Alexander Krawciw — accepted AI-conference papers

2025

Radar Teach and Repeat: Architecture and Initial Field Testing

Xinyuan Qiao, Alexander Krawciw, Sven Lilge, Timothy D. Barfoot

ICRA 2025

Frequency-modulated continuous-wave (FMCW) scanning radar has emerged as an alternative to spinning LiDAR for state estimation on mobile robots. Radar's longer wavelength is less affected by small particulates, providing operational advantages in challenging environments such as dust, smoke, and fog

Cited by 11 Source ↗code ↗Scholar ↗

2025

UAV See, UGV Do: Aerial Imagery and Virtual Teach Enabling Zero-Shot Ground Vehicle Repeat

Desiree Fisker, Alexander Krawciw, Sven Lilge, Melissa Greeff, Timothy D. Barfoot

IROS 2025

This paper presents Virtual Teach and Repeat (VirT&R): an extension of the Teach and Repeat (T&R) framework that enables GPS-denied, zero-shot autonomous ground vehicle navigation in untraversed environments. VirT&R leverages aerial imagery captured for a target environment to train a Neural Radianc

Cited by 1 Source ↗Scholar ↗