Andreas Stelzer

Papers

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About

Andreas Stelzer is a researcher whose work centers on advancing radar-based perception and localization for autonomous systems. His primary contributions lie in the domain of radar odometry, where he has developed novel algorithms that enhance the robustness and accuracy of motion estimation using radar sensors. Stelzer’s most-cited paper, "Spatial-Radon and Doppler Aggregated Radar Odometry" (2024), introduces a statistically robust method for fusing two distinct sources of rotation estimation derived from radar-generated images. This work addresses a critical challenge in radar-only navigation—leveraging both spatial and Doppler information to improve odometry in challenging environments where other sensors, like cameras or LiDAR, may fail. Evaluated with real-world data, the algorithm demonstrates practical viability for applications in robotics and autonomous vehicles. With 2 citations in its early publication stage, this paper signals growing interest in his approach. Stelzer’s research is particularly notable for its focus on exploiting the unique properties of radar, such as its resilience to adverse weather, to push the boundaries of reliable, all-weather localization. His work represents a meaningful step toward more dependable autonomous navigation systems.