Felix Endres
Papers
11
Total Citations
4,911
H-Index
9
About
Felix Endres is a leading researcher in robotics, with key contributions in 3D mapping, RGB-D SLAM (Simultaneous Localization and Mapping), and autonomous object discovery. His most influential work is the seminal 2012 benchmark for evaluating RGB-D SLAM systems, which has garnered over 3,900 citations and set the standard for comparing visual odometry and mapping algorithms using Kinect sensors. Endres also developed a highly accurate 3-D mapping system using only an RGB-D camera, achieving over 820 citations for its robust, sensor-independent approach. His research extends to unsupervised learning, where he pioneered methods for robots to autonomously discover object classes from 3D range data using Latent Dirichlet Allocation, reducing reliance on human-labeled training data. Additionally, he has explored learning dynamic models for robotic manipulation (e.g., opening doors) and enhancing sensor capabilities, such as extending RGB-D cameras with catadioptric optics for wider fields of view. With over 4,900 total citations across his top papers, Endres’s work has profoundly impacted robotics perception, enabling more autonomous and adaptable systems for real-world environments.
Research Focus
Key Achievements
Top Papers
- 1A benchmark for the evaluation of RGB-D SLAM systems3,918 citations · 2012
- 23-D Mapping With an RGB-D Camera822 citations · 2013
- 3
- 4Learning the dynamics of doors for robotic manipulation23 citations · 2013
- 5Monocular range sensing: A non-parametric learning approach20 citations · 2008
- 6
- 7A catadioptric extension for RGB-D cameras11 citations · 2014
- 8
- 9Graph-Based Action Models for Human Motion Classification10 citations · 2012
- 10Online−6D-SLAM für RGB-D-Sensoren8 citations · 2012