Jasmin Gabsteiger

Friedrich-Alexander-Universität Erlangen-Nürnberg

Papers

Total Citations

H-Index

About

Jasmin Gabsteiger is a rising researcher at the forefront of radar-based perception for autonomous robotics, with a focus on enabling mobile robots to understand their environment using non-camera sensors. Her work centers on two critical challenges: gesture recognition and person detection from moving platforms, where traditional static radar approaches fail. In her 2024 paper on gesture recognition using FMCW radar, she tackles the problem of controlling a moving robot through hand gestures—a task complicated by the robot’s own motion introducing environmental noise. Her second major contribution, also from 2024, presents a 60 GHz MIMO radar system integrated on a moving robot for person presence detection, leveraging a deep convolutional neural network trained on 8,000 custom-recorded data frames. These works demonstrate her ability to bridge radar signal processing and deep learning for real-world robotic applications. While still early in her career, with papers accumulating initial citations (2 and 1 respectively), Gabsteiger’s research addresses a critical gap in the literature and holds promise for safer, more intuitive human-robot interaction in dynamic settings.