3 papers
cs.RO2026
Millimeter Wave Radar: From Synthetic Aperture to Probabilistic Mapping
Jui-Te Huang, Ruoyang Xu, Michael Kaess
Robust probabilistic mapping is essential for autonomous robotic systems operating in challenging environments. While traditional sensors fail in adverse conditions such as smoke a…
cs.RO2026
UNRIO: Uncertainty-Aware Velocity Learning for Radar-Inertial Odometry
Jui-Te Huang, Tinashu Huang, Anthony Rowe +1
We present UNRIO, an uncertainty-aware radar-inertial odometry system that estimates ego-velocity directly from raw mmWave radar IQ signals rather than processed point clouds. Exis…
cs.RO2024
BEVLoc: Cross-View Localization and Matching via Birds-Eye-View Synthesis
Christopher Klammer, Michael Kaess
Ground to aerial matching is a crucial and challenging task in outdoor robotics, particularly when GPS is absent or unreliable. Structures like buildings or large dense forests cre…