navigation. Building on this, his subsequent work, "Generation of Human-Aware Navigation Maps Using Graph Neural Networks" (2021, 7 citations), extends the approach to create dynamic navigation maps that adapt to human presence and behavior. Rodriguez-Criado’s contributions are pivotal in advancing socially compliant robotics, bridging the gap between theoretical graph-based models and practical, real-world navigation systems. His research has significant implications for service robots, autonomous vehicles, and collaborative manufacturing, where seamless human-robot coexistence is essential. By combining deep learning with spatial reasoning, he is shaping the future of intelligent, human-aware autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1A graph neural network to model disruption in human-aware robot navigation28 citations · 2021
- 2Generation of Human-Aware Navigation Maps Using Graph Neural Networks7 citations · 2021