Jens Klappstein

About

Jens Klappstein is a leading researcher in autonomous driving and mobile robotics, whose work has fundamentally advanced how vehicles perceive and navigate their environment. His primary research areas include ego-motion estimation, radar-based environmental perception, and extended target tracking using LiDAR sensors. Klappstein’s most influential contribution is his development of a robust algorithm for instantaneous ego-motion estimation using multiple Doppler radars, a paper that has garnered 132 citations and provides critical capabilities for advanced driver assistance systems by determining a vehicle’s complete 2D motion state in real time. He has also pioneered radar gridmap representations for automotive self-localization, with 88 citations, offering robust environmental mapping solutions. His work on monocular motion detection using spatial constraints and 3D outline contour extraction from LiDAR measurements has been instrumental in enabling collision avoidance and autonomous navigation. With a portfolio of highly cited papers, Klappstein’s research bridges the gap between theoretical computer vision and practical automotive applications, making him a key figure in the development of safe, perceptive autonomous systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Instantaneous ego-motion estimation using multiple Doppler radars

   132 citations · 2014
2. 2
   Automotive radar gridmap representations

   88 citations · 2015
3. 3
   Monocular Motion Detection Using Spatial Constraints in a Unified Manner

   33 citations · 2006
4. 4
   Detectability of Moving Objects Using Correspondences over Two and Three Frames

   16 citations · 2007
5. 5
   3D outline contours of vehicles in 3D-LIDAR-measurements for tracking extended targets

   9 citations · 2012
6. 6
   Geometric-model-free tracking of extended targets using 3D lidar measurements

   8 citations · 2012

Key Collaborators

Contact & Links