Fast radar motion estimation with a learnt focus of attention using weak supervision
This paper is about fast motion estimation with scanning radar. We use weak supervision to train a focus of attention policy which actively down-samples the measurement stream before data association steps are undertaken. At training, we avoid laborious manual labelling by exploiting short-term sens...
Autors principals: | Aldera, R, De Martini, D, Gadd, M, Newman, p |
---|---|
Format: | Conference item |
Publicat: |
IEEE
2019
|
Ítems similars
-
What goes around: leveraging a constant-curvature motion constraint in radar odometry
per: Aldera, R, et al.
Publicat: (2022) -
RSS-Net: weakly-supervised multi-class semantic segmentation with FMCW radar
per: Kaul, P, et al.
Publicat: (2021) -
Keep off the grass: permissible driving routes from radar with weak audio supervision
per: Williams, D, et al.
Publicat: (2020) -
What could go wrong? Introspective radar odometry in challenging environments
per: Aldera, R, et al.
Publicat: (2019) -
Systems-driven improvements to radar-only ego-motion estimation
per: Aldera, R
Publicat: (2021)