Marcus G. Müller — accepted AI-conference papers

2024

RATE: Real-time Asynchronous Feature Tracking with Event Cameras

Mikihiro Ikura, Cedric Le Gentil, Marcus G. Müller, Florian Schuler, Atsushi Yamashita, Wolfgang Stürzl

IROS 2024poster

Vision-based self-localization is a crucial technology for enabling autonomous robot navigation in GPS-deprived environments. However, standard frame cameras are subject to motion blur and suffer from a limited dynamic range. This research focuses on efficient feature tracking for self-localization…

Cited by 1 Source ↗code ↗Scholar ↗

2024

Tightly-Coupled Factor Graph Formulation For Radar-Inertial Odometry

Jan Michalczyk, Julius Quell, Florian Steidle, Marcus G. Müller, Stephan Weiss

IROS 2024poster

In this paper, we present a Radar-Inertial Odometry (RIO) method based on the nonlinear optimization of factor graphs in a sliding window fashion. Our method makes use of a light-weight, low-power, inexpensive and commonly available hardware enabling easy deployment on small Unmanned Aerial Vehicles…

Cited by 2 Source ↗code ↗Scholar ↗