LTR² is a teach-and-repeat system that teaches with LiDAR in good conditions and repeats with 4D millimetre-wave radar, which keeps working in bad weather and smoke. A cross-modal registration network aligns sparse forward-looking radar to dense omnidirectional LiDAR using Doppler motion priors and the physics of LiDAR intensity and radar power density, and it fine-tunes itself from localisation errors without ground truth. It was tested on three robot platforms over 40+ km and 6 months, including smoke at night, with centimetre-level accuracy.
Relevance
Six months and 40 km is a real long-term deployment, and teaching with one sensor and repeating with another suits mixed teams. Read for long-term autonomy and multimodal perception.