Maximilian Hilger

RWTH Aachen University, Machine Intelligence Research Institute

Papers

Total Citations

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About

Maximilian Hilger is an emerging researcher specializing in robotic perception, simultaneous localization and mapping (SLAM), and radar-based sensing for autonomous systems. His work focuses on addressing the significant challenges posed by unstructured and vision-denied environments — conditions frequently encountered in rescue robotics and other demanding real-world applications. Hilger's most notable contribution is the development of RaNDT SLAM, a novel radar SLAM framework that leverages intensity-augmented Normal Distributions Transform to handle the complex noise characteristics inherent to Frequency-Modulated Continuous Wave (FMCW) radar sensors. This work, which has already garnered 5 citations since its 2024 publication, represents a meaningful advance in making pivoting radar sensors viable for robust localization. Building on this foundation, his 2025 work on introspective loop closure for SLAM with 4D imaging radar further pushes the boundaries of radar-based navigation, exploring how modern 4D radar technology can improve mapping reliability without reliance on external positioning systems or pre-existing maps. Hilger's research is particularly timely given the growing interest in sensor modalities that outperform cameras and lidars in degraded conditions. His contributions position him as a promising voice in the robotics and autonomous systems community.