Kidnapped radar: topological radar localisation using rotationally-invariant metric learning
This paper presents a system for robust, large-scale topological localisation using Frequency-Modulated ContinuousWave (FMCW) scanning radar. We learn a metric space for embedding polar radar scans using CNN and NetVLAD architectures traditionally applied to the visual domain. However, we tailor the...
Main Authors: | Gadd, M, Sǎftescu, Ş, De Martini, D, Barnes, D, Newman, P |
---|---|
Format: | Conference item |
Sprog: | English |
Udgivet: |
IEEE Xplore
2020
|
Lignende værker
-
kRadar++: coarse-to-fine FMCW scanning radar localisation
af: De Martini, D, et al.
Udgivet: (2020) -
Look around you: sequence-based radar place recognition with learned rotational invariance
af: Gadd, M, et al.
Udgivet: (2020) -
kRadar++: Coarse-to-Fine FMCW Scanning Radar Localisation
af: Daniele De Martini, et al.
Udgivet: (2020-10-01) -
Under the radar: learning to predict robust keypoints for odometry estimation and metric localisation in radar
af: Barnes, D, et al.
Udgivet: (2020) -
RSL-Net: localising in satellite images from a radar on the ground
af: Tang, TY, et al.
Udgivet: (2020)