Gerhard Kurz
Papers
11
Total Citations
96
H-Index
7
About
Gerhard Kurz is a leading researcher in the field of probabilistic state estimation, with a core focus on applying directional statistics and filtering techniques to constrained and non-Euclidean spaces. His work is pivotal for advanced robotics, particularly in autonomous navigation and medical applications. Kurz’s major contributions include the introduction of the partially wrapped normal distribution for SE(2) estimation, a novel approach that elegantly handles rigid motion estimation for robots and autonomous vehicles. He has also pioneered the use of discrete recursive Bayesian estimation on intervals and the unit circle, enabling robust filtering on complex manifolds like SE(2). His research has garnered significant attention, with his most-cited papers each accumulating over 10 citations, reflecting their foundational impact. Notably, Kurz has made groundbreaking strides in robotic beating heart surgery, developing real-time kernel-based multiple target tracking and directional estimation methods to stabilize surgical views and cancel heart motion. His work on toroidal information fusion using the bivariate von Mises distribution further showcases his versatility, addressing challenges in correlated angular data across fields from robotics to bioinformatics. Through these achievements, Kurz has established himself as a key innovator in estimation theory for real-world robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2The partially wrapped normal distribution for SE(2) estimation13 citations · 2014
- 3
- 4
- 5Directional Estimation for Robotic Beating Heart Surgery10 citations · 2015
- 6Toroidal information fusion based on the bivariate von Mises distribution10 citations · 2015
- 7
- 8Discretization of SO(3) using recursive tesseract subdivision6 citations · 2017
- 92D and 3D image stabilization for robotic beating heart surgery5 citations · 2014
- 10