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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, Tianshu Huang, Anthony Rowe +1
mmWave radars are robust to darkness and occlusions such as dust and smoke, and can directly constrain ego-velocity from a single frame via Doppler measurements, making them attrac…
cs.RO2023
Multi-Radar Inertial Odometry for 3D State Estimation using mmWave Imaging Radar
Jui-Te Huang, Ruoyang Xu, Akshay Hinduja +1
State estimation is a crucial component for the successful implementation of robotic systems, relying on sensors such as cameras, LiDAR, and IMUs. However, in real-world scenarios,…