Benedikt Kreis
Papers
3
Total Citations
18
H-Index
2
About
Benedikt Kreis is a robotics researcher focused on human-robot interaction and intelligent manipulation, with key contributions in personalized navigation and object placement. His most cited work, "Learning Depth Vision-Based Personalized Robot Navigation From Dynamic Demonstrations in Virtual Reality" (2023, 14 citations), introduces a novel framework that uses VR-based demonstrations to train depth vision-driven navigation policies tailored to individual user preferences, enhancing human-robot interaction experiences. This approach addresses the critical need for robots to adapt their behavior to personal comfort zones, marking a significant step toward socially aware autonomous systems. Kreis also advances robotic dexterity in "Compact Multi-Object Placement Using Adjacency-Aware Reinforcement Learning" (2024, 2 citations), tackling the challenging task of precisely arranging irregularly shaped objects with sensitive surfaces, and "Reactive Correction of Object Placement Errors for Robotic Arrangement Tasks" (2024, 2 citations), which develops real-time error correction for assembly tasks. His work bridges perception, learning, and control, demonstrating impact through practical applications in domestic and industrial settings. Kreis’s research is notable for integrating immersive demonstration methods with deep learning, offering scalable solutions for personalized and precise robotic behaviors.
Research Focus
Key Achievements
Top Papers
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