Papers
21
Total Citations
223
H-Index
7
About
Raphael Memmesheimer is a robotics researcher whose work spans human-robot interaction, service robotics, and immersive telepresence systems. He has made significant contributions to enabling robots to understand and respond to human behavior, most notably through his development of deep metric learning approaches for skeleton-based one-shot action recognition — allowing robots to recognize previously unseen human actions from a single example, a breakthrough with direct implications for intuitive human-robot interaction (43 citations). Memmesheimer is perhaps best known for his central role in the NimbRo avatar system, which claimed the prestigious $5M grand prize at the international ANA Avatar XPRIZE competition, demonstrating world-leading capabilities in immersive telepresence, force-feedback telemanipulation, and remote locomotion (36 and 21 citations). His work on collaborative robot perception using smart edge sensors further reflects his commitment to real-world robotic deployment. Throughout his career, Memmesheimer has also been a driving force in competitive service robotics, contributing to multiple RoboCup@Home championships with team homer@UniKoblenz and later NimbRo, and helping shape over a decade of progress in the field. His most recent work explores foundation models for robotic perception and planning, signaling an exciting trajectory toward more capable, generalizable autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 4Mobile Manipulation Hackathon: Moving into Real World Applications18 citations · 2021
- 5RoboCup@Home: Summarizing achievements in over eleven years of competition16 citations · 2018
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- 7homer@UniKoblenz: Winning Team of the RoboCup@Home Open Platform League 201712 citations · 2018
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- 9A ROS-Based System for an Autonomous Service Robot7 citations · 2016
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