Roberto Aldera — accepted AI-conference papers

2022

What Goes Around: Leveraging a Constant-Curvature Motion Constraint in Radar Odometry

Roberto Aldera, Matthew Gadd, Daniele De Martini, Paul Newman

RA-L 2022

This letter presents a method that leverages vehicle motion constraints to refine data associations in a point-based radar odometry system. By using the strong prior on how a non-holonomic robot is constrained to move smoothly through its environment, we develop the necessary framework to estimate e

Cited by 18 Source ↗Scholar ↗

2019

Fast Radar Motion Estimation with a Learnt Focus of Attention using Weak Supervision

Roberto Aldera, Daniele De Martini, Matthew Gadd, Paul Newman

ICRA 2019poster

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…

Cited by 69 Source ↗Scholar ↗