Daniel Westhoff
Papers
9
Total Citations
76
H-Index
5
About
Daniel Westhoff’s research lies at the intersection of robotics, artificial intelligence, and human-robot interaction, with a particular focus on episodic memory, multimodal perception, and software architectures for service robots. His most influential contribution is the EPIROME framework (22 citations), a novel approach to implementing high-level episodic memory in artificial systems—bridging insights from psychology and neuroscience to enable robots to recall past experiences and adapt their behavior accordingly. Westhoff also advanced multimodal people tracking and trajectory prediction, developing methods to fuse sensor data and generalize motion patterns for real-time prediction of human movement—critical for safe and intuitive robot navigation in shared spaces. His work on flexible software architectures, such as the roblet-based system, has eased the development of complex service robot applications. Notably, Westhoff demonstrated the practical impact of his research by deploying a mobile robot system that automated sample management in biotechnological cell cultivations, showcasing how service robotics can streamline laboratory workflows. With over 75 total citations across his publications, Westhoff’s contributions have helped lay the groundwork for more intelligent, context-aware, and socially capable service robots.
Research Focus
Key Achievements
Top Papers
- 1EPIROME - A novel framework to investigate high-level episodic robot memory22 citations · 2007
- 2A flexible software architecture for multi-modal service robots12 citations · 2006
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- 9A Comparison of Regional Feature Detectors in Panoramic Images3 citations · 2006