Philipp Steinemann
Papers
2
Total Citations
17
H-Index
2
About
Philipp Steinemann is a researcher whose work lies at the intersection of robotics, autonomous driving, and advanced sensor perception. His primary research focuses on the challenging problem of tracking extended targets using 3D LIDAR measurements—a critical component for collision avoidance and path planning in autonomous systems. Steinemann’s major contributions include developing robust, geometric-model-free methods for extracting 3D outline contours of vehicles from high-definition, 360-degree LIDAR data. His 2012 paper on this topic, which has garnered 9 citations, introduced a novel approach to handling the complexity of tracking objects with irregular shapes, moving beyond traditional point-target models. A subsequent paper, with 8 citations, further advanced this field by proposing a method that eliminates the need for predefined geometric models, making the tracking more adaptable to real-world scenarios. Steinemann’s work is foundational for enabling autonomous vehicles to perceive and predict the motion of surrounding objects, directly impacting safety and navigation. His research remains highly relevant as the industry pushes toward fully autonomous driving, and his contributions continue to inform modern sensor fusion and tracking algorithms.
Research Focus
Key Achievements
Top Papers
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