Michael van Bekkum
Papers
3
Total Citations
31
H-Index
2
About
Michael van Bekkum is a leading researcher at the intersection of human-robot interaction, cloud robotics, and intelligent agent systems. His primary contributions lie in designing robust, long-term social robot systems and developing knowledge-driven AI for healthcare and perception. In his highly cited 2021 work, "A Cloud-based Robot System for Long-term Interaction," van Bekkum established four foundational design principles for sustainable social robotics, demonstrating their efficacy through a real-world cloud-based implementation—a pivotal step toward overcoming the "long-term interaction" challenge in HRI. This paper has garnered 22 citations, reflecting its influence on the field. He also made significant strides in pediatric healthcare with the PAL project, where he developed ontologies for social, cognitive, and affective agent-based support to help children aged 8–14 manage diabetes. His most recent work (2025) advances affordance perception using a knowledge-guided vision-language model with efficient error correction, showcasing his ongoing commitment to bridging AI and robotics. Van Bekkum’s research is notable for its practical, human-centered focus, integrating cloud architectures and ontological reasoning to create scalable, empathetic robotic systems that operate effectively in real-world environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3