Jonathan Liebner
Papers
2
Total Citations
37
H-Index
2
About
Jonathan Liebner is a robotics researcher whose work focuses on enabling mobile robots to perceive and interact with humans in real-world environments. His primary research areas include 3D person detection, posture estimation, and assistive robotics—specifically addressing the computational constraints of autonomous systems. Liebner’s most cited paper, "Fast and Robust 3D Person Detector and Posture Estimator for Mobile Robotic Applications" (2019, 25 citations), tackles the challenge of deploying deep learning-based person detection on resource-limited robotic platforms. He demonstrates that while computer vision has largely solved person detection, mobile robotics requires lightweight, efficient algorithms that maintain robustness in dynamic, crowded spaces. His second notable work, "Now I Need Help! Passing Doors and Using Elevators as an Assistance Requiring Robot" (2019, 12 citations), explores how robots can proactively request human assistance when navigating barriers like doors and elevators—a critical step toward truly autonomous assistive robots. Liebner’s contributions bridge the gap between theoretical computer vision and practical robotic deployment, making him a key figure in developing socially aware, resource-constrained mobile robots for healthcare, service, and domestic applications.
Research Focus
Key Achievements
Top Papers
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