Stephanie von Riegen
Papers
2
Total Citations
39
H-Index
2
About
Stephanie von Riegen is a researcher in cognitive robotics and artificial intelligence, whose work centers on enabling robots to learn from experience and reason about their environments. Her key research areas include ontology-based robot architectures, qualitative spatial reasoning, and knowledge representation for autonomous systems. Her most cited work, "An Ontology-based Multi-level Robot Architecture for Learning from Experiences" (2013, 31 citations), presents a framework developed within the EU project RACE that allows service robots to improve robustness and flexibility through experiential learning. This contribution addresses a fundamental challenge in robotics: how to move beyond pre-programmed behaviors toward adaptive, context-aware performance. In related work on qualitative spatial reasoning (2012, 8 citations), von Riegen demonstrates how robots can reason about spatial relationships to support mobile tasks such as detecting interaction ability. Her research bridges the gap between high-level ontological knowledge and low-level robotic control, offering practical pathways for more intelligent, autonomous systems. For students and researchers, von Riegen’s work exemplifies how integrating structured knowledge representation with robotic learning can advance the field toward truly adaptive machines.
Research Focus
Key Achievements
Top Papers
- 1An Ontology-based Multi-level Robot Architecture for Learning from Experiences31 citations · 2013
- 2Supporting Mobile Robot's Tasks through Qualitative Spatial Reasoning.8 citations · 2012